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. | 14B | — |
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. | $0.20 | $12.50 |
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. | $0.20 | $75.00 |
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. | $0.02 | $1.25 |
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. | $0.20Mistral | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.20Mistral | — |
| $50.00Mistral list price | $6,250OpenAI list price | |
| These models have no shared benchmark scores. | ||
Advanced Cybersecurity Completion Rate (Internal)Agentic tasks — share of advanced cyber requests the model responds to; measures willingness to answer, not exploit success | — | 95% |
| Overview | ||
| Company | Mistral | OpenAI |
| Release date | Dec 2 2025 | Aug 10 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Ministral 3 14B-25-12vsClaude Fable 5.2GPT-5.6 CybervsClaude Fable 5.2Ministral 3 14B-25-12vsGemini 4 CarbonGPT-5.6 CybervsGemini 4 CarbonMinistral 3 14B-25-12vsMuse EmberGPT-5.6 CybervsMuse EmberMinistral 3 14B-25-12vsGrok 4.7GPT-5.6 CybervsGrok 4.7Ministral 3 14B-25-12vsDeepSeek-V4.1-Flash-1017GPT-5.6 CybervsDeepSeek-V4.1-Flash-1017Ministral 3 14B-25-12vsKimi K3.1 ProGPT-5.6 CybervsKimi K3.1 ProFrequently asked questions
Ministral 3 14B-25-12 and GPT-5.6 Cyber don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Ministral 3 14B-25-12 is cheaper on both input and output: $0.20 vs $12.50 per million input tokens, and $0.20 vs $75.00 per million output tokens. Ministral 3 14B-25-12 shipped 251 days before GPT-5.6 Cyber, so benchmark comparisons should account for the intervening progress.
Context windows are 256k (Ministral 3 14B-25-12) vs 400k (GPT-5.6 Cyber). Ministral 3 14B-25-12 is open weight, while GPT-5.6 Cyber is closed.
Direct benchmark comparisons are unavailable — Ministral 3 14B-25-12 and GPT-5.6 Cyber don't publish scores on any of the same benchmarks.