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Claude Haiku 4.5 vs GLM-5

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

Claude Haiku 4.5 Cost
$2.00
GLM-5 Cost
$1.64
GLM-5 is 18% cheaper
FeatureClaude Haiku 4.5GLM-5
ProviderAnthropicZhipu AI
Input Price (1M)$1.00$1.00
Output Price (1M)$5.00$3.20
Context Window200,0001,000,000

Verdict

Claude Haiku 4.5 costs $1.00 per 1M input tokens and $5.00 per 1M output tokens. GLM-5 costs $1.00 per 1M input tokens and $3.20 per 1M output tokens. Claude Haiku 4.5 and GLM-5 have identical input token pricing. For output tokens, GLM-5 is the more affordable option at $3.20/1M vs $5.00.

On context window, GLM-5 supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.

When to choose Claude Haiku 4.5

  • ✓ You are already integrated with Anthropic

When to choose GLM-5

  • ✓ Your workload is output-heavy — GLM-5 generates text cheaper
  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with Zhipu AI

Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.

Frequently Asked Questions

Is Claude Haiku 4.5 cheaper than GLM-5?

Claude Haiku 4.5 and GLM-5 have identical input token pricing at $1.00/1M tokens.

What is the context window of Claude Haiku 4.5 vs GLM-5?

Claude Haiku 4.5 has a 200,000-token context window. GLM-5 has a 1,000,000-token context window. GLM-5 supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: Claude Haiku 4.5 or GLM-5?

The best choice depends on your use case. For cost efficiency on input tokens, Claude Haiku 4.5 is the cheaper option. For maximum context length, GLM-5 supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.