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.
671B8B
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.
$0.27SiliconFlow—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.41SiliconFlow—
$74.50SiliconFlow · fp8—
Overview
CompanyDeepSeekGoogle
Release dateSep 29 2025Oct 3 2024
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

DeepSeek V3.2 Exp and Gemini 1.5 Flash-8B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Gemini 1.5 Flash-8B shipped 361 days before DeepSeek V3.2 Exp, so benchmark comparisons should account for the intervening progress.

DeepSeek V3.2 Exp has 671B parameters, while Gemini 1.5 Flash-8B has 8B. Context windows are 128k (DeepSeek V3.2 Exp) vs 1M (Gemini 1.5 Flash-8B). DeepSeek V3.2 Exp is open weight, while Gemini 1.5 Flash-8B is closed.

Direct benchmark comparisons are unavailable — DeepSeek V3.2 Exp and Gemini 1.5 Flash-8B don't publish scores on any of the same benchmarks.