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GLM-5.1 vs o1-pro

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

GLM-5.1 Cost
$2.28
o1-pro Cost
$270.00
GLM-5.1 is 99% cheaper
FeatureGLM-5.1o1-pro
ProviderZhipu AIOpenAI
Input Price (1M)$1.40$150.00
Output Price (1M)$4.40$600.00
Context Window1,000,000200,000

Verdict

GLM-5.1 costs $1.40 per 1M input tokens and $4.40 per 1M output tokens. o1-pro costs $150.00 per 1M input tokens and $600.00 per 1M output tokens. GLM-5.1 is 99% cheaper on input tokens than o1-pro. For output tokens, GLM-5.1 is the more affordable option at $4.40/1M vs $600.00.

On context window, GLM-5.1 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 GLM-5.1

  • ✓ You need the lowest input token cost ($ 1.40/1M)
  • ✓ Your workload is output-heavy — GLM-5.1 generates text cheaper
  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with Zhipu AI

When to choose o1-pro

  • ✓ You are already integrated with OpenAI

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 GLM-5.1 cheaper than o1-pro?

GLM-5.1 is cheaper on input tokens at $1.40/1M vs $150.00/1M for o1-pro — a 99% saving.

What is the context window of GLM-5.1 vs o1-pro?

GLM-5.1 has a 1,000,000-token context window. o1-pro has a 200,000-token context window. GLM-5.1 supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: GLM-5.1 or o1-pro?

The best choice depends on your use case. For cost efficiency on input tokens, GLM-5.1 is the cheaper option. For maximum context length, GLM-5.1 supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.