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.
671B123B
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.
$0.25SiliconFlow$0.40Mistral
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$1.00SiliconFlow$2.00Mistral
$100SiliconFlow · fp8$180Mistral
These models have no shared benchmark scores.
Overview
CompanyDeepSeekMistral
Release dateMar 24 2025Dec 9 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

DeepSeek V3-0324 and Devstral 2 (123B) don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek V3-0324 shipped 260 days before Devstral 2 (123B), so benchmark comparisons should account for the intervening progress.

DeepSeek V3-0324 has 671B parameters, while Devstral 2 (123B) has 123B. Context windows are 128k (DeepSeek V3-0324) vs 256k (Devstral 2 (123B)).

Direct benchmark comparisons are unavailable — DeepSeek V3-0324 and Devstral 2 (123B) don't publish scores on any of the same benchmarks.