AnthropicClaude Haiku 4.5VSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend GLM-5.2 for complex complex codebases, multi-file repositories, and architectural planning, or the 1.1x cheaper Claude Haiku 4.5 if your budget requires optimizing costs for very high-volume pipelines. While GLM-5.2 offers a clear reasoning advantage, it carries a moderate price premium. Choose GLM-5.2 for architectural codebase planning, or Claude Haiku 4.5 to save on API costs for simple scripts.
▶WHY?
Benchmark Calculations & Evidence:
Coding Evaluation: Claude Haiku 4.5 was evaluated on SWE-bench Verified (scoring 73.3%), while GLM-5.2 was evaluated on SWE-bench Pro (scoring 62.1%).
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. GLM-5.2 scored 91.2%, while Claude Haiku 4.5 scored 73%.
Cost Efficiency: Claude Haiku 4.5 pricing ($1/M input, $5/M output) is 1.1x cheaper than GLM-5.2 ($1.4/M input, $4.4/M output).
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Benchmarks & Scores
Coding (swe-bench-verified)
73.3%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)
73%graduate-level science QA
Cost & Context
Cost (per 1M tokens)1.1x cheaper
$2.00Input: $1.00 | Output: $5.00Context Window
200k tokensBenchmarks & Scores
Coding (swe-bench-pro)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+18.2%)
91.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.15Input: $1.40 | Output: $4.40Context WindowLarger
1.05M tokensFrequently Asked Questions about Claude Haiku 4.5 vs GLM-5.2
Claude Haiku 4.5 is cheaper than GLM-5.2. Claude Haiku 4.5 has a blended cost of $2.00/1M tokens, which is about 1.1x cheaper than GLM-5.2 at $2.15/1M tokens.
For coding tasks, Claude Haiku 4.5 scores 73.3% on swe-bench-verified (multi-file code and clearly defined tasks), while GLM-5.2 scores 62.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning).
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