MetaLlama-3.1 70BVSOpenAIGPT-5.4 nano
Our Take
We recommend GPT-5.4 nano if you need peak intelligence and a much larger context window for full-repo analysis, or the free Llama-3.1 70B if you want zero API costs and total offline privacy. While GPT-5.4 nano offers superior reasoning capability, Llama-3.1 70B runs entirely on your own local hardware. Choose GPT-5.4 nano for repository-scale analysis, or Llama-3.1 70B for zero-cost offline privacy and basic standalone code completion and simple functions.
▶WHY?
Benchmark Calculations & Evidence:
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. GPT-5.4 nano scored 82.8%, while Llama-3.1 70B scored 46.7% (+36.1% gap).
Coding Performance: Evaluated on different benchmarks. Llama-3.1 70B scored 80.5% on HumanEval (basic standalone code completion and simple functions), while GPT-5.4 nano scored 52.4% on SWE-bench Pro (complex codebases, multi-file repositories, and architectural planning).
Context Window: GPT-5.4 nano supports a 400k context window, while Llama-3.1 70B supports 131k.
Hosting Model: Llama-3.1 70B runs locally for $0 API costs, while GPT-5.4 nano is a cloud API.
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Benchmarks & Scores
Coding (human-eval)
80.5%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)
46.7%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
131.07k tokensBenchmarks & Scores
Coding (swe-bench-pro)
52.4%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+36.1%)
82.8%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$0.46Input: $0.20 | Output: $1.25Context WindowLarger
400k tokensFrequently Asked Questions about Llama-3.1 70B vs GPT-5.4 nano
For coding tasks, Llama-3.1 70B scores 80.5% on human-eval (basic standalone code completion and simple functions), while GPT-5.4 nano scores 52.4% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).
Related Matchups
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