diff --git a/docs/adapters/nebius.md b/docs/adapters/nebius.md
new file mode 100644
index 00000000..bda488da
--- /dev/null
+++ b/docs/adapters/nebius.md
@@ -0,0 +1,271 @@
+---
+title: Nebius Token Factory
+id: nebius-adapter
+order: 5
+---
+
+The Nebius Token Factory adapter provides access to various LLMs hosted on Nebius Token Factory, including DeepSeek, Llama, Qwen, and more. Nebius Token Factory offers an OpenAI-compatible API, making it easy to use these models with TanStack AI.
+
+## Installation
+
+```bash
+npm install @tanstack/ai-nebius
+```
+
+## Basic Usage
+
+```typescript
+import { chat } from "@tanstack/ai";
+import { nebiusText } from "@tanstack/ai-nebius";
+
+const stream = chat({
+  adapter: nebiusText("deepseek-ai/DeepSeek-R1-0528"),
+  messages: [{ role: "user", content: "Hello!" }],
+});
+```
+
+## Basic Usage - Custom API Key
+
+```typescript
+import { chat } from "@tanstack/ai";
+import { createNebiusChat } from "@tanstack/ai-nebius";
+
+const adapter = createNebiusChat(
+  "deepseek-ai/DeepSeek-R1-0528",
+  "your-api-key-here"
+);
+
+const stream = chat({
+  adapter,
+  messages: [{ role: "user", content: "Hello!" }],
+});
+```
+
+## Configuration
+
+```typescript
+import { createNebiusChat } from "@tanstack/ai-nebius";
+
+// With explicit API key
+const adapter = createNebiusChat("deepseek-ai/DeepSeek-R1-0528", "your-api-key");
+
+// With custom base URL (optional, defaults to Nebius endpoint)
+const adapter = createNebiusChat(
+  "deepseek-ai/DeepSeek-R1-0528",
+  "your-api-key",
+  { baseURL: "https://api.tokenfactory.nebius.com/v1/" }
+);
+```
+
+## Available Models
+
+Nebius Token Factory offers a variety of models. You can use any model name as a string, but here are some popular options:
+
+### DeepSeek Models
+- `deepseek-ai/DeepSeek-R1-0528` - DeepSeek R1 reasoning model
+- `deepseek-ai/DeepSeek-V3-0324` - DeepSeek V3 model
+
+### Llama Models
+- `meta-llama/Meta-Llama-3.1-70B-Instruct` - Llama 3.1 70B
+- `meta-llama/Meta-Llama-3.1-8B-Instruct` - Llama 3.1 8B
+- `meta-llama/Meta-Llama-3.1-405B-Instruct` - Llama 3.1 405B
+
+### Qwen Models
+- `Qwen/Qwen2.5-72B-Instruct` - Qwen 2.5 72B
+- `Qwen/Qwen2.5-7B-Instruct` - Qwen 2.5 7B
+- `Qwen/Qwen2.5-32B-Instruct` - Qwen 2.5 32B
+
+To see all available models, check the [Nebius Token Factory documentation](https://docs.tokenfactory.nebius.com/ai-models-inference/overview).
+
+## Example: Chat Completion
+
+```typescript
+import { chat, toStreamResponse } from "@tanstack/ai";
+import { nebiusText } from "@tanstack/ai-nebius";
+
+export async function POST(request: Request) {
+  const { messages } = await request.json();
+
+  const stream = chat({
+    adapter: nebiusText("deepseek-ai/DeepSeek-R1-0528"),
+    messages,
+  });
+
+  return toStreamResponse(stream);
+}
+```
+
+## Example: With Tools
+
+```typescript
+import { chat, toolDefinition } from "@tanstack/ai";
+import { nebiusText } from "@tanstack/ai-nebius";
+import { z } from "zod";
+
+const getWeatherDef = toolDefinition({
+  name: "get_weather",
+  description: "Get the current weather",
+  inputSchema: z.object({
+    location: z.string(),
+  }),
+});
+
+const getWeather = getWeatherDef.server(async ({ location }) => {
+  // Fetch weather data
+  return { temperature: 72, conditions: "sunny" };
+});
+
+const stream = chat({
+  adapter: nebiusText("deepseek-ai/DeepSeek-R1-0528"),
+  messages,
+  tools: [getWeather],
+});
+```
+
+**Note:** Tool support varies by model. Models like DeepSeek R1, Llama 3.1, and Qwen 2.5 generally have good tool calling support.
+
+## Model Options
+
+Nebius supports various provider-specific options compatible with OpenAI's chat completions API:
+
+```typescript
+const stream = chat({
+  adapter: nebiusText("deepseek-ai/DeepSeek-R1-0528"),
+  messages,
+  modelOptions: {
+    temperature: 0.7,
+    top_p: 0.9,
+    max_tokens: 1000,
+    presence_penalty: 0.5,
+    frequency_penalty: 0.5,
+    stop: ["END"],
+  },
+});
+```
+
+### Available Options
+
+```typescript
+modelOptions: {
+  // Sampling
+  temperature: 0.7,        // 0-2, controls randomness
+  top_p: 0.9,              // 0-1, nucleus sampling
+  
+  // Generation
+  max_tokens: 1000,        // Maximum tokens to generate
+  stop: ["END"],           // Stop sequences (string or array)
+  
+  // Penalties
+  presence_penalty: 0.5,   // -2.0 to 2.0
+  frequency_penalty: 0.5,  // -2.0 to 2.0
+  
+  // Advanced
+  logit_bias: {},          // Logit bias map
+  user: "user-123",        // User identifier
+}
+```
+
+## Summarization
+
+Summarize long text content:
+
+```typescript
+import { summarize } from "@tanstack/ai";
+import { nebiusSummarize } from "@tanstack/ai-nebius";
+
+const result = await summarize({
+  adapter: nebiusSummarize("deepseek-ai/DeepSeek-R1-0528"),
+  text: "Your long text to summarize...",
+  maxLength: 100,
+  style: "concise", // "concise" | "bullet-points" | "paragraph"
+});
+
+console.log(result.summary);
+```
+
+## Getting Started with Nebius Token Factory
+
+### 1. Create an Account
+
+Visit [Nebius Token Factory](https://tokenfactory.nebius.com) and sign up using your Google or GitHub account.
+
+### 2. Get an API Key
+
+- Navigate to the **API keys** section in your dashboard
+- Click on **Create API key**
+- Provide a name for the key
+- Save the generated API key securely
+
+### 3. Set Environment Variable
+
+```bash
+NEBIUS_API_KEY=your-api-key-here
+```
+
+## Environment Variables
+
+Optionally set the API key in environment variables:
+
+```bash
+NEBIUS_API_KEY=your-api-key-here
+```
+
+The adapter will automatically detect `NEBIUS_API_KEY` from:
+- `process.env` (Node.js)
+- `window.env` (Browser with injected env)
+
+## API Reference
+
+### `nebiusText(model, config?)`
+
+Creates a Nebius text/chat adapter using environment variables.
+
+**Parameters:**
+- `model` - The model name (e.g., 'deepseek-ai/DeepSeek-R1-0528')
+- `config.apiKey?` - Optional API key (if not provided, uses NEBIUS_API_KEY env var)
+- `config.baseURL?` - Optional base URL (defaults to Nebius endpoint)
+
+**Returns:** A Nebius text adapter instance.
+
+### `createNebiusChat(model, apiKey, config?)`
+
+Creates a Nebius text/chat adapter with an explicit API key.
+
+**Parameters:**
+- `model` - The model name
+- `apiKey` - Your Nebius API key
+- `config.baseURL?` - Optional base URL
+
+**Returns:** A Nebius text adapter instance.
+
+### `nebiusSummarize(model, config?)`
+
+Creates a Nebius summarization adapter using environment variables.
+
+**Returns:** A Nebius summarize adapter instance.
+
+### `createNebiusSummarize(model, apiKey, config?)`
+
+Creates a Nebius summarization adapter with an explicit API key.
+
+**Returns:** A Nebius summarize adapter instance.
+
+## Benefits of Nebius Token Factory
+
+- ✅ **Multiple Models** - Access to DeepSeek, Llama, Qwen, and more
+- ✅ **OpenAI-Compatible** - Familiar API interface
+- ✅ **Cost-Effective** - Competitive pricing for inference
+- ✅ **Scalable** - Enterprise-grade infrastructure
+- ✅ **Easy Integration** - Drop-in replacement for OpenAI-compatible workflows
+
+## Limitations
+
+- **Image Generation**: Nebius Token Factory does not support image generation. Use OpenAI or Gemini for image generation.
+- **Model Availability**: Available models may vary. Check the [Nebius documentation](https://docs.tokenfactory.nebius.com/ai-models-inference/overview) for current offerings.
+
+## Next Steps
+
+- [Getting Started](../getting-started/quick-start) - Learn the basics
+- [Tools Guide](../guides/tools) - Learn about tools
+- [Other Adapters](./openai) - Explore other providers
+
diff --git a/docs/config.json b/docs/config.json
index 375489c0..1eb05f83 100644
--- a/docs/config.json
+++ b/docs/config.json
@@ -139,6 +139,10 @@
         {
           "label": "Ollama",
           "to": "adapters/ollama"
+        },
+        {
+          "label": "Nebius Token Factory",
+          "to": "adapters/nebius"
         }
       ]
     },
diff --git a/knip.json b/knip.json
index 8f2913dc..04f475c9 100644
--- a/knip.json
+++ b/knip.json
@@ -27,6 +27,14 @@
     "packages/typescript/ai-openai": {
       "ignore": ["src/tools/**"]
     },
+    "packages/typescript/ai-solid": {
+      "tsdown": false,
+      "ignore": ["tsdown.config.ts"]
+    },
+    "packages/typescript/ai-vue": {
+      "tsdown": false,
+      "ignore": ["tsdown.config.ts"]
+    },
     "packages/typescript/ai-vue-ui": {
       "ignoreDependencies": [
         "@crazydos/vue-markdown",
diff --git a/package.json b/package.json
index 27baecb6..3f4b5321 100644
--- a/package.json
+++ b/package.json
@@ -33,7 +33,7 @@
     "format": "prettier --experimental-cli --ignore-unknown '**/*' --write",
     "generate-docs": "node scripts/generate-docs.ts && pnpm run copy:readme",
     "sync-docs-config": "node scripts/sync-docs-config.ts",
-    "copy:readme": "cp README.md packages/typescript/ai/README.md && cp README.md packages/typescript/ai-devtools/README.md && cp README.md packages/typescript/ai-client/README.md && cp README.md packages/typescript/ai-gemini/README.md && cp README.md packages/typescript/ai-ollama/README.md && cp README.md packages/typescript/ai-openai/README.md && cp README.md packages/typescript/ai-react/README.md && cp README.md packages/typescript/ai-react-ui/README.md && cp README.md packages/typescript/react-ai-devtools/README.md && cp README.md packages/typescript/solid-ai-devtools/README.md",
+    "copy:readme": "cp README.md packages/typescript/ai/README.md && cp README.md packages/typescript/ai-devtools/README.md && cp README.md packages/typescript/ai-client/README.md && cp README.md packages/typescript/ai-gemini/README.md && cp README.md packages/typescript/ai-ollama/README.md && cp README.md packages/typescript/ai-openai/README.md && cp README.md packages/typescript/ai-react/README.md && cp README.md packages/typescript/ai-react-ui/README.md && cp README.md packages/typescript/react-ai-devtools/README.md && cp README.md packages/typescript/solid-ai-devtools/README.md ",
     "changeset": "changeset",
     "changeset:publish": "changeset publish",
     "changeset:version": "changeset version && pnpm install --no-frozen-lockfile && pnpm format"
diff --git a/packages/typescript/ai-nebius/CHANGELOG.md b/packages/typescript/ai-nebius/CHANGELOG.md
new file mode 100644
index 00000000..bba4f305
--- /dev/null
+++ b/packages/typescript/ai-nebius/CHANGELOG.md
@@ -0,0 +1,12 @@
+# @tanstack/ai-nebius
+
+## 0.2.0
+
+### Minor Changes
+
+- Initial release of Nebius Token Factory adapter for TanStack AI
+  - Text/chat adapter with streaming support
+  - Summarization adapter
+  - Tool/function calling support
+  - OpenAI-compatible API using `https://api.tokenfactory.nebius.com/v1/`
+  - Support for DeepSeek, Llama, Qwen models
diff --git a/packages/typescript/ai-nebius/README.md b/packages/typescript/ai-nebius/README.md
new file mode 100644
index 00000000..7d6922a9
--- /dev/null
+++ b/packages/typescript/ai-nebius/README.md
@@ -0,0 +1,25 @@
+# @tanstack/ai-nebius
+
+Nebius Token Factory adapter for TanStack AI.
+
+## Installation
+
+```bash
+npm install @tanstack/ai-nebius
+```
+
+## Usage
+
+```typescript
+import { chat } from '@tanstack/ai'
+import { nebiusText } from '@tanstack/ai-nebius'
+
+const stream = chat({
+  adapter: nebiusText('deepseek-ai/DeepSeek-R1-0528'),
+  messages: [{ role: 'user', content: 'Hello!' }],
+})
+```
+
+## Documentation
+
+See the [Nebius Token Factory adapter documentation](../../../docs/adapters/nebius.md) for full details.
diff --git a/packages/typescript/ai-nebius/package.json b/packages/typescript/ai-nebius/package.json
new file mode 100644
index 00000000..6c417b12
--- /dev/null
+++ b/packages/typescript/ai-nebius/package.json
@@ -0,0 +1,56 @@
+{
+  "name": "@tanstack/ai-nebius",
+  "version": "0.2.0",
+  "description": "Nebius Token Factory adapter for TanStack AI",
+  "author": "",
+  "license": "MIT",
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/TanStack/ai.git",
+    "directory": "packages/typescript/ai-nebius"
+  },
+  "type": "module",
+  "module": "./dist/esm/index.js",
+  "types": "./dist/esm/index.d.ts",
+  "exports": {
+    ".": {
+      "types": "./dist/esm/index.d.ts",
+      "import": "./dist/esm/index.js"
+    }
+  },
+  "files": [
+    "dist",
+    "src"
+  ],
+  "scripts": {
+    "build": "vite build",
+    "clean": "premove ./build ./dist",
+    "lint:fix": "eslint ./src --fix",
+    "test:build": "publint --strict",
+    "test:eslint": "eslint ./src",
+    "test:lib": "vitest run",
+    "test:lib:dev": "pnpm test:lib --watch",
+    "test:types": "tsc"
+  },
+  "keywords": [
+    "ai",
+    "nebius",
+    "token-factory",
+    "deepseek",
+    "llama",
+    "qwen",
+    "tanstack",
+    "adapter"
+  ],
+  "dependencies": {
+    "openai": "^6.9.1"
+  },
+  "devDependencies": {
+    "@vitest/coverage-v8": "4.0.14",
+    "vite": "^7.2.7"
+  },
+  "peerDependencies": {
+    "@tanstack/ai": "workspace:^",
+    "zod": "^4.0.0"
+  }
+}
diff --git a/packages/typescript/ai-nebius/src/adapters/summarize.ts b/packages/typescript/ai-nebius/src/adapters/summarize.ts
new file mode 100644
index 00000000..ece6dd7d
--- /dev/null
+++ b/packages/typescript/ai-nebius/src/adapters/summarize.ts
@@ -0,0 +1,187 @@
+import { BaseSummarizeAdapter } from '@tanstack/ai/adapters'
+import { NebiusTextAdapter } from './text'
+import type {
+  StreamChunk,
+  SummarizationOptions,
+  SummarizationResult,
+} from '@tanstack/ai'
+
+/**
+ * Nebius models suitable for summarization
+ * Note: Nebius models are dynamically available, this is a common subset
+ */
+export const NebiusSummarizeModels = [
+  'deepseek-ai/DeepSeek-R1-0528',
+  'deepseek-ai/DeepSeek-V3-0324',
+  'meta-llama/Meta-Llama-3.1-70B-Instruct',
+  'meta-llama/Meta-Llama-3.1-8B-Instruct',
+  'Qwen/Qwen2.5-72B-Instruct',
+  'Qwen/Qwen2.5-7B-Instruct',
+] as const
+
+export type NebiusSummarizeModel =
+  | (typeof NebiusSummarizeModels)[number]
+  | (string & {})
+
+/**
+ * Nebius-specific provider options for summarization
+ */
+export interface NebiusSummarizeProviderOptions {
+  /** Temperature for response generation (0-2) */
+  temperature?: number
+  /** Maximum tokens in the response */
+  maxTokens?: number
+}
+
+export interface NebiusSummarizeAdapterOptions {
+  apiKey?: string
+  baseURL?: string
+}
+
+/**
+ * Nebius Summarize Adapter
+ *
+ * A thin wrapper around the text adapter that adds summarization-specific prompting.
+ * Delegates all API calls to the NebiusTextAdapter.
+ */
+export class NebiusSummarizeAdapter<
+  TModel extends NebiusSummarizeModel,
+> extends BaseSummarizeAdapter<TModel, NebiusSummarizeProviderOptions> {
+  readonly kind = 'summarize' as const
+  readonly name = 'nebius' as const
+
+  private textAdapter: NebiusTextAdapter<string>
+
+  constructor(
+    config: NebiusSummarizeAdapterOptions | undefined,
+    model: TModel,
+  ) {
+    super({}, model)
+    this.textAdapter = new NebiusTextAdapter(config, model)
+  }
+
+  async summarize(options: SummarizationOptions): Promise<SummarizationResult> {
+    const systemPrompt = this.buildSummarizationPrompt(options)
+
+    // Use the text adapter's streaming and collect the result
+    let summary = ''
+    let id = ''
+    let model = options.model
+    let usage = { promptTokens: 0, completionTokens: 0, totalTokens: 0 }
+
+    for await (const chunk of this.textAdapter.chatStream({
+      model: options.model,
+      messages: [{ role: 'user', content: options.text }],
+      systemPrompts: [systemPrompt],
+      maxTokens: options.maxLength,
+      temperature: 0.3,
+    })) {
+      if (chunk.type === 'content') {
+        summary = chunk.content
+        id = chunk.id
+        model = chunk.model
+      }
+      if (chunk.type === 'done' && chunk.usage) {
+        usage = chunk.usage
+      }
+    }
+
+    return { id, model, summary, usage }
+  }
+
+  async *summarizeStream(
+    options: SummarizationOptions,
+  ): AsyncIterable<StreamChunk> {
+    const systemPrompt = this.buildSummarizationPrompt(options)
+
+    // Delegate directly to the text adapter's streaming
+    yield* this.textAdapter.chatStream({
+      model: options.model,
+      messages: [{ role: 'user', content: options.text }],
+      systemPrompts: [systemPrompt],
+      maxTokens: options.maxLength,
+      temperature: 0.3,
+    })
+  }
+
+  private buildSummarizationPrompt(options: SummarizationOptions): string {
+    let prompt = 'You are a professional summarizer. '
+
+    switch (options.style) {
+      case 'bullet-points':
+        prompt += 'Provide a summary in bullet point format. '
+        break
+      case 'paragraph':
+        prompt += 'Provide a summary in paragraph format. '
+        break
+      case 'concise':
+        prompt += 'Provide a very concise summary in 1-2 sentences. '
+        break
+      default:
+        prompt += 'Provide a clear and concise summary. '
+    }
+
+    if (options.focus && options.focus.length > 0) {
+      prompt += `Focus on the following aspects: ${options.focus.join(', ')}. `
+    }
+
+    if (options.maxLength) {
+      prompt += `Keep the summary under ${options.maxLength} tokens. `
+    }
+
+    return prompt
+  }
+}
+
+/**
+ * Creates a Nebius summarize adapter with explicit API key.
+ * Type resolution happens here at the call site.
+ *
+ * @param model - The model name (e.g., 'deepseek-ai/DeepSeek-R1-0528')
+ * @param apiKey - Your Nebius API key
+ * @param config - Optional additional configuration
+ * @returns Configured Nebius summarize adapter instance with resolved types
+ *
+ * @example
+ * ```typescript
+ * const adapter = createNebiusSummarize('deepseek-ai/DeepSeek-R1-0528', "your-api-key");
+ * ```
+ */
+export function createNebiusSummarize<TModel extends NebiusSummarizeModel>(
+  model: TModel,
+  apiKey: string,
+  config?: Omit<NebiusSummarizeAdapterOptions, 'apiKey'>,
+): NebiusSummarizeAdapter<TModel> {
+  return new NebiusSummarizeAdapter({ apiKey, ...config }, model)
+}
+
+/**
+ * Creates a Nebius summarize adapter with automatic API key detection from environment variables.
+ * Type resolution happens here at the call site.
+ *
+ * Looks for `NEBIUS_API_KEY` in:
+ * - `process.env` (Node.js)
+ * - `window.env` (Browser with injected env)
+ *
+ * @param model - The model name (e.g., 'deepseek-ai/DeepSeek-R1-0528')
+ * @param config - Optional configuration (excluding apiKey which is auto-detected)
+ * @returns Configured Nebius summarize adapter instance with resolved types
+ * @throws Error if NEBIUS_API_KEY is not found in environment
+ *
+ * @example
+ * ```typescript
+ * // Automatically uses NEBIUS_API_KEY from environment
+ * const adapter = nebiusSummarize('deepseek-ai/DeepSeek-R1-0528');
+ *
+ * await summarize({
+ *   adapter,
+ *   text: "Long article text..."
+ * });
+ * ```
+ */
+export function nebiusSummarize<TModel extends NebiusSummarizeModel>(
+  model: TModel,
+  config?: Omit<NebiusSummarizeAdapterOptions, 'apiKey'>,
+): NebiusSummarizeAdapter<TModel> {
+  return new NebiusSummarizeAdapter(config, model)
+}
diff --git a/packages/typescript/ai-nebius/src/adapters/text.ts b/packages/typescript/ai-nebius/src/adapters/text.ts
new file mode 100644
index 00000000..bd168324
--- /dev/null
+++ b/packages/typescript/ai-nebius/src/adapters/text.ts
@@ -0,0 +1,494 @@
+import { BaseTextAdapter } from '@tanstack/ai/adapters'
+import {
+  createNebiusClient,
+  generateId,
+  getNebiusApiKeyFromEnv,
+} from '../utils'
+import type {
+  StructuredOutputOptions,
+  StructuredOutputResult,
+} from '@tanstack/ai/adapters'
+import type OpenAI_SDK from 'openai'
+import type { StreamChunk, TextOptions, Tool } from '@tanstack/ai'
+import type {
+  NebiusImageMetadata,
+  NebiusMessageMetadataByModality,
+} from '../message-types'
+
+/**
+ * Nebius Token Factory text models
+ * Note: Nebius models are dynamically available, this is a common subset
+ */
+export const NebiusTextModels = [
+  // DeepSeek models
+  'deepseek-ai/DeepSeek-R1-0528',
+  'deepseek-ai/DeepSeek-V3-0324',
+  // Llama models
+  'meta-llama/Meta-Llama-3.1-70B-Instruct',
+  'meta-llama/Meta-Llama-3.1-8B-Instruct',
+  'meta-llama/Meta-Llama-3.1-405B-Instruct',
+  // Qwen models
+  'Qwen/Qwen2.5-72B-Instruct',
+  'Qwen/Qwen2.5-7B-Instruct',
+  'Qwen/Qwen2.5-32B-Instruct',
+] as const
+
+export type NebiusTextModel = (typeof NebiusTextModels)[number] | (string & {})
+
+/**
+ * Nebius-specific provider options
+ * Compatible with OpenAI chat completions API options
+ */
+export interface NebiusTextProviderOptions {
+  /** Temperature for sampling (0-2) */
+  temperature?: number
+  /** Top-p sampling (0-1) */
+  top_p?: number
+  /** Maximum tokens to generate */
+  max_tokens?: number
+  /** Stop sequences */
+  stop?: string | Array<string>
+  /** Presence penalty (-2.0 to 2.0) */
+  presence_penalty?: number
+  /** Frequency penalty (-2.0 to 2.0) */
+  frequency_penalty?: number
+  /** Logit bias */
+  logit_bias?: Record<string, number>
+  /** User identifier */
+  user?: string
+}
+
+export interface NebiusTextAdapterOptions {
+  apiKey?: string
+  baseURL?: string
+}
+
+/**
+ * Default input modalities for Nebius models
+ */
+type NebiusInputModalities = readonly ['text', 'image']
+
+/**
+ * Nebius Text/Chat Adapter
+ * A tree-shakeable chat adapter for Nebius Token Factory
+ *
+ * Note: Nebius supports any model name as a string since models are dynamically available.
+ * The predefined NebiusTextModels are common models but any string is accepted.
+ */
+export class NebiusTextAdapter<TModel extends string> extends BaseTextAdapter<
+  TModel,
+  NebiusTextProviderOptions,
+  NebiusInputModalities,
+  NebiusMessageMetadataByModality
+> {
+  readonly kind = 'text' as const
+  readonly name = 'nebius' as const
+
+  private client: OpenAI_SDK
+
+  constructor(config: NebiusTextAdapterOptions | undefined, model: TModel) {
+    super({}, model)
+    const apiKey = config?.apiKey || getNebiusApiKeyFromEnv()
+    this.client = createNebiusClient({
+      apiKey,
+      baseURL: config?.baseURL,
+    })
+  }
+
+  async *chatStream(options: TextOptions): AsyncIterable<StreamChunk> {
+    const requestParams = this.mapTextOptionsToNebius(options)
+
+    try {
+      const stream = await this.client.chat.completions.create({
+        ...requestParams,
+        stream: true,
+      })
+
+      yield* this.processNebiusStreamChunks(stream, options)
+    } catch (error: unknown) {
+      const err = error as Error
+      console.error('>>> chatStream: Fatal error during response creation <<<')
+      console.error('>>> Error message:', err.message)
+      console.error('>>> Error stack:', err.stack)
+      throw error
+    }
+  }
+
+  /**
+   * Generate structured output using Nebius's JSON mode.
+   * Uses response_format: { type: 'json_object' } for basic JSON mode.
+   * Note: For stricter schema validation, include the schema in the system prompt.
+   */
+  async structuredOutput(
+    options: StructuredOutputOptions<NebiusTextProviderOptions>,
+  ): Promise<StructuredOutputResult<unknown>> {
+    const { chatOptions, outputSchema } = options
+
+    const requestParams = this.mapTextOptionsToNebius(chatOptions)
+
+    try {
+      // Add schema to system prompt for better adherence
+      const systemPromptWithSchema = `You must respond with valid JSON matching this schema: ${JSON.stringify(outputSchema, null, 2)}`
+
+      // Prepend system message with schema
+      const messagesWithSchema: Array<OpenAI_SDK.Chat.Completions.ChatCompletionMessageParam> =
+        [
+          { role: 'system', content: systemPromptWithSchema },
+          ...(Array.isArray(requestParams.messages)
+            ? requestParams.messages
+            : []),
+        ]
+
+      // Make non-streaming request with JSON format
+      const response = await this.client.chat.completions.create({
+        ...requestParams,
+        messages: messagesWithSchema,
+        stream: false,
+        response_format: {
+          type: 'json_object',
+        },
+      })
+
+      const rawText = response.choices[0]!.message.content || ''
+
+      // Parse the JSON response
+      let parsed: unknown
+      try {
+        parsed = JSON.parse(rawText)
+      } catch {
+        throw new Error(
+          `Failed to parse structured output as JSON. Content: ${rawText.slice(0, 200)}${rawText.length > 200 ? '...' : ''}`,
+        )
+      }
+
+      return {
+        data: parsed,
+        rawText,
+      }
+    } catch (error: unknown) {
+      const err = error as Error
+      throw new Error(
+        `Structured output generation failed: ${err.message || 'Unknown error occurred'}`,
+      )
+    }
+  }
+
+  private async *processNebiusStreamChunks(
+    stream: AsyncIterable<OpenAI_SDK.Chat.Completions.ChatCompletionChunk>,
+    options: TextOptions,
+  ): AsyncIterable<StreamChunk> {
+    let accumulatedContent = ''
+    const timestamp = Date.now()
+    const responseId = generateId('msg')
+    let model = options.model
+    let hasEmittedToolCalls = false
+    const toolCallMetadata = new Map<
+      string,
+      { index: number; name: string; arguments: string }
+    >()
+
+    try {
+      for await (const chunk of stream) {
+        // Update model from chunk if available
+        if (chunk.model) {
+          model = chunk.model
+        }
+
+        // Handle content deltas
+        const delta = chunk.choices[0]?.delta
+        if (delta?.content) {
+          accumulatedContent += delta.content
+          yield {
+            type: 'content',
+            id: responseId,
+            model,
+            timestamp,
+            delta: delta.content,
+            content: accumulatedContent,
+            role: 'assistant',
+          }
+        }
+
+        // Handle tool call deltas
+        if (delta?.tool_calls) {
+          for (const toolCallDelta of delta.tool_calls) {
+            const toolCallId = toolCallDelta.id
+            if (!toolCallId) continue
+
+            if (!toolCallMetadata.has(toolCallId)) {
+              toolCallMetadata.set(toolCallId, {
+                index: toolCallDelta.index || 0,
+                name: toolCallDelta.function?.name || '',
+                arguments: toolCallDelta.function?.arguments || '',
+              })
+            } else {
+              const metadata = toolCallMetadata.get(toolCallId)!
+              if (toolCallDelta.function?.arguments) {
+                metadata.arguments += toolCallDelta.function.arguments
+              }
+            }
+          }
+        }
+
+        // Handle finish reason
+        const finishReason = chunk.choices[0]?.finish_reason
+        if (finishReason) {
+          // Emit any pending tool calls
+          if (toolCallMetadata.size > 0) {
+            for (const [toolCallId, metadata] of toolCallMetadata.entries()) {
+              yield {
+                type: 'tool_call',
+                id: responseId,
+                model,
+                timestamp,
+                index: metadata.index,
+                toolCall: {
+                  id: toolCallId,
+                  type: 'function',
+                  function: {
+                    name: metadata.name,
+                    arguments: metadata.arguments,
+                  },
+                },
+              }
+              hasEmittedToolCalls = true
+            }
+          }
+
+          yield {
+            type: 'done',
+            id: responseId,
+            model,
+            timestamp,
+            finishReason:
+              finishReason === 'tool_calls' || hasEmittedToolCalls
+                ? 'tool_calls'
+                : finishReason === 'length'
+                  ? 'length'
+                  : 'stop',
+            usage: chunk.usage
+              ? {
+                  promptTokens: chunk.usage.prompt_tokens || 0,
+                  completionTokens: chunk.usage.completion_tokens || 0,
+                  totalTokens: chunk.usage.total_tokens || 0,
+                }
+              : undefined,
+          }
+        }
+      }
+    } catch (error: unknown) {
+      const err = error as Error
+      yield {
+        type: 'error',
+        id: responseId,
+        model,
+        timestamp,
+        error: {
+          message: err.message || 'Unknown error occurred',
+        },
+      }
+    }
+  }
+
+  private convertToolsToNebiusFormat(
+    tools?: Array<Tool>,
+  ): Array<OpenAI_SDK.Chat.Completions.ChatCompletionTool> | undefined {
+    if (!tools || tools.length === 0) {
+      return undefined
+    }
+
+    return tools.map(
+      (tool) =>
+        ({
+          type: 'function' as const,
+          function: {
+            name: tool.name,
+            description: tool.description,
+            parameters: (tool.inputSchema ?? {
+              type: 'object',
+              properties: {},
+              required: [],
+            }) as OpenAI_SDK.FunctionParameters,
+          },
+        }) satisfies OpenAI_SDK.Chat.Completions.ChatCompletionTool,
+    )
+  }
+
+  private formatMessages(
+    messages: TextOptions['messages'],
+  ): Array<OpenAI_SDK.Chat.Completions.ChatCompletionMessageParam> {
+    return messages.map((msg) => {
+      switch (msg.role) {
+        case 'tool':
+          return {
+            role: 'tool',
+            tool_call_id: msg.toolCallId || '',
+            content:
+              typeof msg.content === 'string'
+                ? msg.content
+                : JSON.stringify(msg.content),
+          }
+
+        case 'assistant': {
+          const assistantContent: string | null =
+            typeof msg.content === 'string'
+              ? msg.content
+              : Array.isArray(msg.content)
+                ? msg.content
+                    .filter((p) => p.type === 'text')
+                    .map((p) => p.content)
+                    .join('')
+                : null
+
+          const result: OpenAI_SDK.Chat.Completions.ChatCompletionAssistantMessageParam =
+            {
+              role: 'assistant',
+              content: assistantContent || '',
+            }
+
+          // Add tool calls if present
+          if (msg.toolCalls && msg.toolCalls.length > 0) {
+            result.tool_calls = msg.toolCalls.map((toolCall) => ({
+              id: toolCall.id,
+              type: 'function',
+              function: {
+                name: toolCall.function.name,
+                arguments:
+                  typeof toolCall.function.arguments === 'string'
+                    ? toolCall.function.arguments
+                    : JSON.stringify(toolCall.function.arguments),
+              },
+            }))
+          }
+
+          return result
+        }
+
+        case 'user':
+        default: {
+          const contentParts: Array<
+            | OpenAI_SDK.Chat.Completions.ChatCompletionContentPartText
+            | OpenAI_SDK.Chat.Completions.ChatCompletionContentPartImage
+          > = []
+
+          if (typeof msg.content === 'string') {
+            contentParts.push({
+              type: 'text',
+              text: msg.content,
+            })
+          } else if (Array.isArray(msg.content)) {
+            for (const part of msg.content) {
+              if (part.type === 'text') {
+                contentParts.push({
+                  type: 'text',
+                  text: part.content,
+                })
+              } else if (part.type === 'image') {
+                const imageMetadata = part.metadata as
+                  | NebiusImageMetadata
+                  | undefined
+                contentParts.push({
+                  type: 'image_url',
+                  image_url: {
+                    url: part.source.value,
+                    detail: imageMetadata?.detail || 'auto',
+                  },
+                })
+              }
+            }
+          }
+
+          // If single text part, use string; otherwise use array
+          const firstPart = contentParts[0]
+          const useSimpleString =
+            contentParts.length === 1 &&
+            firstPart !== undefined &&
+            firstPart.type === 'text'
+
+          return {
+            role: 'user',
+            content: useSimpleString ? firstPart.text : contentParts,
+          }
+        }
+      }
+    })
+  }
+
+  private mapTextOptionsToNebius(
+    options: TextOptions,
+  ): OpenAI_SDK.Chat.Completions.ChatCompletionCreateParams {
+    const modelOptions = options.modelOptions as
+      | NebiusTextProviderOptions
+      | undefined
+
+    // Build messages array
+    const formattedMessages = this.formatMessages(options.messages)
+    const messages: Array<OpenAI_SDK.Chat.Completions.ChatCompletionMessageParam> =
+      options.systemPrompts && options.systemPrompts.length > 0
+        ? [
+            {
+              role: 'system',
+              content: options.systemPrompts.join('\n'),
+            },
+            ...formattedMessages,
+          ]
+        : formattedMessages
+
+    return {
+      model: options.model,
+      messages,
+      temperature: options.temperature ?? modelOptions?.temperature,
+      top_p: options.topP ?? modelOptions?.top_p,
+      max_tokens: options.maxTokens ?? modelOptions?.max_tokens,
+      stop: modelOptions?.stop,
+      presence_penalty: modelOptions?.presence_penalty,
+      frequency_penalty: modelOptions?.frequency_penalty,
+      logit_bias: modelOptions?.logit_bias,
+      user: modelOptions?.user,
+      tools: this.convertToolsToNebiusFormat(options.tools),
+    }
+  }
+}
+
+/**
+ * Creates a Nebius chat adapter with explicit API key.
+ * Type resolution happens here at the call site.
+ */
+export function createNebiusChat<TModel extends string>(
+  model: TModel,
+  apiKey: string,
+  config?: Omit<NebiusTextAdapterOptions, 'apiKey'>,
+): NebiusTextAdapter<TModel> {
+  return new NebiusTextAdapter({ apiKey, ...config }, model)
+}
+
+/**
+ * Creates a Nebius text adapter with automatic API key detection from environment variables.
+ * Type resolution happens here at the call site.
+ *
+ * Looks for `NEBIUS_API_KEY` in:
+ * - `process.env` (Node.js)
+ * - `window.env` (Browser with injected env)
+ *
+ * @param model - The model name (e.g., 'deepseek-ai/DeepSeek-R1-0528', 'meta-llama/Meta-Llama-3.1-70B-Instruct')
+ * @param config - Optional configuration (excluding apiKey which is auto-detected)
+ * @returns Configured Nebius text adapter instance with resolved types
+ * @throws Error if NEBIUS_API_KEY is not found in environment
+ *
+ * @example
+ * ```typescript
+ * // Automatically uses NEBIUS_API_KEY from environment
+ * const adapter = nebiusText('deepseek-ai/DeepSeek-R1-0528');
+ *
+ * const stream = chat({
+ *   adapter,
+ *   messages: [{ role: "user", content: "Hello!" }]
+ * });
+ * ```
+ */
+export function nebiusText<TModel extends string>(
+  model: TModel,
+  config?: Omit<NebiusTextAdapterOptions, 'apiKey'>,
+): NebiusTextAdapter<TModel> {
+  return new NebiusTextAdapter(config, model)
+}
diff --git a/packages/typescript/ai-nebius/src/index.ts b/packages/typescript/ai-nebius/src/index.ts
new file mode 100644
index 00000000..afecd1d1
--- /dev/null
+++ b/packages/typescript/ai-nebius/src/index.ts
@@ -0,0 +1,37 @@
+// ===========================
+// New tree-shakeable adapters
+// ===========================
+
+// Text/Chat adapter
+export {
+  NebiusTextAdapter,
+  NebiusTextModels,
+  createNebiusChat,
+  nebiusText,
+  type NebiusTextAdapterOptions,
+  type NebiusTextModel,
+  type NebiusTextProviderOptions,
+} from './adapters/text'
+
+// Summarize adapter
+export {
+  NebiusSummarizeAdapter,
+  NebiusSummarizeModels,
+  createNebiusSummarize,
+  nebiusSummarize,
+  type NebiusSummarizeAdapterOptions,
+  type NebiusSummarizeModel,
+  type NebiusSummarizeProviderOptions,
+} from './adapters/summarize'
+
+// ===========================
+// Type Exports
+// ===========================
+
+export type {
+  NebiusImageMetadata,
+  NebiusAudioMetadata,
+  NebiusVideoMetadata,
+  NebiusDocumentMetadata,
+  NebiusMessageMetadataByModality,
+} from './message-types'
diff --git a/packages/typescript/ai-nebius/src/message-types.ts b/packages/typescript/ai-nebius/src/message-types.ts
new file mode 100644
index 00000000..37689dd7
--- /dev/null
+++ b/packages/typescript/ai-nebius/src/message-types.ts
@@ -0,0 +1,68 @@
+/**
+ * Nebius Token Factory-specific metadata types for multimodal content parts.
+ * These types extend the base ContentPart metadata with Nebius-specific options.
+ *
+ * Nebius Token Factory uses OpenAI-compatible API, so metadata follows OpenAI conventions.
+ * @see https://docs.tokenfactory.nebius.com
+ */
+
+/**
+ * Metadata for Nebius image content parts.
+ * Controls how the model processes and analyzes images.
+ */
+export interface NebiusImageMetadata {
+  /**
+   * Controls how the model processes the image.
+   * - 'auto': Let the model decide based on image size and content
+   * - 'low': Use low resolution processing (faster, cheaper, less detail)
+   * - 'high': Use high resolution processing (slower, more expensive, more detail)
+   *
+   * @default 'auto'
+   */
+  detail?: 'auto' | 'low' | 'high'
+}
+
+/**
+ * Metadata for Nebius audio content parts.
+ * Placeholder for future audio support.
+ */
+export interface NebiusAudioMetadata {
+  /**
+   * The format of the audio.
+   */
+  format?: 'mp3' | 'wav' | 'flac' | 'ogg' | 'webm' | 'aac'
+}
+
+/**
+ * Metadata for Nebius video content parts.
+ * Placeholder for future video support.
+ */
+export interface NebiusVideoMetadata {
+  /**
+   * The format of the video.
+   */
+  format?: 'mp4' | 'webm'
+}
+
+/**
+ * Metadata for Nebius document content parts.
+ * Placeholder for future document support.
+ */
+export interface NebiusDocumentMetadata {
+  /**
+   * The MIME type of the document.
+   */
+  mediaType?: 'application/pdf'
+}
+
+/**
+ * Map of modality types to their Nebius-specific metadata types.
+ * Used for type inference when constructing multimodal messages.
+ */
+export interface NebiusMessageMetadataByModality {
+  text: unknown
+  image: NebiusImageMetadata
+  audio: NebiusAudioMetadata
+  video: NebiusVideoMetadata
+  document: NebiusDocumentMetadata
+}
diff --git a/packages/typescript/ai-nebius/src/utils/client.ts b/packages/typescript/ai-nebius/src/utils/client.ts
new file mode 100644
index 00000000..52407ff4
--- /dev/null
+++ b/packages/typescript/ai-nebius/src/utils/client.ts
@@ -0,0 +1,45 @@
+import OpenAI_SDK from 'openai'
+
+export interface NebiusClientConfig {
+  apiKey: string
+  baseURL?: string
+}
+
+/**
+ * Creates an OpenAI SDK client instance configured for Nebius Token Factory
+ */
+export function createNebiusClient(config: NebiusClientConfig): OpenAI_SDK {
+  return new OpenAI_SDK({
+    apiKey: config.apiKey,
+    baseURL: config.baseURL || 'https://api.tokenfactory.nebius.com/v1/',
+  })
+}
+
+/**
+ * Gets Nebius API key from environment variables
+ * @throws Error if NEBIUS_API_KEY is not found
+ */
+export function getNebiusApiKeyFromEnv(): string {
+  const env =
+    typeof globalThis !== 'undefined' && (globalThis as any).window?.env
+      ? (globalThis as any).window.env
+      : typeof process !== 'undefined'
+        ? process.env
+        : undefined
+  const key = env?.NEBIUS_API_KEY
+
+  if (!key) {
+    throw new Error(
+      'NEBIUS_API_KEY is required. Please set it in your environment variables or use the factory function with an explicit API key.',
+    )
+  }
+
+  return key
+}
+
+/**
+ * Generates a unique ID with a prefix
+ */
+export function generateId(prefix: string): string {
+  return `${prefix}-${Date.now()}-${Math.random().toString(36).substring(7)}`
+}
diff --git a/packages/typescript/ai-nebius/src/utils/index.ts b/packages/typescript/ai-nebius/src/utils/index.ts
new file mode 100644
index 00000000..89728a93
--- /dev/null
+++ b/packages/typescript/ai-nebius/src/utils/index.ts
@@ -0,0 +1,6 @@
+export {
+  createNebiusClient,
+  getNebiusApiKeyFromEnv,
+  generateId,
+  type NebiusClientConfig,
+} from './client'
diff --git a/packages/typescript/ai-nebius/tests/nebius-adapter.test.ts b/packages/typescript/ai-nebius/tests/nebius-adapter.test.ts
new file mode 100644
index 00000000..5303290e
--- /dev/null
+++ b/packages/typescript/ai-nebius/tests/nebius-adapter.test.ts
@@ -0,0 +1,485 @@
+import { describe, it, expect, beforeEach, vi } from 'vitest'
+import { chat, type Tool, type StreamChunk } from '@tanstack/ai'
+import { NebiusTextAdapter } from '../src/adapters/text'
+import type { NebiusTextProviderOptions } from '../src/adapters/text'
+
+const createAdapter = <TModel extends string>(model: TModel) =>
+  new NebiusTextAdapter({ apiKey: 'test-key' }, model)
+
+const toolArguments = JSON.stringify({ location: 'Berlin' })
+
+const weatherTool: Tool = {
+  name: 'lookup_weather',
+  description: 'Return the forecast for a location',
+}
+
+function createMockChatCompletionsStream(
+  chunks: Array<Record<string, unknown>>,
+): AsyncIterable<Record<string, unknown>> {
+  return {
+    async *[Symbol.asyncIterator]() {
+      for (const chunk of chunks) {
+        yield chunk
+      }
+    },
+  }
+}
+
+describe('Nebius adapter', () => {
+  beforeEach(() => {
+    vi.clearAllMocks()
+  })
+
+  describe('option mapping', () => {
+    it('maps options into the Chat Completions API payload', async () => {
+      // Mock the Chat Completions API stream format
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          object: 'chat.completion.chunk',
+          created: 1234567890,
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: 'It is sunny' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          object: 'chat.completion.chunk',
+          created: 1234567890,
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'stop',
+            },
+          ],
+          usage: {
+            prompt_tokens: 12,
+            completion_tokens: 4,
+            total_tokens: 16,
+          },
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('deepseek-ai/DeepSeek-R1-0528')
+      // Replace the internal OpenAI SDK client with our mock
+      ;(adapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      const modelOptions: NebiusTextProviderOptions = {
+        presence_penalty: 0.5,
+        frequency_penalty: 0.3,
+      }
+
+      const chunks: StreamChunk[] = []
+      for await (const chunk of chat({
+        adapter,
+        messages: [
+          { role: 'system', content: 'Stay concise' },
+          { role: 'user', content: 'How is the weather?' },
+        ],
+        tools: [weatherTool],
+        temperature: 0.25,
+        topP: 0.6,
+        maxTokens: 1024,
+        modelOptions,
+      })) {
+        chunks.push(chunk)
+      }
+
+      expect(chatCompletionsCreate).toHaveBeenCalledTimes(1)
+      const [payload] = chatCompletionsCreate.mock.calls[0]
+
+      // Verify Chat Completions API format
+      expect(payload).toMatchObject({
+        model: 'deepseek-ai/DeepSeek-R1-0528',
+        temperature: 0.25,
+        top_p: 0.6,
+        max_tokens: 1024,
+        stream: true,
+        presence_penalty: 0.5,
+        frequency_penalty: 0.3,
+      })
+
+      // Verify messages are included
+      expect(payload.messages).toBeDefined()
+      expect(Array.isArray(payload.messages)).toBe(true)
+
+      // Verify tools are included
+      expect(payload.tools).toBeDefined()
+      expect(Array.isArray(payload.tools)).toBe(true)
+      expect(payload.tools.length).toBeGreaterThan(0)
+    })
+  })
+
+  describe('streaming', () => {
+    it('handles content streaming correctly', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: 'Hello' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: { content: ' world!' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'stop',
+            },
+          ],
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('meta-llama/Meta-Llama-3.1-70B-Instruct')
+      ;(adapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      const chunks: StreamChunk[] = []
+      for await (const chunk of chat({
+        adapter,
+        messages: [{ role: 'user', content: 'Say hello!' }],
+      })) {
+        chunks.push(chunk)
+      }
+
+      // Should have content chunks plus done chunk
+      expect(chunks.length).toBeGreaterThanOrEqual(2)
+
+      // Find content chunks
+      const contentChunks = chunks.filter((c) => c.type === 'content')
+      expect(contentChunks.length).toBe(2)
+
+      // Verify accumulated content
+      const lastContentChunk = contentChunks[contentChunks.length - 1]
+      if (lastContentChunk.type === 'content') {
+        expect(lastContentChunk.content).toBe('Hello world!')
+      }
+
+      // Verify done chunk
+      const doneChunk = chunks.find((c) => c.type === 'done')
+      expect(doneChunk).toBeDefined()
+      if (doneChunk?.type === 'done') {
+        expect(doneChunk.finishReason).toBe('stop')
+      }
+    })
+  })
+
+  describe('tool calls', () => {
+    it('handles tool call streaming correctly', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'Qwen/Qwen2.5-72B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: {
+                role: 'assistant',
+                content: null,
+                tool_calls: [
+                  {
+                    id: 'call_abc123',
+                    index: 0,
+                    type: 'function',
+                    function: {
+                      name: 'lookup_weather',
+                      arguments: '{"loc',
+                    },
+                  },
+                ],
+              },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'Qwen/Qwen2.5-72B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: {
+                tool_calls: [
+                  {
+                    id: 'call_abc123',
+                    index: 0,
+                    function: {
+                      arguments: 'ation":"Berlin"}',
+                    },
+                  },
+                ],
+              },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'Qwen/Qwen2.5-72B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'tool_calls',
+            },
+          ],
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('Qwen/Qwen2.5-72B-Instruct')
+      ;(adapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      const chunks: StreamChunk[] = []
+      for await (const chunk of chat({
+        adapter,
+        messages: [{ role: 'user', content: 'What is the weather in Berlin?' }],
+        tools: [weatherTool],
+      })) {
+        chunks.push(chunk)
+      }
+
+      // Find tool call chunk
+      const toolCallChunk = chunks.find((c) => c.type === 'tool_call')
+      expect(toolCallChunk).toBeDefined()
+      if (toolCallChunk?.type === 'tool_call') {
+        expect(toolCallChunk.toolCall.function.name).toBe('lookup_weather')
+        expect(toolCallChunk.toolCall.function.arguments).toContain('Berlin')
+      }
+
+      // Verify done chunk with tool_calls finish reason
+      const doneChunk = chunks.find((c) => c.type === 'done')
+      expect(doneChunk).toBeDefined()
+      if (doneChunk?.type === 'done') {
+        expect(doneChunk.finishReason).toBe('tool_calls')
+      }
+    })
+  })
+
+  describe('message formatting', () => {
+    it('handles conversation with tool results', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: 'The temperature is 72°F' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'stop',
+            },
+          ],
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('deepseek-ai/DeepSeek-R1-0528')
+      ;(adapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      const chunks: StreamChunk[] = []
+      for await (const chunk of chat({
+        adapter,
+        messages: [
+          { role: 'user', content: 'What is the weather in Berlin?' },
+          {
+            role: 'assistant',
+            content: null,
+            toolCalls: [
+              {
+                id: 'call_weather',
+                type: 'function',
+                function: { name: 'lookup_weather', arguments: toolArguments },
+              },
+            ],
+          },
+          { role: 'tool', toolCallId: 'call_weather', content: '{"temp":72}' },
+        ],
+      })) {
+        chunks.push(chunk)
+      }
+
+      expect(chatCompletionsCreate).toHaveBeenCalledTimes(1)
+      const [payload] = chatCompletionsCreate.mock.calls[0]
+
+      // Verify messages include user, assistant with tool calls, and tool result
+      expect(payload.messages.length).toBe(3)
+
+      // Verify tool message format
+      const toolMessage = payload.messages.find(
+        (m: Record<string, unknown>) => m.role === 'tool',
+      )
+      expect(toolMessage).toBeDefined()
+      expect(toolMessage.tool_call_id).toBe('call_weather')
+      expect(toolMessage.content).toBe('{"temp":72}')
+    })
+  })
+
+  describe('multimodal content', () => {
+    it('handles image content in messages', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: 'I see a cat.' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'stop',
+            },
+          ],
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('meta-llama/Meta-Llama-3.1-70B-Instruct')
+      ;(adapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      const chunks: StreamChunk[] = []
+      for await (const chunk of chat({
+        adapter,
+        messages: [
+          {
+            role: 'user',
+            content: [
+              { type: 'text', content: 'What is in this image?' },
+              {
+                type: 'image',
+                source: {
+                  type: 'url',
+                  value: 'https://example.com/cat.jpg',
+                },
+              },
+            ],
+          },
+        ],
+      })) {
+        chunks.push(chunk)
+      }
+
+      expect(chatCompletionsCreate).toHaveBeenCalledTimes(1)
+      const [payload] = chatCompletionsCreate.mock.calls[0]
+
+      // Verify multimodal content format
+      const userMessage = payload.messages[0]
+      expect(userMessage.role).toBe('user')
+      expect(Array.isArray(userMessage.content)).toBe(true)
+      expect(userMessage.content.length).toBe(2)
+
+      // Verify text part
+      expect(userMessage.content[0].type).toBe('text')
+      expect(userMessage.content[0].text).toBe('What is in this image?')
+
+      // Verify image part
+      expect(userMessage.content[1].type).toBe('image_url')
+      expect(userMessage.content[1].image_url.url).toBe(
+        'https://example.com/cat.jpg',
+      )
+    })
+  })
+})
+
+describe('Nebius client configuration', () => {
+  it('uses correct default base URL', () => {
+    const adapter = new NebiusTextAdapter(
+      { apiKey: 'test-key' },
+      'deepseek-ai/DeepSeek-R1-0528',
+    )
+
+    // The client should be configured with Nebius Token Factory URL
+    const client = (adapter as any).client
+    expect(client).toBeDefined()
+  })
+
+  it('allows custom base URL', () => {
+    const adapter = new NebiusTextAdapter(
+      { apiKey: 'test-key', baseURL: 'https://custom.api.com/v1/' },
+      'deepseek-ai/DeepSeek-R1-0528',
+    )
+
+    const client = (adapter as any).client
+    expect(client).toBeDefined()
+  })
+})
diff --git a/packages/typescript/ai-nebius/tests/nebius-summarize.test.ts b/packages/typescript/ai-nebius/tests/nebius-summarize.test.ts
new file mode 100644
index 00000000..7b400721
--- /dev/null
+++ b/packages/typescript/ai-nebius/tests/nebius-summarize.test.ts
@@ -0,0 +1,258 @@
+import { describe, it, expect, beforeEach, vi } from 'vitest'
+import { NebiusSummarizeAdapter } from '../src/adapters/summarize'
+import type { StreamChunk } from '@tanstack/ai'
+
+const createAdapter = <TModel extends string>(model: TModel) =>
+  new NebiusSummarizeAdapter({ apiKey: 'test-key' }, model)
+
+function createMockChatCompletionsStream(
+  chunks: Array<Record<string, unknown>>,
+): AsyncIterable<Record<string, unknown>> {
+  return {
+    async *[Symbol.asyncIterator]() {
+      for (const chunk of chunks) {
+        yield chunk
+      }
+    },
+  }
+}
+
+describe('Nebius Summarize Adapter', () => {
+  beforeEach(() => {
+    vi.clearAllMocks()
+  })
+
+  describe('summarize', () => {
+    it('generates a summary using the text adapter', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: 'This is a summary.' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'stop',
+            },
+          ],
+          usage: {
+            prompt_tokens: 100,
+            completion_tokens: 5,
+            total_tokens: 105,
+          },
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('deepseek-ai/DeepSeek-R1-0528')
+      // Mock the internal text adapter's client
+      const textAdapter = (adapter as any).textAdapter
+      ;(textAdapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      const result = await adapter.summarize({
+        model: 'deepseek-ai/DeepSeek-R1-0528',
+        text: 'This is a long article about AI and machine learning. It discusses various topics including neural networks, deep learning, and natural language processing.',
+        style: 'concise',
+        maxLength: 100,
+      })
+
+      expect(result.summary).toBe('This is a summary.')
+      expect(result.model).toBe('deepseek-ai/DeepSeek-R1-0528')
+    })
+
+    it('applies correct summarization prompt for bullet-points style', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: '• Point 1\n• Point 2' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'stop',
+            },
+          ],
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('meta-llama/Meta-Llama-3.1-70B-Instruct')
+      const textAdapter = (adapter as any).textAdapter
+      ;(textAdapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      await adapter.summarize({
+        model: 'meta-llama/Meta-Llama-3.1-70B-Instruct',
+        text: 'Long text here...',
+        style: 'bullet-points',
+      })
+
+      expect(chatCompletionsCreate).toHaveBeenCalledTimes(1)
+      const [payload] = chatCompletionsCreate.mock.calls[0]
+
+      // Verify system prompt includes bullet point instruction
+      const systemMessage = payload.messages.find(
+        (m: Record<string, unknown>) => m.role === 'system',
+      )
+      expect(systemMessage).toBeDefined()
+      expect(systemMessage.content).toContain('bullet point')
+    })
+
+    it('applies focus areas in the prompt', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'Qwen/Qwen2.5-72B-Instruct',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: 'Summary with focus' },
+              finish_reason: 'stop',
+            },
+          ],
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('Qwen/Qwen2.5-72B-Instruct')
+      const textAdapter = (adapter as any).textAdapter
+      ;(textAdapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      await adapter.summarize({
+        model: 'Qwen/Qwen2.5-72B-Instruct',
+        text: 'Long text about multiple topics...',
+        focus: ['technology', 'innovation'],
+      })
+
+      expect(chatCompletionsCreate).toHaveBeenCalledTimes(1)
+      const [payload] = chatCompletionsCreate.mock.calls[0]
+
+      // Verify focus areas are in the system prompt
+      const systemMessage = payload.messages.find(
+        (m: Record<string, unknown>) => m.role === 'system',
+      )
+      expect(systemMessage.content).toContain('technology')
+      expect(systemMessage.content).toContain('innovation')
+    })
+  })
+
+  describe('summarizeStream', () => {
+    it('streams summary content', async () => {
+      const mockStream = createMockChatCompletionsStream([
+        {
+          id: 'chatcmpl-123',
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: { role: 'assistant', content: 'This ' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: { content: 'is a summary.' },
+              finish_reason: null,
+            },
+          ],
+        },
+        {
+          id: 'chatcmpl-123',
+          model: 'deepseek-ai/DeepSeek-R1-0528',
+          choices: [
+            {
+              index: 0,
+              delta: {},
+              finish_reason: 'stop',
+            },
+          ],
+        },
+      ])
+
+      const chatCompletionsCreate = vi.fn().mockResolvedValueOnce(mockStream)
+
+      const adapter = createAdapter('deepseek-ai/DeepSeek-R1-0528')
+      const textAdapter = (adapter as any).textAdapter
+      ;(textAdapter as any).client = {
+        chat: {
+          completions: {
+            create: chatCompletionsCreate,
+          },
+        },
+      }
+
+      const chunks: StreamChunk[] = []
+      for await (const chunk of adapter.summarizeStream({
+        model: 'deepseek-ai/DeepSeek-R1-0528',
+        text: 'Long text to summarize...',
+        style: 'paragraph',
+      })) {
+        chunks.push(chunk)
+      }
+
+      // Should have content chunks plus done chunk
+      expect(chunks.length).toBeGreaterThanOrEqual(2)
+
+      // Find content chunks
+      const contentChunks = chunks.filter((c) => c.type === 'content')
+      expect(contentChunks.length).toBe(2)
+
+      // Verify accumulated content
+      const lastContentChunk = contentChunks[contentChunks.length - 1]
+      if (lastContentChunk.type === 'content') {
+        expect(lastContentChunk.content).toBe('This is a summary.')
+      }
+
+      // Verify done chunk
+      const doneChunk = chunks.find((c) => c.type === 'done')
+      expect(doneChunk).toBeDefined()
+    })
+  })
+})
diff --git a/packages/typescript/ai-nebius/tsconfig.json b/packages/typescript/ai-nebius/tsconfig.json
new file mode 100644
index 00000000..ea11c109
--- /dev/null
+++ b/packages/typescript/ai-nebius/tsconfig.json
@@ -0,0 +1,9 @@
+{
+  "extends": "../../../tsconfig.json",
+  "compilerOptions": {
+    "outDir": "dist",
+    "rootDir": "src"
+  },
+  "include": ["src/**/*.ts", "src/**/*.tsx"],
+  "exclude": ["node_modules", "dist", "**/*.config.ts"]
+}
diff --git a/packages/typescript/ai-nebius/vite.config.ts b/packages/typescript/ai-nebius/vite.config.ts
new file mode 100644
index 00000000..77bcc2e6
--- /dev/null
+++ b/packages/typescript/ai-nebius/vite.config.ts
@@ -0,0 +1,36 @@
+import { defineConfig, mergeConfig } from 'vitest/config'
+import { tanstackViteConfig } from '@tanstack/vite-config'
+import packageJson from './package.json'
+
+const config = defineConfig({
+  test: {
+    name: packageJson.name,
+    dir: './',
+    watch: false,
+    globals: true,
+    environment: 'node',
+    include: ['tests/**/*.test.ts'],
+    coverage: {
+      provider: 'v8',
+      reporter: ['text', 'json', 'html', 'lcov'],
+      exclude: [
+        'node_modules/',
+        'dist/',
+        'tests/',
+        '**/*.test.ts',
+        '**/*.config.ts',
+        '**/types.ts',
+      ],
+      include: ['src/**/*.ts'],
+    },
+  },
+})
+
+export default mergeConfig(
+  config,
+  tanstackViteConfig({
+    entry: ['./src/index.ts'],
+    srcDir: './src',
+    cjs: false,
+  }),
+)
diff --git a/packages/typescript/ai-nebius/vitest.config.ts b/packages/typescript/ai-nebius/vitest.config.ts
new file mode 100644
index 00000000..fa253174
--- /dev/null
+++ b/packages/typescript/ai-nebius/vitest.config.ts
@@ -0,0 +1,22 @@
+import { defineConfig } from 'vitest/config'
+
+export default defineConfig({
+  test: {
+    globals: true,
+    environment: 'node',
+    include: ['tests/**/*.test.ts'],
+    coverage: {
+      provider: 'v8',
+      reporter: ['text', 'json', 'html', 'lcov'],
+      exclude: [
+        'node_modules/',
+        'dist/',
+        'tests/',
+        '**/*.test.ts',
+        '**/*.config.ts',
+        '**/types.ts',
+      ],
+      include: ['src/**/*.ts'],
+    },
+  },
+})
diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml
index c3ed56e5..0e6a8d8a 100644
--- a/pnpm-lock.yaml
+++ b/pnpm-lock.yaml
@@ -695,6 +695,25 @@ importers:
         specifier: ^7.2.7
         version: 7.2.7(@types/node@25.0.1)(jiti@2.6.1)(lightningcss@1.30.2)(terser@5.44.1)(tsx@4.21.0)(yaml@2.8.2)
 
+  packages/typescript/ai-nebius:
+    dependencies:
+      '@tanstack/ai':
+        specifier: workspace:^
+        version: link:../ai
+      openai:
+        specifier: ^6.9.1
+        version: 6.10.0(ws@8.18.3)(zod@4.2.1)
+      zod:
+        specifier: ^4.0.0
+        version: 4.2.1
+    devDependencies:
+      '@vitest/coverage-v8':
+        specifier: 4.0.14
+        version: 4.0.14(vitest@4.0.15(@types/node@25.0.1)(happy-dom@20.0.11)(jiti@2.6.1)(jsdom@27.3.0(postcss@8.5.6))(lightningcss@1.30.2)(terser@5.44.1)(tsx@4.21.0)(yaml@2.8.2))
+      vite:
+        specifier: ^7.2.7
+        version: 7.2.7(@types/node@25.0.1)(jiti@2.6.1)(lightningcss@1.30.2)(terser@5.44.1)(tsx@4.21.0)(yaml@2.8.2)
+
   packages/typescript/ai-ollama:
     dependencies:
       '@tanstack/ai':
@@ -13736,6 +13755,11 @@ snapshots:
       ws: 8.18.3
       zod: 4.1.13
 
+  openai@6.10.0(ws@8.18.3)(zod@4.2.1):
+    optionalDependencies:
+      ws: 8.18.3
+      zod: 4.2.1
+
   optionator@0.9.4:
     dependencies:
       deep-is: 0.1.4