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o4-mini vs MiniMax M2.5
A detailed comparison of o4-mini (OpenAI) and MiniMax M2.5 (MiniMax) across pricing, performance, and features.
Pricing Comparison
| Metric | o4-mini | MiniMax M2.5 | Difference |
|---|---|---|---|
| Input / 1M tokens | $1.10 | $0.30 | -73% |
| Output / 1M tokens | $4.40 | $1.20 | -73% |
| Context window | 200K | 200K | — |
| Max output | 100K | 128K | — |
Benchmark Comparison
| Benchmark | o4-mini | MiniMax M2.5 |
|---|---|---|
| MMLU-Pro | 85% | 82% |
| HumanEval | 93.5% | 90% |
| GPQA | 76% | — |
Capabilities
| Capability | o4-mini | MiniMax M2.5 |
|---|---|---|
| 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
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 o4-mini if you need the best possible quality for complex tasks.