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 | 397B |
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. | 256k | 1M |
| API pricingUSD per 1M tokens · lower wins · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $0.50 | $0.40 |
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 | $2.40 |
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 | $0.26Alibaba |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $1.50Mistral | $1.56Alibaba |
| $175Mistral list price | $130Alibaba | |
| 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% | — |
| Overview | ||
| Company | Mistral | Qwen |
| Release date | Dec 2 2025 | Feb 16 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Mistral Large 3vsClaude Haiku 5.5Qwen3.5-PlusvsClaude Haiku 5.5Mistral Large 3vsGPT-6.1 SolQwen3.5-PlusvsGPT-6.1 SolMistral Large 3vsGemini 4 ArgonQwen3.5-PlusvsGemini 4 ArgonMistral Large 3vsMuse Spark OpenQwen3.5-PlusvsMuse Spark OpenMistral Large 3vsGrok 4.7Qwen3.5-PlusvsGrok 4.7Mistral Large 3vsDeepSeek-V4.1-Flash-1017Qwen3.5-PlusvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mistral Large 3 and Qwen3.5-Plus don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen3.5-Plus is cheaper on input: $0.40 vs $0.50 per million tokens. Mistral Large 3 is cheaper on output: $1.50 vs $2.40 per million tokens. Figures are base-tier rates. Mistral Large 3 shipped 76 days before Qwen3.5-Plus, so benchmark comparisons should account for the intervening progress.
Mistral Large 3 has 675B parameters, while Qwen3.5-Plus has 397B. Context windows are 256k (Mistral Large 3) vs 1M (Qwen3.5-Plus). Mistral Large 3 is open weight, while Qwen3.5-Plus is closed.
Direct benchmark comparisons are unavailable — Mistral Large 3 and Qwen3.5-Plus don't publish scores on any of the same benchmarks.