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 | 12B |
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 | $0.018DekaLLM |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $0.32DeepInfra | $0.027Io Net |
| Overview | ||
| Company | Meta | Mistral |
| Release date | Dec 6 2024 | Jul 18 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
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LLaMA 3.3 and Mistral NeMo don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mistral NeMo shipped 141 days before LLaMA 3.3, so benchmark comparisons should account for the intervening progress.
LLaMA 3.3 has 70B parameters, while Mistral NeMo has 12B.
Direct benchmark comparisons are unavailable — LLaMA 3.3 and Mistral NeMo don't publish scores on any of the same benchmarks.