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GLM-4.7 vs MiniMax M2.5
A detailed comparison of GLM-4.7 (Zhipu AI) and MiniMax M2.5 (MiniMax) across pricing, performance, and features.
Pricing Comparison
| Metric | GLM-4.7 | MiniMax M2.5 | Difference |
|---|---|---|---|
| Input / 1M tokens | $0.60 | $0.30 | -50% |
| Output / 1M tokens | $2.20 | $1.20 | -45% |
| Context window | 200K | 200K | — |
| Max output | 128K | 128K | — |
Benchmark Comparison
| Benchmark | GLM-4.7 | MiniMax M2.5 |
|---|---|---|
| MMLU-Pro | 84.3% | 82% |
| HumanEval | — | 90% |
| GPQA | 85.7% | — |
Capabilities
| Capability | GLM-4.7 | MiniMax M2.5 |
|---|---|---|
| code | ✓ | ✓ |
| reasoning | ✓ | ✓ |
| text | ✓ | ✓ |
| vision | ✓ | ✗ |
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
MiniMax M2.5 Strengths
- ✓Frontier quality at budget pricing ($0.30/$1.20)
- ✓80.2% SWE-Bench Verified — among the best
- ✓Open-source (MIT) with 10B active params — easy to run
MiniMax M2.5 Weaknesses
- ✗Text-only — no vision or audio
- ✗No tool-use support
- ✗Newer provider — smaller ecosystem
Quick Verdict
Best value: MiniMax M2.5 is the more affordable option at $0.3/$1.2 per 1M tokens.
Higher benchmarks: MiniMax M2.5 scores higher on average across available benchmarks (86.0% avg).
Choose MiniMax M2.5 if cost matters most. Choose GLM-4.7 if you need the best possible quality for complex tasks.