Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 8B/70B/405B | 24B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 128k | 40k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.02DeepInfra | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.04DeepInfra | — |
| $6.00DeepInfra · fp8 | — | |
| These models have no shared benchmark scores. | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 14% | — |
| Overview | ||
| Company | Meta | Mistral |
| Release date | Jul 23 2024 | Jun 10 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
LLaMA 3.1vsClaude Haiku 5.5Magistral SmallvsClaude Haiku 5.5LLaMA 3.1vsGPT-6.1 SolMagistral SmallvsGPT-6.1 SolLLaMA 3.1vsGemini 4 ArgonMagistral SmallvsGemini 4 ArgonLLaMA 3.1vsGrok 4.7Magistral SmallvsGrok 4.7LLaMA 3.1vsDeepSeek-V4.1-Flash-1017Magistral SmallvsDeepSeek-V4.1-Flash-1017LLaMA 3.1vsKimi K3Magistral SmallvsKimi K3Frequently asked questions
LLaMA 3.1 and Magistral Small don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 3.1 shipped 322 days before Magistral Small, so benchmark comparisons should account for the intervening progress.
LLaMA 3.1 has 8B/70B/405B parameters, while Magistral Small has 24B. Context windows are 128k (LLaMA 3.1) vs 40k (Magistral Small). LLaMA 3.1 is open weight, while Magistral Small is closed.
Direct benchmark comparisons are unavailable — LLaMA 3.1 and Magistral Small don't publish scores on any of the same benchmarks.