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 | 4B |
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 | 256k |
| 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. | $0.0166Io Net | — |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.0216Io Net | — |
| $4.40Io Net · fp16 | — | |
| These models have no shared benchmark scores. | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | — | 59.5% |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | — | 18.1% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 72.41% |
IFBenchInstruction following — Tests whether the AI can follow detailed instructions and satisfy multiple constraints at once. Higher is better. | — | 77.94% |
| Overview | ||
| Company | Mistral | NVIDIA |
| Release date | Jul 18 2024 | Oct 16 2026 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Mistral NeMovsClaude Fable 5.2Nemotron Labs Dory 1.0 4BvsClaude Fable 5.2Mistral NeMovsGPT-6.1 TerraNemotron Labs Dory 1.0 4BvsGPT-6.1 TerraMistral NeMovsGemini 4 CarbonNemotron Labs Dory 1.0 4BvsGemini 4 CarbonMistral NeMovsMuse EmberNemotron Labs Dory 1.0 4BvsMuse EmberMistral NeMovsGrok 4.7Nemotron Labs Dory 1.0 4BvsGrok 4.7Mistral NeMovsDeepSeek-V4.1-Flash-1017Nemotron Labs Dory 1.0 4BvsDeepSeek-V4.1-Flash-1017Frequently asked questions
Mistral NeMo and Nemotron Labs Dory 1.0 4B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral NeMo shipped 820 days before Nemotron Labs Dory 1.0 4B, so benchmark comparisons should account for the intervening progress.
Mistral NeMo has 12B parameters, while Nemotron Labs Dory 1.0 4B has 4B. Context windows are 128k (Mistral NeMo) vs 256k (Nemotron Labs Dory 1.0 4B).
Direct benchmark comparisons are unavailable — Mistral NeMo and Nemotron Labs Dory 1.0 4B don't publish scores on any of the same benchmarks.