Model comparison
GPT-5.4 mini vs MAI-Thinking-1
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.4 mini #75 (Estimated); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.4 mini and MAI-Thinking-1 share 2 comparable benchmark results. 3 of 8 categories are comparable. 28 results are unique to GPT-5.4 mini; 11 to MAI-Thinking-1.
Updated July 23, 2026- Shared results
- 2
- GPT-5.4 mini only
- 28
- MAI-Thinking-1 only
- 11
- Comparable categories
- 3 / 8
Treat this as a split decision. GPT-5.4 mini makes more sense if agentic is the priority or you need the larger 400K context window; MAI-Thinking-1 is the better fit if mathematics is the priority.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 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
GPT-5.4 mini and MAI-Thinking-1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
GPT-5.4 mini gives you the larger context window at 400K, compared with 256K for MAI-Thinking-1.
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 mini | Δ | MAI-Thinking-1 |
|---|---|---|---|
| Math | GPT-5.4 mini21.7 | Margin→ 68.0 | MAI-Thinking-189.7 |
| Knowledge | GPT-5.4 mini47.8 | Margin→ 24.7 | MAI-Thinking-172.5 |
| Agentic | GPT-5.4 mini65.7 | Margin← 19.7 | MAI-Thinking-146.0 |
| Coding | GPT-5.4 miniNot measured | MarginNo overlap | MAI-Thinking-165.5 |
| Multimodal | GPT-5.4 mini76.6 | MarginNo overlap | MAI-Thinking-1Not measured |
| Inst. Following | GPT-5.4 miniNot measured | MarginNo overlap | MAI-Thinking-185.0 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 60%B 46%Winner: GPT-5.4 miniΔ 14Terminal-Bench 2.0: GPT-5.4 mini scored 60%; MAI-Thinking-1 scored 46%. GPT-5.4 mini wins this benchmark. - Source ↗
GPQA
KnowledgeA 88%B 84.2%Winner: GPT-5.4 miniΔ 3.8GPQA: GPT-5.4 mini scored 88%; MAI-Thinking-1 scored 84.2%. GPT-5.4 mini wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.4 mini | MAI-Thinking-1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.4 mini$0.75 input / $4.5 output | MAI-Thinking-1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.4 mini201 tok/s | MAI-Thinking-1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.4 mini3.85 s | MAI-Thinking-1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.4 mini400K | MAI-Thinking-1256K | GPT-5.4 mini lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.4 mini wins9 benchmarks
| Benchmark | GPT-5.4 mini | MAI-Thinking-1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 60% | 46% | GPT-5.4 mini leads |
| OSWorld-VerifiedSource | 72.1% | — | Not comparable |
| MCP AtlasSource | 57.7% | — | Not comparable |
| ToolathlonSource | 42.9% | — | Not comparable |
| τ²-bench resultsSource | 83.3% | — | Not comparable |
| AA Agentic IndexSource | 30.2% | — | Not comparable |
| APEX-Agents-AASource | 28.2% | — | Not comparable |
| GDPval-AASource | 33.6% | — | Not comparable |
| GDPval-AASource | 1171 | — | Not comparable |
Coding7 benchmarks
| Benchmark | GPT-5.4 mini | MAI-Thinking-1 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 47.97% | — | Not comparable |
| AA Coding IndexSource | 56.1% | — | Not comparable |
| AA-SciCodeSource | 49.9% | — | Not comparable |
| FrontierCode 1.1 MainSource | 27.0% | — | Not comparable |
| SWE-bench VerifiedSource | — | 73.5% | Not comparable |
| SWE-bench ProSource | — | 52.8% | Not comparable |
| Terminal-Bench 2.0Source | — | 46.0% | Not comparable |
Reasoning3 benchmarks
KnowledgeMAI-Thinking-1 wins12 benchmarks
| Benchmark | GPT-5.4 mini | MAI-Thinking-1 | Result |
|---|---|---|---|
| GPQASource | 88% | 84.2% | GPT-5.4 mini leads |
| HLESource | 41.5% | — | Not comparable |
| HLE w/o toolsSource | 28.2% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 40.0% | — | Not comparable |
| AA-GPQA DiamondSource | 87.5% | — | Not comparable |
| AA-HLESource | 26.6% | — | Not comparable |
| AA-Omniscience IndexSource | -18.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 37.5% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 89.8% | — | Not comparable |
| GPQA-DSource | — | 84.2% | Not comparable |
| MMLU-ProSource | — | 85% | Not comparable |
| SimpleQASource | — | 31% | Not comparable |
MathMAI-Thinking-1 wins5 benchmarks
Multimodal3 benchmarks
Frequently Asked Questions (4)
Which is better, GPT-5.4 mini or MAI-Thinking-1?
GPT-5.4 mini and MAI-Thinking-1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, GPT-5.4 mini or MAI-Thinking-1?
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 47.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.4 mini or MAI-Thinking-1?
MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 21.7. GPT-5.4 mini stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, GPT-5.4 mini or MAI-Thinking-1?
GPT-5.4 mini has the edge for agentic tasks in this comparison, averaging 65.7 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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