Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 70B | 47B |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 128k | 32k |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. 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 every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | $0.32DeepInfra | — |
| $36.00DeepInfra · turbo · fp8 | — | |
| Overview | ||
| Company | Meta | Mistral |
| Release date | Dec 6 2024 | Dec 8 2023 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
LLaMA 3.3vsClaude Haiku 5.5Mixtral 8×7BvsClaude Haiku 5.5LLaMA 3.3vsGPT-6.1 SolMixtral 8×7BvsGPT-6.1 SolLLaMA 3.3vsGemini 4 ArgonMixtral 8×7BvsGemini 4 ArgonLLaMA 3.3vsGrok 4.7Mixtral 8×7BvsGrok 4.7LLaMA 3.3vsDeepSeek-V4.1-Flash-1017Mixtral 8×7BvsDeepSeek-V4.1-Flash-1017LLaMA 3.3vsKimi K3Mixtral 8×7BvsKimi K3Frequently asked questions
LLaMA 3.3 and Mixtral 8×7B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Mixtral 8×7B shipped 364 days before LLaMA 3.3, so benchmark comparisons should account for the intervening progress.
LLaMA 3.3 has 70B parameters, while Mixtral 8×7B has 47B. Context windows are 128k (LLaMA 3.3) vs 32k (Mixtral 8×7B).
Direct benchmark comparisons are unavailable — LLaMA 3.3 and Mixtral 8×7B don't publish scores on any of the same benchmarks.