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.
12B480B
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.
128k256k
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$0.30DeepInfra
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$1.00DeepInfra
$4.40Io Net · fp16$110DeepInfra · turbo · fp4
These models have no shared benchmark scores.
Overview
CompanyMistralQwen
Release dateJul 18 2024Jul 22 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

Mistral NeMo and Qwen3-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral NeMo shipped 369 days before Qwen3-Coder, so benchmark comparisons should account for the intervening progress.

Mistral NeMo has 12B parameters, while Qwen3-Coder has 480B. Context windows are 128k (Mistral NeMo) vs 256k (Qwen3-Coder).

Direct benchmark comparisons are unavailable — Mistral NeMo and Qwen3-Coder don't publish scores on any of the same benchmarks.