Model comparison
gpt-oss-120b vs Step 3.7 Flash
gpt-oss-120b and Step 3.7 Flash score almost the same on the Noometry Index (36.3 vs 37.3), so choose on price, context window or the category you care about most.
Last verified . 3 shared benchmarks.
StepFunSummary
- They share 3 benchmarks with published results for both. gpt-oss-120b scores higher in 1 category and Step 3.7 Flash in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 52.5 to 42.9.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.18 / $1.11 for Step 3.7 Flash.
- Step 3.7 Flash accepts more context: 256K tokens versus 131K.
Side by side
| gpt-oss-120b | Step 3.7 Flash | |
|---|---|---|
| Provider | OpenAI | StepFun |
| Noometry Index | 36.3 | 37.3 |
| Released | 2025-08-05 | 2026-05-29 |
| Weights | Open | Open |
| Context window | 131K | 256K |
| Max output | 41K | 256K |
| Input $ / M tokens | $0.037 | $0.18 |
| Output $ / M tokens | $0.17 | $1.11 |
| Results tracked | 48 | 5 |
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Category by category
Coding Step 3.7 Flash leads
gpt-oss-120b: 33.5 (#256), Step 3.7 Flash: 40.0 (#150)
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| SciCode | 36% | 40% |
| ALE-Bench | 575.62 | 694.12 |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| WeirdML | 48.2% | — |
| LMArena Coding | 1380 | — |
| AlgoTune | 1.41 | — |
Agentic & Tool Use Not comparable
gpt-oss-120b: 12.2 (#153), Step 3.7 Flash: —
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |
Reasoning Step 3.7 Flash leads
gpt-oss-120b: 20.0 (#245), Step 3.7 Flash: 21.6 (#219)
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| CritPt | 1.1% | 2.3% |
| SimpleBench | 22.1% | — |
| Kagi LLM Benchmark | 58.6% | — |
| NYT Connections (extended) | — | 39.7% |
| Chess Puzzles | 20% | — |
| LMArena Hard Prompts | 1364 | — |
| Mystery Game Puzzles | 2% | — |
| DTBench | 76.3% | — |
| LMCA | 22.1% | — |
| Surface Evolver Bench | 25% | — |
| Epoch Capabilities Index | 139.93 | — |
Math gpt-oss-120b leads
gpt-oss-120b: 52.5 (#50), Step 3.7 Flash: 42.9 (#82)
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| MathArena Final-Answer Competitions | — | 68.5% |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| Omni-MATH | 68.8% | — |
| LMArena Math | 1389 | — |
Knowledge Not comparable
gpt-oss-120b: 42.4 (#96), Step 3.7 Flash: —
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| Vectara Hallucination Rate | 14.2% | — |
| GPQA (HELM) | 68.4% | — |
| LMArena Expert | 1356 | — |
Multilingual Not comparable
gpt-oss-120b: 48.0 (#147), Step 3.7 Flash: —
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| LMArena Non-English | 1351 | — |
| LMArena Chinese | 1385 | — |
| LMArena French | 1369 | — |
| LMArena German | 1353 | — |
| LMArena Japanese | 1331 | — |
| LMArena Korean | 1282 | — |
| LMArena Russian | 1343 | — |
| LMArena Spanish | 1389 | — |
Instruction Following Not comparable
gpt-oss-120b: 69.3 (#173), Step 3.7 Flash: —
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| IFEval | 83.6% | — |
| LMArena Instruction Following | 1318 | — |
Long Context Not comparable
gpt-oss-120b: 31.4 (#278), Step 3.7 Flash: —
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1319 | — |
Writing & Preference Not comparable
gpt-oss-120b: 46.5 (#217), Step 3.7 Flash: —
| Benchmark | gpt-oss-120b | Step 3.7 Flash |
|---|---|---|
| LMArena Text | 1365 | — |
| LMArena Creative Writing | 1275 | — |
| Short-Story Creative Writing | 77.1% | — |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |
| LMArena Multi-Turn | 1340 | — |
Frequently asked questions
Is gpt-oss-120b better than Step 3.7 Flash?
gpt-oss-120b and Step 3.7 Flash score almost the same on the Noometry Index (36.3 vs 37.3), so choose on price, context window or the category you care about most.
Which is cheaper, gpt-oss-120b or Step 3.7 Flash?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Step 3.7 Flash lists at $0.18 and $1.11.
Is gpt-oss-120b or Step 3.7 Flash better for coding?
Step 3.7 Flash scores higher on coding benchmarks: 40.0 versus 33.5 in the Noometry coding category.
Which has the bigger context window?
Step 3.7 Flash does, with 256K tokens against 131K.
How many benchmarks do gpt-oss-120b and Step 3.7 Flash share?
3 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Step 3.7 Flash has 5.