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 | 340B |
| 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 | NVIDIA |
| Release date | Dec 6 2024 | Jun 14 2024 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
LLaMA 3.3vsClaude Haiku 5.5Nemotron-4 340BvsClaude Haiku 5.5LLaMA 3.3vsGPT-6.1 SolNemotron-4 340BvsGPT-6.1 SolLLaMA 3.3vsGemini 4 ArgonNemotron-4 340BvsGemini 4 ArgonLLaMA 3.3vsGrok 4.7Nemotron-4 340BvsGrok 4.7LLaMA 3.3vsDeepSeek-V4.1-FlashNemotron-4 340BvsDeepSeek-V4.1-FlashLLaMA 3.3vsMistral Large 4Nemotron-4 340BvsMistral Large 4Frequently asked questions
LLaMA 3.3 and Nemotron-4 340B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Nemotron-4 340B shipped 175 days before LLaMA 3.3, so benchmark comparisons should account for the intervening progress.
LLaMA 3.3 has 70B parameters, while Nemotron-4 340B has 340B.
Direct benchmark comparisons are unavailable — LLaMA 3.3 and Nemotron-4 340B don't publish scores on any of the same benchmarks.