GLM-5.3-Flash vs o3-mini
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | GLM-5.3-Flash | o3-mini |
|---|---|---|
| Provider | Zhipu AI | OpenAI |
| Input Price (1M) | $0.07 | $1.10 |
| Output Price (1M) | $0.25 | $4.40 |
| Context Window | 1,000,000 | 200,000 |
Verdict
GLM-5.3-Flash costs $0.07 per 1M input tokens and $0.25 per 1M output tokens. o3-mini costs $1.10 per 1M input tokens and $4.40 per 1M output tokens. GLM-5.3-Flash is 93% cheaper on input tokens than o3-mini. For output tokens, GLM-5.3-Flash is the more affordable option at $0.25/1M vs $4.40.
On context window, GLM-5.3-Flash supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose GLM-5.3-Flash
- ✓ You need the lowest input token cost ($ 0.07/1M)
- ✓ Your workload is output-heavy — GLM-5.3-Flash generates text cheaper
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with Zhipu AI
When to choose o3-mini
- ✓ 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-5.3-Flash cheaper than o3-mini? ▼
GLM-5.3-Flash is cheaper on input tokens at $0.07/1M vs $1.10/1M for o3-mini — a 93% saving.
What is the context window of GLM-5.3-Flash vs o3-mini? ▼
GLM-5.3-Flash has a 1,000,000-token context window. o3-mini has a 200,000-token context window. GLM-5.3-Flash supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: GLM-5.3-Flash or o3-mini? ▼
The best choice depends on your use case. For cost efficiency on input tokens, GLM-5.3-Flash is the cheaper option. For maximum context length, GLM-5.3-Flash supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.