Model comparison
GPT-5.2 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-5.2 #23; MiniMax M3 #18
BenchAlign evidence: GPT-5.2 estimated; MiniMax M3 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2 and MiniMax M3 share 18 comparable benchmark results. 4 of 8 categories are comparable. 11 results are unique to GPT-5.2; 27 to MiniMax M3.
Updated July 16, 2026- Shared results
- 18
- GPT-5.2 only
- 11
- MiniMax M3 only
- 27
- Comparable categories
- 4 / 8
Pick GPT-5.2 if you want the stronger benchmark profile. MiniMax M3 only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.2 is clearly ahead on the provisional aggregate, 74 to 70. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in multimodal & grounded, where it averages 80.4 against 64.9. The single biggest benchmark swing on the page is OSWorld-Verified, 47.3% to 70.1%. MiniMax M3 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M3. That is roughly 11.7x on output cost alone. GPT-5.2 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. MiniMax M3 gives you the larger context window at 1M, compared with 400K for GPT-5.2.
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-5.2 | Δ | MiniMax M3 |
|---|---|---|---|
| Math | GPT-5.235.2 | Margin→ 50.5 | MiniMax M385.7 |
| Agentic | GPT-5.255.7 | Margin→ 16.6 | MiniMax M372.3 |
| Multimodal | GPT-5.280.4 | Margin← 15.5 | MiniMax M364.9 |
| Coding | GPT-5.270.6 | Margin→ 1.6 | MiniMax M372.2 |
| Reasoning | GPT-5.252.9 | MarginNo overlap | MiniMax M3Not measured |
| Knowledge | GPT-5.292.4 | MarginNo overlap | MiniMax M3Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
OSWorld-Verified
AgenticA 47.3%B 70.1%Winner: MiniMax M3Δ 22.8OSWorld-Verified: GPT-5.2 scored 47.3%; MiniMax M3 scored 70.1%. MiniMax M3 wins this benchmark. - Source ↗
BrowseComp
AgenticA 65.8%B 83.5%Winner: MiniMax M3Δ 17.7BrowseComp: GPT-5.2 scored 65.8%; MiniMax M3 scored 83.5%. MiniMax M3 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 55.6%B 59%Winner: MiniMax M3Δ 3.4SWE-bench Pro: GPT-5.2 scored 55.6%; MiniMax M3 scored 59%. MiniMax M3 wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 79.5%B 78.1%Winner: GPT-5.2Δ 1.4MMMU-Pro: GPT-5.2 scored 79.5%; MiniMax M3 scored 78.1%. GPT-5.2 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 80%B 80.5%Winner: MiniMax M3Δ 0.5SWE-bench Verified: GPT-5.2 scored 80%; MiniMax M3 scored 80.5%. MiniMax M3 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.2 | MiniMax M3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 output | MiniMax M3$0.3 input / $1.2 output | MiniMax M3 has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.273 tok/s | MiniMax M3Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | MiniMax M3Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2400K | MiniMax M31M | MiniMax M3 lists the larger context window. |
Benchmark Deep Dive
AgenticMiniMax M3 wins18 benchmarks
| Benchmark | GPT-5.2 | MiniMax M3 | Result |
|---|---|---|---|
| BrowseCompSource | 65.8% | 83.5% | MiniMax M3 leads |
| OSWorld-VerifiedSource | 47.3% | 70.1% | MiniMax M3 leads |
| τ²-bench resultsSource | 84.8% | 88.9% | MiniMax M3 leads |
| Gert LabsSource | 46.54% | — | Not comparable |
| JobBenchSource | 34.3% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 66% | Not comparable |
| MCP AtlasSource | — | 74.2% | Not comparable |
| Claw-EvalSource | — | 74.5% | Not comparable |
| AA Agentic IndexSource | — | 35.4% | 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 | — | 6.7% | Not comparable |
CodingMiniMax M3 wins12 benchmarks
| Benchmark | GPT-5.2 | MiniMax M3 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80% | 80.5% | MiniMax M3 leads |
| SWE-bench ProSource | 55.6% | 59% | MiniMax M3 leads |
| Vibe Code BenchSource | 53.50% | — | Not comparable |
| Terminal-Bench HardSource | 47.0% | 42.4% | GPT-5.2 leads |
| AA-SciCodeSource | 52.1% | 45.4% | GPT-5.2 leads |
| Terminal-Bench 2.0Source | — | 66.0% | Not comparable |
| NL2RepoSource | — | 42.1% | Not comparable |
| AA Coding IndexSource | — | 58.6% | 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 |
Reasoning3 benchmarks
Knowledge8 benchmarks
| Benchmark | GPT-5.2 | MiniMax M3 | Result |
|---|---|---|---|
| GPQASource | 92.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 42.2% | 44.4% | MiniMax M3 leads |
| AA-GPQA DiamondSource | 90.3% | 92.9% | MiniMax M3 leads |
| AA-HLESource | 35.4% | 37.1% | MiniMax M3 leads |
| AA-Omniscience IndexSource | -1.0% | 1.4% | MiniMax M3 leads |
| AA-Omniscience AccuracySource | 43.8% | 15.0% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 79.7% | 16.1% | MiniMax M3 leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
MathMiniMax M3 wins4 benchmarks
MultimodalGPT-5.2 wins10 benchmarks
| Benchmark | GPT-5.2 | MiniMax M3 | Result |
|---|---|---|---|
| MMMU-ProSource | 79.5% | 78.1% | GPT-5.2 leads |
| MathVisionSource | 83.0% | — | Not comparable |
| CharXivSource | 82.1% | — | Not comparable |
| V*Source | 75.9% | — | Not comparable |
| Design Arena WebsiteSource | 1229 | 1294 | MiniMax M3 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 |
| AA-MMMU-ProSource | — | 78.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.2 | MiniMax M3 | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 82.9% | MiniMax M3 leads |
Frequently Asked Questions (5)
Which is better, GPT-5.2 or MiniMax M3?
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 74 to 70. The biggest single separator in this matchup is OSWorld-Verified, where the scores are 47.3% and 70.1%.
Which is better for coding, GPT-5.2 or MiniMax M3?
MiniMax M3 has the edge for coding in this comparison, averaging 72.2 versus 70.6. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.2 or MiniMax M3?
MiniMax M3 has the edge for math in this comparison, averaging 85.7 versus 35.2. GPT-5.2 stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, GPT-5.2 or MiniMax M3?
MiniMax M3 has the edge for agentic tasks in this comparison, averaging 72.3 versus 55.7. Inside this category, OSWorld-Verified is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.2 or MiniMax M3?
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.4 versus 64.9. Inside this category, Design Arena Website is the benchmark that creates the most daylight between them.
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