AnthropicClaude Haiku 4.5VSZ.ai (Zhipu AI)GLM-4.6
Our Take
We recommend GLM-4.6 for a 2.0x API cost saving and superior reasoning capability, or Claude Haiku 4.5 if your workflow requires peak coding performance. While GLM-4.6 is more cost-effective, Claude Haiku 4.5 holds a clear coding advantage. Choose GLM-4.6 for complex logic, or Claude Haiku 4.5 for codebase development.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Verified benchmark. Claude Haiku 4.5 scored 73.3%, while GLM-4.6 scored 68%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Claude Haiku 4.5 scored 73%, while GLM-4.6 scored 82.9%.
Cost Efficiency: Claude Haiku 4.5 pricing ($1/M input, $5/M output) is 2.0x cheaper than GLM-4.6 ($0.6/M input, $2.2/M output).
Was this recommendation helpful?
Benchmarks & Scores
Coding (swe-bench-verified)Winner (+5.3%)
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)
68%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+9.9%)
82.9%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-4.6
GLM-4.6 is cheaper than Claude Haiku 4.5. GLM-4.6 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.
Claude Haiku 4.5 is better for coding tasks on this benchmark. It scores 73.3% on swe-bench-verified (multi-file code and clearly defined tasks) compared to GLM-4.6 which scores 68%.
Related Matchups
Explore similar comparisons for Claude Haiku 4.5 and GLM-4.6.
Do you want to find a model for your constraints?
Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.