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o4-mini vs GLM-4.7
A detailed comparison of o4-mini (OpenAI) and GLM-4.7 (Zhipu AI) across pricing, performance, and features.
Pricing Comparison
| Metric | o4-mini | GLM-4.7 | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.10 | $0.60 | -45% |
| Output / 1M tokens | $4.40 | $2.20 | -50% |
| Context window | 200K | 200K | — |
| Max output | 100K | 128K | — |
Benchmark Comparison
| Benchmark | o4-mini | GLM-4.7 |
|---|---|---|
| MMLU-Pro | 85% | 84.3% |
| HumanEval | 93.5% | — |
| GPQA | 76% | 85.7% |
Capabilities
| Capability | o4-mini | GLM-4.7 |
|---|---|---|
| code | ✓ | ✓ |
| reasoning | ✓ | ✓ |
| text | ✓ | ✓ |
| tool-use | ✓ | ✗ |
| vision | ✓ | ✓ |
o4-mini Strengths
- ✓Affordable reasoning model
- ✓200K context window
- ✓Good for math and science
o4-mini Weaknesses
- ✗Slower than non-reasoning models
- ✗Reasoning tokens add to effective cost
GLM-4.7 Strengths
- ✓Excellent value — strong benchmarks at $0.60/$2.20
- ✓Open-weight (MIT license)
- ✓Top scores on AIME 25 and BrowseComp
GLM-4.7 Weaknesses
- ✗No tool-use support yet
- ✗358B parameters — still heavy for self-hosting
- ✗Smaller ecosystem than OpenAI/Anthropic
Quick Verdict
Best value: GLM-4.7 is the more affordable option at $0.6/$2.2 per 1M tokens.
Higher benchmarks: GLM-4.7 scores higher on average across available benchmarks (85.0% avg).
Choose GLM-4.7 if cost matters most. Choose o4-mini if you need the best possible quality for complex tasks.