LLaMA 3.3vsQwen2
LLaMA 3.3 | Qwen2 | |
|---|---|---|
| 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 | 72B |
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. | $0.10DeepInfra | — |
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 | Qwen |
| Release date | Dec 6 2024 | Jun 6 2024 |
| Access | Open Weight | Open Weight |
Other comparisons
Frequently asked questions
LLaMA 3.3 and Qwen2 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Qwen2 shipped 183 days before LLaMA 3.3, so benchmark comparisons should account for the intervening progress.
LLaMA 3.3 has 70B parameters, while Qwen2 has 72B.
Direct benchmark comparisons are unavailable — LLaMA 3.3 and Qwen2 don't publish scores on any of the same benchmarks.