Compare AI models
| 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. | 70B | 9B |
| 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. | $0.10DeepInfra | — |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.32DeepInfra | — |
| Overview | ||
| Company | Meta | Z.ai |
| Release date | Dec 6 2024 | Jun 5 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
LLaMA 3.3vsClaude Haiku 5.5GLM-4-9BvsClaude Haiku 5.5LLaMA 3.3vsGPT-6.1 SolGLM-4-9BvsGPT-6.1 SolLLaMA 3.3vsGemini 4 ArgonGLM-4-9BvsGemini 4 ArgonLLaMA 3.3vsGrok 4.7GLM-4-9BvsGrok 4.7LLaMA 3.3vsDeepSeek-V4.1-FlashGLM-4-9BvsDeepSeek-V4.1-FlashLLaMA 3.3vsMistral Large 4GLM-4-9BvsMistral Large 4Frequently asked questions
LLaMA 3.3 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 184 days before LLaMA 3.3, so benchmark comparisons should account for the intervening progress.
LLaMA 3.3 has 70B parameters, while GLM-4-9B has 9B.
Direct benchmark comparisons are unavailable — LLaMA 3.3 and GLM-4-9B don't publish scores on any of the same benchmarks.