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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.
236B—
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.
128k400k
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.
—$1.25Azure
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$10.00Azure
—$750Azure
Overview
CompanyDeepSeekOpenAI
Release dateDec 10 2024Nov 19 2025
AccessOpen WeightClosed
Model detailsView modelView model

Frequently asked questions

DeepSeek V2.5 (Revised) and GPT-5.1-Codex-Max don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek V2.5 (Revised) shipped 344 days before GPT-5.1-Codex-Max, so benchmark comparisons should account for the intervening progress.

Context windows are 128k (DeepSeek V2.5 (Revised)) vs 400k (GPT-5.1-Codex-Max). DeepSeek V2.5 (Revised) is open weight, while GPT-5.1-Codex-Max is closed.

Direct benchmark comparisons are unavailable — DeepSeek V2.5 (Revised) and GPT-5.1-Codex-Max don't publish scores on any of the same benchmarks.