Model comparison
gpt-oss-120b vs Nemotron 3.5 Lightning
Nemotron 3.5 Lightning is the stronger model overall, scoring 40.0 to 36.3 on the Noometry Index.
Last verified . 18 shared benchmarks.
NVIDIASummary
- They share 18 benchmarks with published results for both. gpt-oss-120b scores higher in 3 categories and Nemotron 3.5 Lightning in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 52.5 to 37.5.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.05 / $0.20 for Nemotron 3.5 Lightning.
- Nemotron 3.5 Lightning accepts more context: 262K tokens versus 131K.
Side by side
| gpt-oss-120b | Nemotron 3.5 Lightning | |
|---|---|---|
| Provider | OpenAI | NVIDIA |
| Noometry Index | 36.3 | 40.0 |
| Released | 2025-08-05 | 2026-08-11 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 41K | 262K |
| Input $ / M tokens | $0.037 | $0.05 |
| Output $ / M tokens | $0.17 | $0.20 |
| Results tracked | 48 | 18 |
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Category by category
Coding Nemotron 3.5 Lightning leads
gpt-oss-120b: 33.5 (#256), Nemotron 3.5 Lightning: 40.4 (#141)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Coding | 1380 | 1375 |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| SciCode | 36% | — |
| WeirdML | 48.2% | — |
| ALE-Bench | 575.62 | — |
| AlgoTune | 1.41 | — |
Agentic & Tool Use Not comparable
gpt-oss-120b: 12.2 (#153), Nemotron 3.5 Lightning: —
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |
Reasoning Nemotron 3.5 Lightning leads
gpt-oss-120b: 20.0 (#245), Nemotron 3.5 Lightning: 26.8 (#127)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Hard Prompts | 1364 | 1337 |
| SimpleBench | 22.1% | — |
| Kagi LLM Benchmark | 58.6% | — |
| CritPt | 1.1% | — |
| Chess Puzzles | 20% | — |
| 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), Nemotron 3.5 Lightning: 37.5 (#155)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Math | 1389 | 1359 |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| Omni-MATH | 68.8% | — |
Knowledge gpt-oss-120b leads
gpt-oss-120b: 42.4 (#96), Nemotron 3.5 Lightning: 37.5 (#154)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Expert | 1356 | 1356 |
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| Vectara Hallucination Rate | 14.2% | — |
| GPQA (HELM) | 68.4% | — |
Multilingual gpt-oss-120b leads
gpt-oss-120b: 48.0 (#147), Nemotron 3.5 Lightning: 44.0 (#180)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Non-English | 1351 | 1295 |
| LMArena Chinese | 1385 | 1359 |
| LMArena French | 1369 | 1366 |
| LMArena German | 1353 | 1282 |
| LMArena Japanese | 1331 | 1206 |
| LMArena Korean | 1282 | 1238 |
| LMArena Russian | 1343 | 1253 |
| LMArena Spanish | 1389 | 1345 |
Instruction Following Too close to call
gpt-oss-120b: 69.3 (#173), Nemotron 3.5 Lightning: 69.6 (#170)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Instruction Following | 1318 | 1318 |
| IFEval | 83.6% | — |
Long Context Nemotron 3.5 Lightning leads
gpt-oss-120b: 31.4 (#278), Nemotron 3.5 Lightning: 39.9 (#165)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Longer Query | 1319 | 1314 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference Nemotron 3.5 Lightning leads
gpt-oss-120b: 46.5 (#217), Nemotron 3.5 Lightning: 48.5 (#201)
| Benchmark | gpt-oss-120b | Nemotron 3.5 Lightning |
|---|---|---|
| LMArena Text | 1365 | 1327 |
| LMArena Creative Writing | 1275 | 1254 |
| EQ-Bench Creative Writing | 961 | 1280 |
| LMArena Multi-Turn | 1340 | 1328 |
| Short-Story Creative Writing | 77.1% | — |
| WildBench | 84.5% | — |
Frequently asked questions
Is gpt-oss-120b better than Nemotron 3.5 Lightning?
Nemotron 3.5 Lightning is the stronger model overall, scoring 40.0 to 36.3 on the Noometry Index.
Which is cheaper, gpt-oss-120b or Nemotron 3.5 Lightning?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Nemotron 3.5 Lightning lists at $0.05 and $0.20.
Is gpt-oss-120b or Nemotron 3.5 Lightning better for coding?
Nemotron 3.5 Lightning scores higher on coding benchmarks: 40.4 versus 33.5 in the Noometry coding category.
Which has the bigger context window?
Nemotron 3.5 Lightning does, with 262K tokens against 131K.
How many benchmarks do gpt-oss-120b and Nemotron 3.5 Lightning share?
18 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Nemotron 3.5 Lightning has 18.