Codestral 2508 vs Llama 3.1 405B
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Codestral 2508 and Llama 3.1 405B.
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. [Blog Post](https://mistral.ai/news/codestral-25-08)
Llama 3.1 405B
Llama 3.1 405B is Meta's largest open-weight language model and one of the most capable openly available models in the world. With 405 billion parameters, it achieves performance competitive with GPT-4 and Claude Opus across benchmarks spanning general knowledge, mathematics, coding, and multilingual tasks. Llama 3.1 405B is released under Meta's custom commercial license, supporting broad use cases including deployment via major cloud providers (AWS, GCP, Azure) and self-hosted inference with multi-GPU configurations.
Technical Specifications
| Specification | Codestral 2508 | Llama 3.1 405B |
|---|---|---|
| Provider | Mistral | Meta |
| Context Window | 256,000 tokens | 131,072 tokens |
| Agent Suitability | N/A | 90/100 |
| Time to First Token (TTFT) | N/A | 550 ms |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-08-01 | 2024-07-23 |
API Pricing Comparison
Input Price per Million Tokens
Codestral 2508
$0.30
Llama 3.1 405B
$0.80
Output Price per Million Tokens
Codestral 2508
$0.90
Llama 3.1 405B
$0.80
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Codestral 2508 Quirks & Gotchas
No developer gotchas reported.
Llama 3.1 405B Quirks & Gotchas
- ▸Massive model — requires 8× A100 80GB for FP16 inference
- ▸Available via Together AI, Fireworks, and Bedrock as managed API