Devstral Small 2 24B
devstral-small-2-24b
🇮🇹 Italy
Mistral AI's model for programming (December 2025): it reads a project, calls your functions and edits several files. A European alternative to the two Qwen coders. It reads images too. Context of 131,072 tokens, 8-bit FP8 weights by Mistral AI. Runs on NVIDIA L40S, in Italy. In service.
At a glance
| Publisher | Mistral AI |
|---|---|
| Architecture | Dense, 24 billion parameters |
| Licence | Apache 2.0 |
| Precision | FP8, 8 bits, as released by Mistral AI |
| Context | 131,072 tokens, prompt and answer together |
| Longest answer | max_tokens up to 32,768 |
| Reads | Text |
| Calls tools | Yes |
| JSON schema | Yes |
| Reasons | No, as served: it answers straight away. |
| Runs in | 🇮🇹 Italy |
| Status | Loaded: the first request answers without a start-up wait. Live state on Status. |
Use it
curl https://api.ai.itsincom.org/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "devstral-small-2-24b",
"messages": [{"role": "user", "content": "Summarise in one line: the meeting moves to Thursday at 10."}]
}'
import os
from openai import OpenAI
client = OpenAI(base_url="https://api.ai.itsincom.org/v1", api_key=os.environ["API_KEY"])
answer = client.chat.completions.create(
model="devstral-small-2-24b",
messages=[{"role": "user", "content": "Summarise in one line: the meeting moves to Thursday at 10."}],
)
print(answer.choices[0].message.content)
More in Quickstart and Chat completions.
Limits
- Prompt and answer together stay within 131,072 tokens; beyond that the engine refuses the request with a
400that says so. - Text only: a request with an image gets a
400. - A request goes only to the zones your key allows; if the model has no machine there now, a
503names the zones. It is never sent elsewhere.