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.
1B/3B/11B/90B0.5B/1.5B/3B/7B/14B/32B
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.
128k—
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.
$0.027Cloudflare$0.66Cloudflare
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.201Cloudflare$1.00Cloudflare
$15.45Cloudflare$182Cloudflare
Overview
CompanyMetaQwen
Release dateSep 25 2024Nov 12 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Other comparisons

LLaMA 3.2vsClaude Haiku 5.5Qwen2.5-CodervsClaude Haiku 5.5LLaMA 3.2vsGPT-6.1 TerraQwen2.5-CodervsGPT-6.1 TerraLLaMA 3.2vsGemini 4 CarbonQwen2.5-CodervsGemini 4 CarbonLLaMA 3.2vsGrok 4.7Qwen2.5-CodervsGrok 4.7LLaMA 3.2vsDeepSeek-V4.1-Flash-1017Qwen2.5-CodervsDeepSeek-V4.1-Flash-1017LLaMA 3.2vsMistral Large 4Qwen2.5-CodervsMistral Large 4

Frequently asked questions

LLaMA 3.2 and Qwen2.5-Coder don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. LLaMA 3.2 shipped 48 days before Qwen2.5-Coder, so benchmark comparisons should account for the intervening progress.

LLaMA 3.2 has 1B/3B/11B/90B parameters, while Qwen2.5-Coder has 0.5B/1.5B/3B/7B/14B/32B.

Direct benchmark comparisons are unavailable — LLaMA 3.2 and Qwen2.5-Coder don't publish scores on any of the same benchmarks.