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. | 8B | — |
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 | 400k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $0.15 | — |
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. | $0.15 | — |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.015 | — |
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. | $0.15Mistral | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.15Mistral | — |
| $37.50Mistral list price | — | |
| 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. | — | 32% |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Dec 2 2025 | Nov 13 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Ministral 3 8B-25-12vsClaude Fable 5.2GPT-5.1-CodexvsClaude Fable 5.2Ministral 3 8B-25-12vsGemini 4 CarbonGPT-5.1-CodexvsGemini 4 CarbonMinistral 3 8B-25-12vsMuse EmberGPT-5.1-CodexvsMuse EmberMinistral 3 8B-25-12vsGrok 4.7GPT-5.1-CodexvsGrok 4.7Ministral 3 8B-25-12vsDeepSeek-V4.1-Flash-1017GPT-5.1-CodexvsDeepSeek-V4.1-Flash-1017Ministral 3 8B-25-12vsKimi K3.1 ProGPT-5.1-CodexvsKimi K3.1 ProFrequently asked questions
Ministral 3 8B-25-12 and GPT-5.1-Codex don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Ministral 3 8B-25-12 has a verified first-party price for an available API: $0.15 per million input tokens and $0.15 per million output tokens. No currently available pay-as-you-go API rate is tracked for GPT-5.1-Codex. GPT-5.1-Codex shipped 19 days before Ministral 3 8B-25-12, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Ministral 3 8B-25-12) vs 400k (GPT-5.1-Codex). Ministral 3 8B-25-12 is open weight, while GPT-5.1-Codex is closed.
Direct benchmark comparisons are unavailable — Ministral 3 8B-25-12 and GPT-5.1-Codex don't publish scores on any of the same benchmarks.