Model comparison
GPT-5.2 vs Step 3.7 Flash
Head-to-head evidence from 17 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GPT-5.2 #23; Step 3.7 Flash unranked
BenchAlign evidence: GPT-5.2 estimated; Step 3.7 Flash estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2 and Step 3.7 Flash share 17 comparable benchmark results. 2 of 8 categories are comparable. 12 results are unique to GPT-5.2; 13 to Step 3.7 Flash.
Updated July 16, 2026- Shared results
- 17
- GPT-5.2 only
- 12
- Step 3.7 Flash only
- 13
- Comparable categories
- 2 / 8
Pick GPT-5.2 if you want the stronger benchmark profile. Step 3.7 Flash only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 6 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
GPT-5.2 is clearly ahead on the provisional aggregate, 74 to 57. 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 coding, where it averages 70.6 against 56.3. The single biggest benchmark swing on the page is BrowseComp, 65.8% to 75.8%. Step 3.7 Flash does hit back in agentic, 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 $0.20 input / $1.15 output per 1M tokens for Step 3.7 Flash. That is roughly 12.2x on output cost alone. GPT-5.2 gives you the larger context window at 400K, 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-5.2 | Δ | Step 3.7 Flash |
|---|---|---|---|
| Coding | GPT-5.270.6 | Margin← 14.3 | Step 3.7 Flash56.3 |
| Agentic | GPT-5.255.7 | Margin→ 10.7 | Step 3.7 Flash66.4 |
| Reasoning | GPT-5.252.9 | MarginNo overlap | Step 3.7 FlashNot measured |
| Knowledge | GPT-5.292.4 | MarginNo overlap | Step 3.7 FlashNot measured |
| Math | GPT-5.235.2 | MarginNo overlap | Step 3.7 FlashNot measured |
| Multimodal | GPT-5.280.4 | MarginNo overlap | Step 3.7 FlashNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 65.8%B 75.8%Winner: Step 3.7 FlashΔ 10BrowseComp: GPT-5.2 scored 65.8%; Step 3.7 Flash scored 75.8%. Step 3.7 Flash wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 55.6%B 56.3%Winner: Step 3.7 FlashΔ 0.7SWE-bench Pro: GPT-5.2 scored 55.6%; 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 | GPT-5.2 | Step 3.7 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 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-5.273 tok/s | Step 3.7 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | Step 3.7 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2400K | Step 3.7 Flash256K | GPT-5.2 lists the larger context window. |
Benchmark Deep Dive
AgenticStep 3.7 Flash wins14 benchmarks
| Benchmark | GPT-5.2 | Step 3.7 Flash | Result |
|---|---|---|---|
| BrowseCompSource | 65.8% | 75.8% | Step 3.7 Flash leads |
| OSWorld-VerifiedSource | 47.3% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | 98.5% | Step 3.7 Flash leads |
| Gert LabsSource | 46.54% | 51.57% | Step 3.7 Flash leads |
| JobBenchSource | 34.3% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 59.5% | 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 |
| AA Agentic IndexSource | — | 21.5% | Not comparable |
| GDPval-AASource | — | 1017 | Not comparable |
| APEX-Agents-AASource | — | 14.8% | Not comparable |
CodingGPT-5.2 wins7 benchmarks
| Benchmark | GPT-5.2 | Step 3.7 Flash | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 80% | — | Not comparable |
| SWE-bench ProSource | 55.6% | 56.3% | Step 3.7 Flash leads |
| Vibe Code BenchSource | 53.50% | — | Not comparable |
| Terminal-Bench HardSource | 47.0% | 35.6% | GPT-5.2 leads |
| AA-SciCodeSource | 52.1% | 40.0% | GPT-5.2 leads |
| Terminal-Bench 2.0Source | — | 59.5% | Not comparable |
| AA Coding IndexSource | — | 39.6% | Not comparable |
Reasoning3 benchmarks
Knowledge7 benchmarks
| Benchmark | GPT-5.2 | Step 3.7 Flash | Result |
|---|---|---|---|
| GPQASource | 92.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 42.2% | 30.3% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 90.3% | 80.9% | GPT-5.2 leads |
| AA-HLESource | 35.4% | 19.9% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -1.0% | -37.5% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 43.8% | 25.4% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 79.7% | 84.4% | GPT-5.2 leads |
Math3 benchmarks
Multimodal7 benchmarks
| Benchmark | GPT-5.2 | Step 3.7 Flash | Result |
|---|---|---|---|
| MMMU-ProSource | 79.5% | — | Not comparable |
| MathVisionSource | 83.0% | — | Not comparable |
| CharXivSource | 82.1% | — | Not comparable |
| V*Source | 75.9% | 95.3% | Step 3.7 Flash leads |
| Design Arena WebsiteSource | 1229 | 1218 | GPT-5.2 leads |
| SimpleVQASource | — | 79.2% | Not comparable |
| AA-MMMU-ProSource | — | 75.3% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.2 | Step 3.7 Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 67.3% | GPT-5.2 leads |
Frequently Asked Questions (3)
Which is better, GPT-5.2 or Step 3.7 Flash?
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 74 to 57. The biggest single separator in this matchup is BrowseComp, where the scores are 65.8% and 75.8%.
Which is better for coding, GPT-5.2 or Step 3.7 Flash?
GPT-5.2 has the edge for coding in this comparison, averaging 70.6 versus 56.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.2 or Step 3.7 Flash?
Step 3.7 Flash has the edge for agentic tasks in this comparison, averaging 66.4 versus 55.7. Inside this category, τ²-bench results is the benchmark that creates the most daylight between them.
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