Model comparison
GPT-4.1 mini vs Step 3.7 Flash
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
BenchAlign evidence: GPT-4.1 mini estimated; Step 3.7 Flash estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 mini and Step 3.7 Flash share 18 comparable benchmark results. 1 of 8 categories are comparable. 5 results are unique to GPT-4.1 mini; 12 to Step 3.7 Flash.
Updated July 16, 2026- Shared results
- 18
- GPT-4.1 mini only
- 5
- Step 3.7 Flash only
- 12
- Comparable categories
- 1 / 8
Pick Step 3.7 Flash if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Step 3.7 Flash is clearly ahead on the provisional aggregate, 57 to 42. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Step 3.7 Flash's sharpest advantage is in coding, where it averages 56.3 against 23.6.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. Step 3.7 Flash is the reasoning model in the pair, while GPT-4.1 mini 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-4.1 mini gives you the larger context window at 1M, compared with 256K for Step 3.7 Flash.
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-4.1 mini | Δ | Step 3.7 Flash |
|---|---|---|---|
| Coding | GPT-4.1 mini23.6 | Margin→ 32.7 | Step 3.7 Flash56.3 |
| Agentic | GPT-4.1 miniNot measured | MarginNo overlap | Step 3.7 Flash66.4 |
| Knowledge | GPT-4.1 mini64.2 | MarginNo overlap | Step 3.7 FlashNot measured |
| Math | GPT-4.1 mini4.5 | MarginNo overlap | Step 3.7 FlashNot measured |
| Inst. Following | GPT-4.1 mini88.5 | MarginNo overlap | Step 3.7 FlashNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 mini | Step 3.7 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1 mini$0.4 input / $1.6 output | Step 3.7 Flash$0.2 input / $1.15 output | Step 3.7 Flash has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1 mini80 tok/s | Step 3.7 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-4.1 mini0.76 s | Step 3.7 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-4.1 mini1M | Step 3.7 Flash256K | GPT-4.1 mini lists the larger context window. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | GPT-4.1 mini | Step 3.7 Flash | Result |
|---|---|---|---|
| AA Agentic IndexSource | 1.7% | 21.5% | Step 3.7 Flash leads |
| τ²-bench resultsSource | 52.9% | 98.5% | Step 3.7 Flash leads |
| GDPval-AASource | 0.1% | 25.9% | Step 3.7 Flash leads |
| GDPval-AASource | 503 | 1017 | Step 3.7 Flash leads |
| Terminal-Bench 2.0Source | — | 59.5% | Not comparable |
| BrowseCompSource | — | 75.8% | Not comparable |
| DeepSearchQASource | — | 92.8% | 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 |
| APEX-Agents-AASource | — | 14.8% | Not comparable |
CodingStep 3.7 Flash wins6 benchmarks
| Benchmark | GPT-4.1 mini | Step 3.7 Flash | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 23.6% | — | Not comparable |
| AA Coding IndexSource | 20.2% | 39.6% | Step 3.7 Flash leads |
| Terminal-Bench HardSource | 7.6% | 35.6% | Step 3.7 Flash leads |
| AA-SciCodeSource | 40.4% | 40.0% | GPT-4.1 mini leads |
| SWE-bench ProSource | — | 56.3% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.5% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GPT-4.1 mini | Step 3.7 Flash | Result |
|---|---|---|---|
| MMLUSource | 87.5% | — | Not comparable |
| GPQASource | 64.2% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 14.8% | 30.3% | Step 3.7 Flash leads |
| AA-GPQA DiamondSource | 66.4% | 80.9% | Step 3.7 Flash leads |
| AA-HLESource | 4.6% | 19.9% | Step 3.7 Flash leads |
| AA-Omniscience IndexSource | -50.1% | -37.5% | Step 3.7 Flash leads |
| AA-Omniscience AccuracySource | 17.5% | 25.4% | Step 3.7 Flash leads |
| AA-Omniscience Hallucination RateSource | 82.0% | 84.4% | GPT-4.1 mini leads |
Math1 benchmarks
| Benchmark | GPT-4.1 mini | Step 3.7 Flash | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 4.483% | — | Not comparable |
Multimodal4 benchmarks
Frequently Asked Questions (2)
Which is better, GPT-4.1 mini or Step 3.7 Flash?
Step 3.7 Flash is ahead on BenchLM's provisional leaderboard, 57 to 42.
Which is better for coding, GPT-4.1 mini or Step 3.7 Flash?
Step 3.7 Flash has the edge for coding in this comparison, averaging 56.3 versus 23.6. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.
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