diff --git a/src/providers/embedding/openai.ts b/src/providers/embedding/openai.ts
index 99205c6..308479f 100644
--- a/src/providers/embedding/openai.ts
+++ b/src/providers/embedding/openai.ts
@@ -4,19 +4,48 @@ import { getEnvVar } from "../../config.js";
 const DEFAULT_BASE_URL = "https://api.openai.com";
 const DEFAULT_MODEL = "text-embedding-3-small";
 
+/**
+ * Known OpenAI embedding model dimensions. Extend as new models ship.
+ * Override in any case via OPENAI_EMBEDDING_DIMENSIONS for custom or
+ * self-hosted OpenAI-compatible endpoints returning non-standard sizes.
+ */
+const MODEL_DIMENSIONS: Record<string, number> = {
+  "text-embedding-3-small": 1536,
+  "text-embedding-3-large": 3072,
+  "text-embedding-ada-002": 1536,
+};
+
+const DEFAULT_DIMENSIONS = MODEL_DIMENSIONS[DEFAULT_MODEL] ?? 1536;
+
+function resolveDimensions(model: string, override: string | undefined): number {
+  if (override !== undefined && override.trim().length > 0) {
+    const parsed = parseInt(override, 10);
+    if (!Number.isFinite(parsed) || parsed <= 0) {
+      throw new Error(
+        `OPENAI_EMBEDDING_DIMENSIONS must be a positive integer, got: ${override}`,
+      );
+    }
+    return parsed;
+  }
+  return MODEL_DIMENSIONS[model] ?? DEFAULT_DIMENSIONS;
+}
+
 /**
  * OpenAI-compatible embedding provider.
  *
  * Required env vars:
- *   OPENAI_API_KEY           — API key
+ *   OPENAI_API_KEY            — API key
  *
  * Optional:
- *   OPENAI_BASE_URL          — base URL without path (default: https://api.openai.com)
- *   OPENAI_EMBEDDING_MODEL   — model name (default: text-embedding-3-small)
+ *   OPENAI_BASE_URL           — base URL without path (default: https://api.openai.com)
+ *   OPENAI_EMBEDDING_MODEL    — model name (default: text-embedding-3-small)
+ *   OPENAI_EMBEDDING_DIMENSIONS — override reported dimensions (required for
+ *                                 custom / self-hosted models not in the
+ *                                 MODEL_DIMENSIONS table above)
  */
 export class OpenAIEmbeddingProvider implements EmbeddingProvider {
   readonly name = "openai";
-  readonly dimensions = 1536;
+  readonly dimensions: number;
   private apiKey: string;
   private baseUrl: string;
   private model: string;
@@ -28,6 +57,10 @@ export class OpenAIEmbeddingProvider implements EmbeddingProvider {
       getEnvVar("OPENAI_BASE_URL") || DEFAULT_BASE_URL;
     this.model =
       getEnvVar("OPENAI_EMBEDDING_MODEL") || DEFAULT_MODEL;
+    this.dimensions = resolveDimensions(
+      this.model,
+      getEnvVar("OPENAI_EMBEDDING_DIMENSIONS"),
+    );
   }
 
   async embed(text: string): Promise<Float32Array> {
diff --git a/test/embedding-provider.test.ts b/test/embedding-provider.test.ts
index 2cf3271..48092eb 100644
--- a/test/embedding-provider.test.ts
+++ b/test/embedding-provider.test.ts
@@ -55,6 +55,7 @@ describe("OpenAIEmbeddingProvider", () => {
     process.env = { ...originalEnv };
     delete process.env["OPENAI_BASE_URL"];
     delete process.env["OPENAI_EMBEDDING_MODEL"];
+    delete process.env["OPENAI_EMBEDDING_DIMENSIONS"];
   });
 
   afterEach(() => {
@@ -103,4 +104,48 @@ describe("OpenAIEmbeddingProvider", () => {
 
     fetchSpy.mockRestore();
   });
+
+  it("derives dimensions from model in the known-models table", () => {
+    process.env["OPENAI_EMBEDDING_MODEL"] = "text-embedding-3-large";
+    const large = new OpenAIEmbeddingProvider("test-key");
+    expect(large.dimensions).toBe(3072);
+
+    process.env["OPENAI_EMBEDDING_MODEL"] = "text-embedding-ada-002";
+    const ada = new OpenAIEmbeddingProvider("test-key");
+    expect(ada.dimensions).toBe(1536);
+
+    process.env["OPENAI_EMBEDDING_MODEL"] = "text-embedding-3-small";
+    const small = new OpenAIEmbeddingProvider("test-key");
+    expect(small.dimensions).toBe(1536);
+  });
+
+  it("OPENAI_EMBEDDING_DIMENSIONS overrides the model-derived dimensions", () => {
+    process.env["OPENAI_EMBEDDING_MODEL"] = "text-embedding-3-large";
+    process.env["OPENAI_EMBEDDING_DIMENSIONS"] = "768";
+    const provider = new OpenAIEmbeddingProvider("test-key");
+    expect(provider.dimensions).toBe(768);
+  });
+
+  it("falls back to 1536 for unknown custom models", () => {
+    process.env["OPENAI_EMBEDDING_MODEL"] = "mystery-self-hosted-model";
+    const provider = new OpenAIEmbeddingProvider("test-key");
+    expect(provider.dimensions).toBe(1536);
+  });
+
+  it("rejects invalid OPENAI_EMBEDDING_DIMENSIONS values", () => {
+    process.env["OPENAI_EMBEDDING_DIMENSIONS"] = "not-a-number";
+    expect(() => new OpenAIEmbeddingProvider("test-key")).toThrow(
+      /OPENAI_EMBEDDING_DIMENSIONS must be a positive integer/,
+    );
+
+    process.env["OPENAI_EMBEDDING_DIMENSIONS"] = "-5";
+    expect(() => new OpenAIEmbeddingProvider("test-key")).toThrow(
+      /OPENAI_EMBEDDING_DIMENSIONS must be a positive integer/,
+    );
+
+    process.env["OPENAI_EMBEDDING_DIMENSIONS"] = "0";
+    expect(() => new OpenAIEmbeddingProvider("test-key")).toThrow(
+      /OPENAI_EMBEDDING_DIMENSIONS must be a positive integer/,
+    );
+  });
 });