Model comparison
GPT-5.4 Pro vs MiniMax M3
Head-to-head evidence from 3 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.4 Pro #44 (Estimated); MiniMax M3 #15 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.4 Pro and MiniMax M3 share 3 comparable benchmark results. 3 of 8 categories are comparable. 9 results are unique to GPT-5.4 Pro; 42 to MiniMax M3.
Updated July 23, 2026- Shared results
- 3
- GPT-5.4 Pro only
- 9
- MiniMax M3 only
- 42
- Comparable categories
- 3 / 8
Pick MiniMax M3 if you want the stronger benchmark profile. GPT-5.4 Pro only becomes the better choice if multimodal & grounded is the priority or you need the larger 1.05M context window.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 3 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MiniMax M3 is clearly ahead on the BenchAlign aggregate, 69.75 to 60.89. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M3's sharpest advantage is in mathematics, where it averages 85.7 against 46.9. The single biggest benchmark swing on the page is MMMU-Pro, 94% to 78.1%. GPT-5.4 Pro does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 Pro is also the more expensive model on tokens at $30.00 input / $180.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. That is roughly 150.0x on output cost alone. GPT-5.4 Pro is the reasoning model in the pair, while MiniMax M3 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5.4 Pro gives you the larger context window at 1.05M, compared with 1M for MiniMax M3.
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-5.4 Pro | Δ | MiniMax M3 |
|---|---|---|---|
| Math | GPT-5.4 Pro46.9 | Margin→ 38.8 | MiniMax M385.7 |
| Multimodal | GPT-5.4 Pro94.0 | Margin← 29.1 | MiniMax M364.9 |
| Agentic | GPT-5.4 Pro89.3 | Margin← 17.0 | MiniMax M372.3 |
| Coding | GPT-5.4 ProNot measured | MarginNo overlap | MiniMax M372.2 |
| Reasoning | GPT-5.4 Pro83.3 | MarginNo overlap | MiniMax M3Not measured |
| Knowledge | GPT-5.4 Pro58.7 | MarginNo overlap | MiniMax M3Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMMU-Pro
MultimodalA 94%B 78.1%Winner: GPT-5.4 ProΔ 15.9MMMU-Pro: GPT-5.4 Pro scored 94%; MiniMax M3 scored 78.1%. GPT-5.4 Pro wins this benchmark. - Source ↗
BrowseComp
AgenticA 89.3%B 83.5%Winner: GPT-5.4 ProΔ 5.8BrowseComp: GPT-5.4 Pro scored 89.3%; MiniMax M3 scored 83.5%. GPT-5.4 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.4 Pro | MiniMax M3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.4 Pro$30 input / $180 output | MiniMax M3$0.3 input / $1.2 output | MiniMax M3 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.4 Pro74 tok/s | MiniMax M3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.4 Pro151.79 s | MiniMax M3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.4 Pro1.05M | MiniMax M31M | GPT-5.4 Pro lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.4 Pro wins18 benchmarks
| Benchmark | GPT-5.4 Pro | MiniMax M3 | Result |
|---|---|---|---|
| BrowseCompSource | 89.3% | 83.5% | GPT-5.4 Pro leads |
| Terminal-Bench 2.0Source | — | 66% | Not comparable |
| OSWorld-VerifiedSource | — | 70.1% | Not comparable |
| MCP AtlasSource | — | 74.2% | Not comparable |
| Claw-EvalSource | — | 74.5% | Not comparable |
| AA Agentic IndexSource | — | 35.4% | Not comparable |
| τ²-bench resultsSource | — | 88.9% | Not comparable |
| GDPval-AASource | — | 44.7% | Not comparable |
| GDPval-AASource | — | 1395 | 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 | — | 88.4% | Not comparable |
| terminalBenchHardSource | — | 42.4% | Not comparable |
| aaTerminalBench21Source | — | 65.2% | Not comparable |
Coding9 benchmarks
| Benchmark | GPT-5.4 Pro | MiniMax M3 | Result |
|---|---|---|---|
| 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 |
| AA Coding IndexSource | — | 58.6% | Not comparable |
| AA-SciCodeSource | — | 45.4% | Not comparable |
| VIBE V2Source | — | 50.1% | Not comparable |
| SVG-BenchSource | — | 63.7% | Not comparable |
| KernelBench HardSource | — | 28.8% | Not comparable |
Reasoning3 benchmarks
Knowledge11 benchmarks
| Benchmark | GPT-5.4 Pro | MiniMax M3 | Result |
|---|---|---|---|
| HLESource | 58.7% | — | Not comparable |
| FrontierScienceSource | 36.7% | — | Not comparable |
| FrontierScience ResearchSource | 36.7% | — | Not comparable |
| HLE w/o toolsSource | 42.7% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 44.4% | Not comparable |
| AA-GPQA DiamondSource | — | 92.9% | Not comparable |
| AA-HLESource | — | 37.1% | Not comparable |
| AA-Omniscience IndexSource | — | 1.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 15.0% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 16.1% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
MathMiniMax M3 wins5 benchmarks
MultimodalGPT-5.4 Pro wins7 benchmarks
| Benchmark | GPT-5.4 Pro | MiniMax M3 | Result |
|---|---|---|---|
| MMMU-ProSource | 94% | 78.1% | GPT-5.4 Pro leads |
| OfficeQA ProSource | — | 45.1% | Not comparable |
| OmniDocBench 1.5Source | — | 91.6% | Not comparable |
| VideoMMMUSource | — | 84.6% | Not comparable |
| Video-MME (with subtitle)Source | — | 85.4% | Not comparable |
| Design Arena WebsiteSource | — | 1289 | Not comparable |
| AA-MMMU-ProSource | — | 78.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.4 Pro | MiniMax M3 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 82.9% | Not comparable |
Frequently Asked Questions (4)
Which is better, GPT-5.4 Pro or MiniMax M3?
MiniMax M3 is ahead on BenchLM's BenchAlign leaderboard, 69.75 to 60.89. The biggest single separator in this matchup is MMMU-Pro, where the scores are 94% and 78.1%.
Which is better for math, GPT-5.4 Pro or MiniMax M3?
MiniMax M3 has the edge for math in this comparison, averaging 85.7 versus 46.9. GPT-5.4 Pro stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, GPT-5.4 Pro or MiniMax M3?
GPT-5.4 Pro has the edge for agentic tasks in this comparison, averaging 89.3 versus 72.3. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.4 Pro or MiniMax M3?
GPT-5.4 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 94 versus 64.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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