AnthropicClaude Haiku 4.5VSMetaLlama-3.1 8B
Our Take
We recommend Claude Haiku 4.5 if you need peak intelligence and a much larger context window for full-repo analysis, or the free Llama-3.1 8B if you want zero API costs and total offline privacy. While Claude Haiku 4.5 offers superior reasoning capability, Llama-3.1 8B runs entirely on your own local hardware. Choose Claude Haiku 4.5 for repository-scale analysis, or Llama-3.1 8B 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. Claude Haiku 4.5 scored 73%, while Llama-3.1 8B scored 30.4% (+42.6% gap).
Coding Performance: Evaluated on different benchmarks. Llama-3.1 8B scored 72.6% on HumanEval (basic standalone code completion and simple functions), while Claude Haiku 4.5 scored 73.3% on SWE-bench Verified (multi-file code and clearly defined tasks).
Context Window: Claude Haiku 4.5 supports a 200k context window, while Llama-3.1 8B supports 131k.
Hosting Model: Llama-3.1 8B runs locally for $0 API costs, while Claude Haiku 4.5 is a cloud API.
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Benchmarks & Scores
Coding (swe-bench-verified)
73.3%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+42.6%)
73%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.00Input: $1.00 | Output: $5.00Context WindowLarger
200k tokensBenchmarks & Scores
Coding (human-eval)
72.6%basic standalone code completion and simple functions
Reasoning (gpqa-diamond)
30.4%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
131.07k tokensFrequently Asked Questions about Claude Haiku 4.5 vs Llama-3.1 8B
For coding tasks, Claude Haiku 4.5 scores 73.3% on swe-bench-verified (multi-file code and clearly defined tasks), while Llama-3.1 8B scores 72.6% on human-eval (basic standalone code completion and simple functions).
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