diff --git a/src/index.ts b/src/index.ts
index 02c9f26..3ae5fa0 100644
--- a/src/index.ts
+++ b/src/index.ts
@@ -24,6 +24,8 @@ export { getGridBounds } from './utils/grid-utils';
 export {
   LLMProvider,
   LLMResponse,
+  LocalLLMProvider,
+  LocalVisionLLMProvider,
   OpenAIProvider,
   AnthropicProvider,
   GLMProvider,
diff --git a/src/llm-provider.ts b/src/llm-provider.ts
index 9816c24..5acf2e3 100644
--- a/src/llm-provider.ts
+++ b/src/llm-provider.ts
@@ -68,6 +68,211 @@ export abstract class LLMProvider {
   }
 }
 
+/**
+ * Local OpenAI-compatible Provider (Ollama / LM Studio / llama.cpp server, etc.)
+ *
+ * This is the TypeScript equivalent of Python's LocalLLMProvider concept, but instead of
+ * embedding a full HF runtime inside Node, it calls a local HTTP server that exposes an
+ * OpenAI-compatible Chat Completions API.
+ *
+ * Examples of compatible local servers:
+ * - Ollama (OpenAI-compatible endpoint)
+ * - LM Studio (OpenAI-compatible endpoint)
+ * - llama.cpp server (OpenAI-compatible endpoint)
+ */
+export class LocalLLMProvider extends LLMProvider {
+  private _modelName: string;
+  private _baseUrl: string;
+  private _apiKey?: string;
+  private _defaultHeaders: Record<string, string>;
+  private _timeoutMs: number;
+
+  constructor(
+    options: {
+      model?: string;
+      baseUrl?: string;
+      apiKey?: string;
+      timeoutMs?: number;
+      headers?: Record<string, string>;
+    } = {}
+  ) {
+    super();
+    this._modelName = options.model ?? process.env.SENTIENCE_LOCAL_LLM_MODEL ?? 'local-model';
+    // Common defaults:
+    // - Ollama OpenAI-compatible: http://localhost:11434/v1
+    // - LM Studio: http://localhost:1234/v1
+    this._baseUrl =
+      options.baseUrl ?? process.env.SENTIENCE_LOCAL_LLM_BASE_URL ?? 'http://localhost:11434/v1';
+    this._apiKey = options.apiKey ?? process.env.SENTIENCE_LOCAL_LLM_API_KEY;
+    this._timeoutMs = options.timeoutMs ?? 60_000;
+    this._defaultHeaders = {
+      'Content-Type': 'application/json',
+      ...(options.headers ?? {}),
+    };
+    if (this._apiKey) {
+      this._defaultHeaders.Authorization = `Bearer ${this._apiKey}`;
+    }
+  }
+
+  supportsJsonMode(): boolean {
+    // Many local OpenAI-compatible servers don't reliably implement response_format=json_object.
+    return false;
+  }
+
+  get modelName(): string {
+    return this._modelName;
+  }
+
+  async generate(
+    systemPrompt: string,
+    userPrompt: string,
+    options: Record<string, any> = {}
+  ): Promise<LLMResponse> {
+    const fetchFn = (globalThis as any).fetch as typeof fetch | undefined;
+    if (!fetchFn) {
+      throw new Error(
+        'Global fetch is not available. Use Node 18+ or polyfill fetch before using LocalLLMProvider.'
+      );
+    }
+
+    const controller = new AbortController();
+    const timeoutId = setTimeout(() => controller.abort(), options.timeoutMs ?? this._timeoutMs);
+
+    const payload: any = {
+      model: this._modelName,
+      messages: [
+        ...(systemPrompt ? [{ role: 'system', content: systemPrompt }] : []),
+        { role: 'user', content: userPrompt },
+      ],
+      temperature: options.temperature ?? 0.0,
+    };
+
+    if (options.max_tokens !== undefined) payload.max_tokens = options.max_tokens;
+    if (options.top_p !== undefined) payload.top_p = options.top_p;
+
+    // Allow pass-through of server-specific fields, but avoid overriding core fields accidentally
+    const { timeoutMs: _ignoredTimeout, ...rest } = options;
+    Object.assign(payload, rest);
+
+    try {
+      const res = await fetchFn(`${this._baseUrl}/chat/completions`, {
+        method: 'POST',
+        headers: this._defaultHeaders,
+        body: JSON.stringify(payload),
+        signal: controller.signal,
+      });
+
+      const text = await res.text();
+      if (!res.ok) {
+        throw new Error(`Local LLM HTTP ${res.status}: ${text.slice(0, 500)}`);
+      }
+
+      const data = JSON.parse(text);
+      const choice = data?.choices?.[0];
+      const content = choice?.message?.content ?? '';
+      const usage = data?.usage;
+
+      return {
+        content,
+        promptTokens: usage?.prompt_tokens,
+        completionTokens: usage?.completion_tokens,
+        totalTokens: usage?.total_tokens,
+        modelName: data?.model ?? this._modelName,
+      };
+    } finally {
+      clearTimeout(timeoutId);
+    }
+  }
+}
+
+/**
+ * Local OpenAI-compatible Vision Provider.
+ *
+ * This is the TypeScript analogue of Python's LocalVisionLLMProvider, but it assumes your
+ * local server supports the OpenAI vision message format (image_url with data: URI).
+ *
+ * If your local stack uses a different schema (e.g., Ollama images array), you can implement
+ * a custom provider by extending LLMProvider.
+ */
+export class LocalVisionLLMProvider extends LocalLLMProvider {
+  supportsVision(): boolean {
+    return true;
+  }
+
+  async generateWithImage(
+    systemPrompt: string,
+    userPrompt: string,
+    imageBase64: string,
+    options: Record<string, any> = {}
+  ): Promise<LLMResponse> {
+    const fetchFn = (globalThis as any).fetch as typeof fetch | undefined;
+    if (!fetchFn) {
+      throw new Error(
+        'Global fetch is not available. Use Node 18+ or polyfill fetch before using LocalVisionLLMProvider.'
+      );
+    }
+
+    const controller = new AbortController();
+    const timeoutId = setTimeout(
+      () => controller.abort(),
+      options.timeoutMs ?? (this as any)._timeoutMs ?? 60_000
+    );
+
+    // Rebuild payload (we cannot reuse LocalLLMProvider.generate because message shape differs)
+    const modelName = (this as any)._modelName ?? 'local-model';
+    const baseUrl = (this as any)._baseUrl ?? 'http://localhost:11434/v1';
+    const headers = (this as any)._defaultHeaders ?? { 'Content-Type': 'application/json' };
+
+    const payload: any = {
+      model: modelName,
+      messages: [
+        ...(systemPrompt ? [{ role: 'system', content: systemPrompt }] : []),
+        {
+          role: 'user',
+          content: [
+            { type: 'text', text: userPrompt },
+            { type: 'image_url', image_url: { url: `data:image/png;base64,${imageBase64}` } },
+          ],
+        },
+      ],
+      temperature: options.temperature ?? 0.0,
+    };
+
+    if (options.max_tokens !== undefined) payload.max_tokens = options.max_tokens;
+    const { timeoutMs: _ignoredTimeout, ...rest } = options;
+    Object.assign(payload, rest);
+
+    try {
+      const res = await fetchFn(`${baseUrl}/chat/completions`, {
+        method: 'POST',
+        headers,
+        body: JSON.stringify(payload),
+        signal: controller.signal,
+      });
+
+      const text = await res.text();
+      if (!res.ok) {
+        throw new Error(`Local Vision LLM HTTP ${res.status}: ${text.slice(0, 500)}`);
+      }
+
+      const data = JSON.parse(text);
+      const choice = data?.choices?.[0];
+      const content = choice?.message?.content ?? '';
+      const usage = data?.usage;
+
+      return {
+        content,
+        promptTokens: usage?.prompt_tokens,
+        completionTokens: usage?.completion_tokens,
+        totalTokens: usage?.total_tokens,
+        modelName: data?.model ?? modelName,
+      };
+    } finally {
+      clearTimeout(timeoutId);
+    }
+  }
+}
+
 /**
  * OpenAI Provider (GPT-4, GPT-4o, etc.)
  * Requires: npm install openai
diff --git a/tests/local-llm-provider.test.ts b/tests/local-llm-provider.test.ts
new file mode 100644
index 0000000..a7d582c
--- /dev/null
+++ b/tests/local-llm-provider.test.ts
@@ -0,0 +1,75 @@
+import { LocalLLMProvider, LocalVisionLLMProvider } from '../src/llm-provider';
+
+describe('LocalLLMProvider (OpenAI-compatible)', () => {
+  const originalFetch = (globalThis as any).fetch;
+
+  afterEach(() => {
+    (globalThis as any).fetch = originalFetch;
+  });
+
+  it('should call /chat/completions and parse response', async () => {
+    (globalThis as any).fetch = jest.fn(async () => {
+      return {
+        ok: true,
+        status: 200,
+        text: async () =>
+          JSON.stringify({
+            model: 'local-model',
+            choices: [{ message: { content: 'hello' } }],
+            usage: { prompt_tokens: 1, completion_tokens: 2, total_tokens: 3 },
+          }),
+      };
+    });
+
+    const llm = new LocalLLMProvider({
+      baseUrl: 'http://localhost:11434/v1',
+      model: 'local-model',
+    });
+    const resp = await llm.generate('sys', 'user', { temperature: 0.0 });
+
+    expect(resp.content).toBe('hello');
+    expect(resp.modelName).toBe('local-model');
+    expect(resp.totalTokens).toBe(3);
+    expect((globalThis as any).fetch).toHaveBeenCalledTimes(1);
+    expect(((globalThis as any).fetch as any).mock.calls[0][0]).toBe(
+      'http://localhost:11434/v1/chat/completions'
+    );
+  });
+});
+
+describe('LocalVisionLLMProvider (OpenAI-compatible)', () => {
+  const originalFetch = (globalThis as any).fetch;
+
+  afterEach(() => {
+    (globalThis as any).fetch = originalFetch;
+  });
+
+  it('should send image_url message content', async () => {
+    let capturedBody: any = null;
+    (globalThis as any).fetch = jest.fn(async (_url: string, init: any) => {
+      capturedBody = JSON.parse(init.body);
+      return {
+        ok: true,
+        status: 200,
+        text: async () =>
+          JSON.stringify({
+            model: 'local-vision',
+            choices: [{ message: { content: 'YES' } }],
+            usage: { prompt_tokens: 1, completion_tokens: 1, total_tokens: 2 },
+          }),
+      };
+    });
+
+    const llm = new LocalVisionLLMProvider({
+      baseUrl: 'http://localhost:1234/v1',
+      model: 'local-vision',
+    });
+
+    const resp = await llm.generateWithImage('sys', 'is there a button?', 'AAAA', {});
+    expect(resp.content).toBe('YES');
+    expect(capturedBody.messages[1].content[1].type).toBe('image_url');
+    expect(capturedBody.messages[1].content[1].image_url.url).toContain(
+      'data:image/png;base64,AAAA'
+    );
+  });
+});