eurollm-9b-it
Text Generation • utter-project
@cf/utter-project/eurollm-9b-it
- Cloudflare-hosted
- Function calling
EuroLLM-9B is a 9B parameter model trained on 4 trillion tokens divided across the considered languages and several data sources: Web data, parallel data (en-xx and xx-en), and high-quality datasets. For access, please fill out this form: https://forms.gle/kgvmkr6ucHN3xNuH6
| Model Info | |
|---|---|
| Context Window ↗ | 32,000 tokens |
| Function calling ↗ | Yes |
Playground
Try out this model with Workers AI LLM Playground. It does not require any setup or authentication and is an instant way to preview and test a model directly in the browser.
Usage
export interface Env {
AI: Ai;
}
export default {
async fetch(request, env): Promise<Response> {
const messages = [
{ role: "system", content: "You are a friendly assistant" },
{
role: "user",
content: "What is the origin of the phrase Hello, World",
},
];
const stream = await env.AI.run("@cf/utter-project/eurollm-9b-it", {
messages,
stream: true,
});
return new Response(stream, {
headers: { "content-type": "text/event-stream" },
});
},
} satisfies ExportedHandler<Env>;
export interface Env {
AI: Ai;
}
export default {
async fetch(request, env): Promise<Response> {
const messages = [
{ role: "system", content: "You are a friendly assistant" },
{
role: "user",
content: "What is the origin of the phrase Hello, World",
},
];
const response = await env.AI.run("@cf/utter-project/eurollm-9b-it", { messages });
return Response.json(response);
},
} satisfies ExportedHandler<Env>;
import os
import requests
ACCOUNT_ID = "your-account-id"
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")
prompt = "Tell me all about PEP-8"
response = requests.post(
f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/utter-project/eurollm-9b-it",
headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
json={
"messages": [
{"role": "system", "content": "You are a friendly assistant"},
{"role": "user", "content": prompt}
]
}
)
result = response.json()
print(result)
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/utter-project/eurollm-9b-it \
-X POST \
-H "Authorization: Bearer $CLOUDFLARE_AUTH_TOKEN" \
-d '{ "messages": [{ "role": "system", "content": "You are a friendly assistant" }, { "role": "user", "content": "Why is pizza so good" }]}'
OpenAI compatible endpoints
Workers AI also supports OpenAI compatible API endpoints for /v1/chat/completions and /v1/embeddings. For more details, refer to Configurations .
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description: GLM-4.7-Flash is a fast and efficient multilingual text generation model with a 131,072 token context window. Optimized for dialogue, instruction-following, and multi-turn tool calling across 100+ languages. title: glm-4.7-flash image: https://developers.cloudflare.com/og-docs.png
Documentation Index
Fetch the complete documentation index at: https://developers.cloudflare.com/llms.txt
Use this file to discover all available pages before exploring further.

