AnthropicClaude Haiku 4.5VSZ.ai (Zhipu AI)GLM-4.7
Our Take
We recommend choosing GLM-4.7 because it outperforms or matches Claude Haiku 4.5 across reasoning, coding, and context capacity while being cheaper or equal in cost. Choose GLM-4.7 for superior overall value.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Verified benchmark. GLM-4.7 scored 73.8%, while Claude Haiku 4.5 scored 73.3%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. GLM-4.7 scored 85.7%, while Claude Haiku 4.5 scored 73%.
Context Window: GLM-4.7 supports a 203k context window compared to 200k for Claude Haiku 4.5.
Cost Comparison: GLM-4.7 blended CPM is $0.6/$2.2 compared to $1/$5 for Claude Haiku 4.5.
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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)
$2.00Input: $1.00 | Output: $5.00Context Window
200k tokensBenchmarks & Scores
Coding (swe-bench-verified)Winner (+0.5%)
73.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+12.7%)
85.7%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.0x cheaper
$1.00Input: $0.60 | Output: $2.20Context WindowLarger
202.75k tokensFrequently Asked Questions about Claude Haiku 4.5 vs GLM-4.7
GLM-4.7 is cheaper than Claude Haiku 4.5. GLM-4.7 has a blended cost of $1.00/1M tokens, which is about 2.0x cheaper than Claude Haiku 4.5 at $2.00/1M tokens.
GLM-4.7 is better for coding tasks on this benchmark. It scores 73.8% on swe-bench-verified (multi-file code and clearly defined tasks) compared to Claude Haiku 4.5 which scores 73.3%.
Related Matchups
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