Compare AI models
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | — | 480B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | — | 256k |
| 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. | $0.15 | $1.00 |
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 | $5.00 |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.15Mistral | $0.22Google |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.60Mistral | $1.00DeepInfra |
| Benchmarks | ||
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% | 20% |
| Overview | ||
| Company | Mistral | Qwen |
| Release date | Mar 16 2026 | Jul 22 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
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Qwen3-Coder leads Mistral Small 4 on 1 of the 1 benchmark they both report (BullshitBench v2). Mistral Small 4 is cheaper on both input and output: $0.15 vs $1.00 per million input tokens, and $0.60 vs $5.00 per million output tokens. Figures are base-tier rates. Qwen3-Coder shipped 237 days before Mistral Small 4, so benchmark comparisons should account for the intervening progress.
Mistral Small 4 is closed, while Qwen3-Coder is open weight.
On BullshitBench v2, Qwen3-Coder leads at 20% vs Mistral Small 4 at 6%.