Model comparison
GPT-5.1-Codex-Max vs MiniMax M2.5
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.1-Codex-Max #90 (Estimated); MiniMax M2.5 #55 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.1-Codex-Max and MiniMax M2.5 share 1 comparable benchmark result. 0 of 8 categories are comparable. 12 results are unique to GPT-5.1-Codex-Max; 0 to MiniMax M2.5.
Updated July 20, 2026- Shared results
- 1
- GPT-5.1-Codex-Max only
- 12
- MiniMax M2.5 only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.1-Codex-Max and MiniMax M2.5 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.1-Codex-Max is priced at $1.25 input / $10.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.5. GPT-5.1-Codex-Max has the larger context window at 400K, compared with 128K for MiniMax M2.5.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.1-Codex-Max | MiniMax M2.5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.1-Codex-Max$1.25 input / $10 output | MiniMax M2.5$0.3 input / $1.2 output | MiniMax M2.5 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.1-Codex-MaxNot available | MiniMax M2.546 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.1-Codex-MaxNot available | MiniMax M2.52.12 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.1-Codex-Max400K | MiniMax M2.5128K | GPT-5.1-Codex-Max lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | GPT-5.1-Codex-Max | MiniMax M2.5 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 83% | — | Not comparable |
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-5.1-Codex-Max | MiniMax M2.5 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 34.7% | — | Not comparable |
| AA-GPQA DiamondSource | 86.0% | — | Not comparable |
| AA-HLESource | 23.4% | — | Not comparable |
| AA-Omniscience IndexSource | -6.0% | — | Not comparable |
| AA-Omniscience AccuracySource | 39.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 74.4% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | GPT-5.1-Codex-Max | MiniMax M2.5 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 72.5% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.1-Codex-Max | MiniMax M2.5 | Result |
|---|---|---|---|
| AA-IFBenchSource | 70.0% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5.1-Codex-Max and MiniMax M2.5 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GPT-5.1-Codex-Max and MiniMax M2.5 today?
GPT-5.1-Codex-Max: $1.25 input / $10.00 output per 1M tokens MiniMax M2.5: $0.30 input / $1.20 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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