AI Model Release Tracker

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.
7B/67B5.1B/8B/26B/31B
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.
4k256k
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.
—$0.042Darkbloom
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$0.18Makora
—$19.40Darkbloom
These models have no shared benchmark scores.
Overview
CompanyDeepSeekGoogle
Release dateNov 29 2023Apr 2 2026
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

DeepSeek-LLMvsClaude Haiku 5.5Gemma 4vsClaude Haiku 5.5DeepSeek-LLMvsGPT-6.1 SolGemma 4vsGPT-6.1 SolDeepSeek-LLMvsMuse Spark OpenGemma 4vsMuse Spark OpenDeepSeek-LLMvsGrok 4.7Gemma 4vsGrok 4.7DeepSeek-LLMvsMistral Large 4Gemma 4vsMistral Large 4DeepSeek-LLMvsKimi K3Gemma 4vsKimi K3

Frequently asked questions

DeepSeek-LLM and Gemma 4 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-LLM shipped 855 days before Gemma 4, so benchmark comparisons should account for the intervening progress.

DeepSeek-LLM has 7B/67B parameters, while Gemma 4 has 5.1B/8B/26B/31B. Context windows are 4k (DeepSeek-LLM) vs 256k (Gemma 4).

Direct benchmark comparisons are unavailable — DeepSeek-LLM and Gemma 4 don't publish scores on any of the same benchmarks.