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. | — | 70B |
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 | 128k |
| 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. | $0.40Mistral | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $2.00Mistral | — |
| $180Mistral · zdr | — | |
| Overview | ||
| Company | Mistral | NVIDIA |
| Release date | May 7 2025 | Oct 15 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
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Mistral Medium 3 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Llama 3.1 Nemotron 70B shipped 204 days before Mistral Medium 3, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (Mistral Medium 3) vs 128k (Llama 3.1 Nemotron 70B). Mistral Medium 3 is closed, while Llama 3.1 Nemotron 70B is open weight.
Direct benchmark comparisons are unavailable — Mistral Medium 3 and Llama 3.1 Nemotron 70B don't publish scores on any of the same benchmarks.