Qwen2.5vsGLM-4-9B
Qwen2.5 | GLM-4-9B | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 72B | 9B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 128k | — |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.36DeepInfra | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.40DeepInfra | — |
| Overview | ||
| Company | Qwen | Z.ai |
| Release date | Sep 19 2024 | Jun 5 2024 |
| Access | Open Weight | Open Weight |
Other comparisons
Frequently asked questions
Qwen2.5 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 106 days before Qwen2.5, so benchmark comparisons should account for the intervening progress.
Qwen2.5 has 72B parameters, while GLM-4-9B has 9B.
Direct benchmark comparisons are unavailable — Qwen2.5 and GLM-4-9B don't publish scores on any of the same benchmarks.