Model comparison
MAI-Thinking-1 vs Step 3.7 Flash
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MAI-Thinking-1 unranked (Not scored); Step 3.7 Flash #110 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MAI-Thinking-1 and Step 3.7 Flash share 3 comparable benchmark results. 2 of 8 categories are comparable. 10 results are unique to MAI-Thinking-1; 26 to Step 3.7 Flash.
Updated July 23, 2026- Shared results
- 3
- MAI-Thinking-1 only
- 10
- Step 3.7 Flash only
- 26
- Comparable categories
- 2 / 8
Treat this as a split decision. MAI-Thinking-1 makes more sense if coding is the priority; Step 3.7 Flash is the better fit if agentic is the priority.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
MAI-Thinking-1 and Step 3.7 Flash 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.
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 | MAI-Thinking-1 | Δ | Step 3.7 Flash |
|---|---|---|---|
| Agentic | MAI-Thinking-146.0 | Margin→ 20.4 | Step 3.7 Flash66.4 |
| Coding | MAI-Thinking-165.5 | Margin← 9.2 | Step 3.7 Flash56.3 |
| Knowledge | MAI-Thinking-172.5 | MarginNo overlap | Step 3.7 FlashNot measured |
| Math | MAI-Thinking-189.7 | MarginNo overlap | Step 3.7 FlashNot measured |
| Inst. Following | MAI-Thinking-185.0 | MarginNo overlap | Step 3.7 FlashNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 46%B 59.5%Winner: Step 3.7 FlashΔ 13.5Terminal-Bench 2.0: MAI-Thinking-1 scored 46%; Step 3.7 Flash scored 59.5%. Step 3.7 Flash wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 52.8%B 56.3%Winner: Step 3.7 FlashΔ 3.5SWE-bench Pro: MAI-Thinking-1 scored 52.8%; Step 3.7 Flash scored 56.3%. Step 3.7 Flash wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MAI-Thinking-1 | Step 3.7 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MAI-Thinking-1Not available | Step 3.7 Flash$0.2 input / $1.15 output | A complete price comparison is not available. |
| Generation speedtokens per second | MAI-Thinking-1Not available | Step 3.7 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MAI-Thinking-1Not available | Step 3.7 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MAI-Thinking-1256K | Step 3.7 Flash256K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticStep 3.7 Flash wins12 benchmarks
| Benchmark | MAI-Thinking-1 | Step 3.7 Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 46% | 59.5% | Step 3.7 Flash leads |
| BrowseCompSource | — | 75.8% | Not comparable |
| DeepSearchQASource | — | 92.8% | Not comparable |
| GDPval-AASource | — | 25.9% | Not comparable |
| ToolathlonSource | — | 49.5% | Not comparable |
| Claw-EvalSource | — | 67.1% | Not comparable |
| HLE w/ toolsSource | — | 47.2% | Not comparable |
| Gert LabsSource | — | 51.57% | Not comparable |
| AA Agentic IndexSource | — | 21.5% | Not comparable |
| τ²-bench resultsSource | — | 98.5% | Not comparable |
| GDPval-AASource | — | 1017 | Not comparable |
| APEX-Agents-AASource | — | 14.8% | Not comparable |
CodingMAI-Thinking-1 wins5 benchmarks
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | MAI-Thinking-1 | Step 3.7 Flash | Result |
|---|---|---|---|
| GPQASource | 84.2% | — | Not comparable |
| GPQA-DSource | 84.2% | — | Not comparable |
| MMLU-ProSource | 85% | — | Not comparable |
| SimpleQASource | 31% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 30.3% | Not comparable |
| AA-GPQA DiamondSource | — | 80.9% | Not comparable |
| AA-HLESource | — | 19.9% | Not comparable |
| AA-Omniscience IndexSource | — | -37.5% | Not comparable |
| AA-Omniscience AccuracySource | — | 25.4% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 84.4% | Not comparable |
Math3 benchmarks
Multimodal4 benchmarks
Frequently Asked Questions (3)
Which is better, MAI-Thinking-1 or Step 3.7 Flash?
MAI-Thinking-1 and Step 3.7 Flash 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 coding, MAI-Thinking-1 or Step 3.7 Flash?
MAI-Thinking-1 has the edge for coding in this comparison, averaging 65.5 versus 56.3. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, MAI-Thinking-1 or Step 3.7 Flash?
Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 66.4 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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