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. | 141B | 7B |
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. | 64k | 2k |
| 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. | $2.00Mistral | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $6.00Mistral | — |
| $700Mistral · zdr | — | |
| Overview | ||
| Company | Mistral | Qwen |
| Release date | Apr 10 2024 | Aug 3 2023 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Mixtral 8×22BvsClaude Haiku 5.5Qwen-7BvsClaude Haiku 5.5Mixtral 8×22BvsGPT-6.1 SolQwen-7BvsGPT-6.1 SolMixtral 8×22BvsGemini 4 ArgonQwen-7BvsGemini 4 ArgonMixtral 8×22BvsMuse Spark OpenQwen-7BvsMuse Spark OpenMixtral 8×22BvsGrok 4.7Qwen-7BvsGrok 4.7Mixtral 8×22BvsDeepSeek-V4.1-Flash-1017Qwen-7BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mixtral 8×22B and Qwen-7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen-7B shipped 251 days before Mixtral 8×22B, so benchmark comparisons should account for the intervening progress.
Mixtral 8×22B has 141B parameters, while Qwen-7B has 7B. Context windows are 64k (Mixtral 8×22B) vs 2k (Qwen-7B).
Direct benchmark comparisons are unavailable — Mixtral 8×22B and Qwen-7B don't publish scores on any of the same benchmarks.