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.
0.6B/1.7B/4B/8B/14B/30B/32B/235B9B
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.
$0.08DeepInfra—
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.22NextBit—
$30.00DeepInfra · fp8—
These models have no shared benchmark scores.
Overview
CompanyQwenZ.ai
Release dateApr 29 2025Jun 5 2024
AccessOpen WeightOpen Weight
Model detailsView modelView model

Frequently asked questions

Qwen3 and GLM-4-9B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. GLM-4-9B shipped 328 days before Qwen3, so benchmark comparisons should account for the intervening progress.

Qwen3 has 0.6B/1.7B/4B/8B/14B/30B/32B/235B parameters, while GLM-4-9B has 9B.

Direct benchmark comparisons are unavailable — Qwen3 and GLM-4-9B don't publish scores on any of the same benchmarks.