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.
671B16B
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.
128k128k
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
CompanyDeepSeekMoonshot AI
Release dateSep 29 2025Apr 10 2025
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

DeepSeek V3.2 ExpvsClaude Haiku 5.5Kimi-VLvsClaude Haiku 5.5DeepSeek V3.2 ExpvsGPT-6.1 SolKimi-VLvsGPT-6.1 SolDeepSeek V3.2 ExpvsGemini 4 ArgonKimi-VLvsGemini 4 ArgonDeepSeek V3.2 ExpvsMuse Spark OpenKimi-VLvsMuse Spark OpenDeepSeek V3.2 ExpvsGrok 4.7Kimi-VLvsGrok 4.7DeepSeek V3.2 ExpvsMistral Large 4Kimi-VLvsMistral Large 4

Frequently asked questions

DeepSeek V3.2 Exp and Kimi-VL don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Kimi-VL shipped 172 days before DeepSeek V3.2 Exp, so benchmark comparisons should account for the intervening progress.

DeepSeek V3.2 Exp has 671B parameters, while Kimi-VL has 16B. Context windows are 128k (DeepSeek V3.2 Exp) vs 128k (Kimi-VL).

Direct benchmark comparisons are unavailable — DeepSeek V3.2 Exp and Kimi-VL don't publish scores on any of the same benchmarks.