MetaLlama-3.1 405BVSMistral AIMistral Large 3
Our Take
We recommend Llama-3.1 405B for practical local execution on standard developer hardware, or Mistral Large 3 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While Mistral Large 3 offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose Llama-3.1 405B for standard local setups, or Mistral Large 3 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: Mistral Large 3 is a massive 675B parameter model requiring heavy GPU infrastructure, while Llama-3.1 405B is a 405B parameter model.
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Benchmarks & Scores
Coding (human-eval)
89%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)
50.7%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
131.07k tokensBenchmarks & Scores
Coding (live-code-bench)
34.4%scripting single-file apps or clearly defined functions
Reasoning (gpqa-diamond)Winner (+34.8%)
85.5%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$0.75Input: $0.50 | Output: $1.50Context WindowLarger
262.14k tokensFrequently Asked Questions about Llama-3.1 405B vs Mistral Large 3
For coding tasks, Llama-3.1 405B scores 89% on human-eval (basic standalone code completion and simple functions), while Mistral Large 3 scores 34.4% on live-code-bench (scripting single-file apps or clearly defined functions).
Related Matchups
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