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.
671B—
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.
128k1M
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.
$0.25DeepInfra—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.95DeepInfra—
$97.50DeepInfra · fp4—
These models have no shared benchmark scores.
Overview
CompanyDeepSeekGoogle
Release dateAug 21 2025Sep 24 2024
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

DeepSeek V3.1 and Gemini 1.5 Flash-002 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 1.5 Flash-002 shipped 331 days before DeepSeek V3.1, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (DeepSeek V3.1) vs 1M (Gemini 1.5 Flash-002). DeepSeek V3.1 is open weight, while Gemini 1.5 Flash-002 is closed.

Direct benchmark comparisons are unavailable — DeepSeek V3.1 and Gemini 1.5 Flash-002 don't publish scores on any of the same benchmarks.