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. | 7B | 119B |
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. | 4k | 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. | — | $0.15 |
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. | — | $0.60 |
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. | — | $0.15Mistral |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.60Mistral |
| — | $60.00Mistral 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. | — | 6% |
| Overview | ||
| Company | DeepSeek | Mistral |
| Release date | Feb 5 2024 | Mar 16 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
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DeepSeek-Math and Mistral Small 4 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Mistral Small 4 has a verified first-party API price: $0.15 per million input tokens and $0.60 per million output tokens. No pay-as-you-go API rate is tracked for DeepSeek-Math. DeepSeek-Math shipped 770 days before Mistral Small 4, so benchmark comparisons should account for the intervening progress.
DeepSeek-Math has 7B parameters, while Mistral Small 4 has 119B. Context windows are 4k (DeepSeek-Math) vs 256k (Mistral Small 4). DeepSeek-Math is open weight, while Mistral Small 4 is closed.
Direct benchmark comparisons are unavailable — DeepSeek-Math and Mistral Small 4 don't publish scores on any of the same benchmarks.