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. | 12B | 0.6B/1.7B/4B/8B/14B/30B/32B/235B |
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 · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $0.70 |
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. | — | $2.80 |
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. | — | $0.08DeepInfra |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.22NextBit |
| — | $30.00DeepInfra · fp8 | |
| 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 | Mistral | Qwen |
| Release date | Sep 11 2024 | Apr 29 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Pixtral 24.09vsClaude Haiku 5.5Qwen3vsClaude Haiku 5.5Pixtral 24.09vsGPT-6.1 SolQwen3vsGPT-6.1 SolPixtral 24.09vsGemini 4 ArgonQwen3vsGemini 4 ArgonPixtral 24.09vsMuse Spark OpenQwen3vsMuse Spark OpenPixtral 24.09vsGrok 4.7Qwen3vsGrok 4.7Pixtral 24.09vsDeepSeek-V4.1-Flash-1017Qwen3vsDeepSeek-V4.1-Flash-1017Frequently asked questions
Pixtral 24.09 and Qwen3 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Qwen3 has a verified first-party API price: $0.70 per million input tokens and $2.80 per million output tokens. No pay-as-you-go API rate is tracked for Pixtral 24.09. Pixtral 24.09 shipped 230 days before Qwen3, so benchmark comparisons should account for the intervening progress.
Pixtral 24.09 has 12B parameters, while Qwen3 has 0.6B/1.7B/4B/8B/14B/30B/32B/235B. Context windows are 128k (Pixtral 24.09) vs 128k (Qwen3).
Direct benchmark comparisons are unavailable — Pixtral 24.09 and Qwen3 don't publish scores on any of the same benchmarks.