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. | — | 675B |
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. | 1M | 256k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $0.50 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $1.50 |
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. | — | $0.50Mistral |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $1.50Mistral |
| — | $175Mistral list price | |
| 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. | — | 2% |
Terminal-Bench 4.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Version 4.0 recalibrated how much time, CPU and memory each task gets, removed eight tasks and fixed nineteen, so fewer runs fail for reasons that have nothing to do with the model. Scores are not comparable with earlier versions. Higher is better. | 60.9% | — |
| Overview | ||
| Company | Anthropic | Mistral |
| Release date | Sep 1 2026 | Dec 2 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Claude Mythos 5.1vsGPT-6.1 SolMistral Large 3vsGPT-6.1 SolClaude Mythos 5.1vsGemini 4 ArgonMistral Large 3vsGemini 4 ArgonClaude Mythos 5.1vsMuse Spark OpenMistral Large 3vsMuse Spark OpenClaude Mythos 5.1vsGrok 4.7Mistral Large 3vsGrok 4.7Claude Mythos 5.1vsDeepSeek-V4.1-Flash-1017Mistral Large 3vsDeepSeek-V4.1-Flash-1017Claude Mythos 5.1vsKimi K3Mistral Large 3vsKimi K3Frequently asked questions
Claude Mythos 5.1 and Mistral Large 3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Mistral Large 3 has a verified first-party API price: $0.50 per million input tokens and $1.50 per million output tokens. No pay-as-you-go API rate is tracked for Claude Mythos 5.1. Mistral Large 3 shipped 273 days before Claude Mythos 5.1, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Claude Mythos 5.1) vs 256k (Mistral Large 3). Claude Mythos 5.1 is closed, while Mistral Large 3 is open weight.
Direct benchmark comparisons are unavailable — Claude Mythos 5.1 and Mistral Large 3 don't publish scores on any of the same benchmarks.