Mistral · Balanced
Codestral 2508
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation.
- Input
- Text
- Output
- Text
- Discovery tier
- Balanced
Pricing
USD per 1M tokens- Input
- $0.30
- Output
- $0.90
Reference prices as published by the model provider. API example
Specifications
- Context window
- 256K
- Max output
- 32.8K
- Average output (7 days)
- 124 tokens
- Longer than 12% of 468 models
Side by side
Codestral 2508 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Codestral 2508MistralThis model | Mistral Large 4MistralRemove | |
|---|---|---|
| Provider | Mistral | Mistral |
| Discovery tier | Balanced | Open weights |
| Added | Aug 1, 2025 | Oct 6, 2026 |
| Limits | ||
| Context window | 256K | 524.29KBest |
| Max output | 32.77K | — |
| Average output | 124 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.30Best | $0.68 |
| Output | $0.90Best | $2.09 |
| Cache read | — | $0.07 |
| Performance | ||
| Request success (24h) | — | 69.0% |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Vision | No | Yes |
| Structured output | No | Yes |
| Reasoning effort | — | none, high |
Public evaluations
Benchmarks
There are no public benchmark results for these models yet.
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "mistralai/codestral-2508",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="mistralai/codestral-2508",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Mistral
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