Model comparison
GPT-5 (high) vs MiniMax M3
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GPT-5 (high) unranked; MiniMax M3 #18
BenchAlign evidence: GPT-5 (high) estimated; MiniMax M3 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5 (high) and MiniMax M3 share 18 comparable benchmark results. 0 of 8 categories are comparable. 3 results are unique to GPT-5 (high); 27 to MiniMax M3.
Updated July 16, 2026- Shared results
- 18
- GPT-5 (high) only
- 3
- MiniMax M3 only
- 27
- Comparable categories
- 0 / 8
Benchmark data for GPT-5 (high) and MiniMax M3 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 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 (high) is priced at $1.25 input / $10.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. MiniMax M3 has the larger context window at 1M, compared with 128K for GPT-5 (high).
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5 (high) | Δ | MiniMax M3 |
|---|---|---|---|
| Agentic | GPT-5 (high)Not measured | MarginNo overlap | MiniMax M372.3 |
| Coding | GPT-5 (high)Not measured | MarginNo overlap | MiniMax M372.2 |
| Math | GPT-5 (high)Not measured | MarginNo overlap | MiniMax M385.7 |
| Multimodal | GPT-5 (high)Not measured | MarginNo overlap | MiniMax M364.9 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5 (high) | MiniMax M3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5 (high)$1.25 input / $10 output | MiniMax M3$0.3 input / $1.2 output | MiniMax M3 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5 (high)83 tok/s | MiniMax M3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5 (high)36.28 s | MiniMax M3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5 (high)128K | MiniMax M31M | MiniMax M3 lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | GPT-5 (high) | MiniMax M3 | Result |
|---|---|---|---|
| AA Agentic IndexSource | 25.7% | 35.4% | MiniMax M3 leads |
| τ²-bench resultsSource | 84.8% | 88.9% | MiniMax M3 leads |
| GDPval-AASource | 28.7% | 44.7% | MiniMax M3 leads |
| GDPval-AASource | 1075 | 1395 | MiniMax M3 leads |
| JobBenchSource | 8.5% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 66% | Not comparable |
| BrowseCompSource | — | 83.5% | Not comparable |
| OSWorld-VerifiedSource | — | 70.1% | Not comparable |
| MCP AtlasSource | — | 74.2% | Not comparable |
| Claw-EvalSource | — | 74.5% | Not comparable |
| GDPval rubricsSource | — | 74.7% | Not comparable |
| BankerToolBenchSource | — | 76.1% | Not comparable |
| ResearchClawBenchSource | — | 19.8% | Not comparable |
| OSWorld 2.0Source | — | 4.6% | Not comparable |
| AA BriefcaseSource | — | 1110 | Not comparable |
| AA EnterpriseOps-GymSource | — | 32.1% | Not comparable |
| AA Harvey LABSource | — | 6.7% | Not comparable |
Coding12 benchmarks
| Benchmark | GPT-5 (high) | MiniMax M3 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 20.09% | — | Not comparable |
| AA Coding IndexSource | 37.8% | 58.6% | MiniMax M3 leads |
| Terminal-Bench HardSource | 32.6% | 42.4% | MiniMax M3 leads |
| AA-SciCodeSource | 42.9% | 45.4% | MiniMax M3 leads |
| SWE-bench VerifiedSource | — | 80.5% | Not comparable |
| SWE-bench ProSource | — | 59% | Not comparable |
| Terminal-Bench 2.0Source | — | 66.0% | Not comparable |
| NL2RepoSource | — | 42.1% | Not comparable |
| VIBE V2Source | — | 50.1% | Not comparable |
| SVG-BenchSource | — | 63.7% | Not comparable |
| KernelBench HardSource | — | 28.8% | Not comparable |
| AA Terminal-Bench 2.1Source | — | 65.2% | Not comparable |
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | GPT-5 (high) | MiniMax M3 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 34.7% | 44.4% | MiniMax M3 leads |
| AA-GPQA DiamondSource | 85.4% | 92.9% | MiniMax M3 leads |
| AA-HLESource | 26.5% | 37.1% | MiniMax M3 leads |
| AA-Omniscience IndexSource | -8.1% | 1.4% | MiniMax M3 leads |
| AA-Omniscience AccuracySource | 40.7% | 15.0% | GPT-5 (high) leads |
| AA-Omniscience Hallucination RateSource | 82.1% | 16.1% | MiniMax M3 leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math2 benchmarks
Multimodal7 benchmarks
| Benchmark | GPT-5 (high) | MiniMax M3 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 74.2% | 78.6% | MiniMax M3 leads |
| Design Arena WebsiteSource | 1219 | 1294 | MiniMax M3 leads |
| OfficeQA ProSource | — | 45.1% | Not comparable |
| OmniDocBench 1.5Source | — | 91.6% | Not comparable |
| MMMU-ProSource | — | 78.1% | Not comparable |
| VideoMMMUSource | — | 84.6% | Not comparable |
| Video-MME (with subtitle)Source | — | 85.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5 (high) | MiniMax M3 | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.1% | 82.9% | MiniMax M3 leads |
Frequently Asked Questions (3)
Can I compare GPT-5 (high) and MiniMax M3 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 (high) and MiniMax M3 today?
GPT-5 (high): $1.25 input / $10.00 output per 1M tokens MiniMax M3: $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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