gpt-oss-120b vs Nemotron 3.5 Super VL
Updated October 21, 2026. 9 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Nemotron 3.5 Super VL for coding: it scores 65.5 on the Vibe Coding Index against 34.5 for gpt-oss-120b, though on 1 benchmark against 2.
gpt-oss-120b is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 9
- gpt-oss-120b only
- 69
- Nemotron 3.5 Super VL only
- 7
- Like-for-like categories
- 5 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL scores 65.5 against 34.5.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads, 26.5 against 11.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only gpt-oss-120b has a AA Agentic Index result, 3.7.
Directional only
Reasoning
GPQA Diamond
No call
Only gpt-oss-120b has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only gpt-oss-120b has a AIME result, 92.6%.
Directional only
Knowledge
MMLU Pro
No call
Only gpt-oss-120b has a MMLU Pro result, 79.2%.
Directional only
Web design
Design Arena: websites
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads, 1171 against 968.
Same board, both measured
Long documents
Listed context window
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Super VL
gpt-oss-120b $0.0004, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only gpt-oss-120b has the number, $0.51.
Directional only
At a glance
- Coding index
- gpt-oss-120b 34.5 from 2 benchmarks, Nemotron 3.5 Super VL 65.5 from 1 benchmark.
- Widest category
- Web design, 24.1 points apart on average over 5 shared benchmarks.
- Widest single gap
- Design Arena: 3D: gpt-oss-120b 901 against Nemotron 3.5 Super VL 1132, 28.9 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-120b $0.60 against Nemotron 3.5 Super VL $0.50 per million output tokens, 1.2x apart.
- Context window
- gpt-oss-120b takes 131K tokens, Nemotron 3.5 Super VL 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | gpt-oss-120b | Bars | Nemotron 3.5 Super VL | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Web design | 0 | 5 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 9 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index01
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Aider polyglot | 41.8% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified | 26.0% | Not measured | Only gpt-oss-120b measured |
| LiveBench coding | Not measured | 65.5% | Only Nemotron 3.5 Super VL measured |
| AA Coding Index | 30.4 | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Vals AI) | 83.2% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified (Vals AI) | 33.6% | Not measured | Only gpt-oss-120b measured |
| LiveCodeBench (Artificial Analysis run) | 87.8% | Not measured | Only gpt-oss-120b measured |
| SciCode | 34.0% | 47.8% | Nemotron 3.5 Super VL |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench | 18.7% | Not measured | Only gpt-oss-120b measured |
| WeirdML | 48.2% | Not measured | Only gpt-oss-120b measured |
| ALE-Bench | 575.6 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: coding | 1379 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: software and IT | 1387 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.6 | 26.5 | Nemotron 3.5 Super VL |
| Epoch Capabilities Index | 139.8 | Not measured | Only gpt-oss-120b measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Agentic Index | 3.7 | Not measured | Only gpt-oss-120b measured |
| LiveBench research | Not measured | 70.9% | Only Nemotron 3.5 Super VL measured |
| LiveBench browser | Not measured | 4.0% | Only Nemotron 3.5 Super VL measured |
| LiveBench long agentic | Not measured | 15.8% | Only Nemotron 3.5 Super VL measured |
| τ²-Bench Telecom | 65.8% | Not measured | Only gpt-oss-120b measured |
| APEX-Agents | 4.4% | Not measured | Only gpt-oss-120b measured |
| METR time horizons | 56.6% | Not measured | Only gpt-oss-120b measured |
| Vending-Bench 2 | -$22 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | Not measured | Only gpt-oss-120b measured |
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| GPQA Diamond (Artificial Analysis run) | 78.2% | Not measured | Only gpt-oss-120b measured |
| Humanity's Last Exam (Artificial Analysis run) | 19.6% | 30.7% | Nemotron 3.5 Super VL |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only gpt-oss-120b measured |
| SimpleBench | 22.1% | Not measured | Only gpt-oss-120b measured |
| Mystery game puzzles | 2.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: hard prompts | 1364 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: expert | 1356 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: hard prompts in English | 1368 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AIME | 92.6% | Not measured | Only gpt-oss-120b measured |
| MATH 500 (Vals AI) | 94.8% | Not measured | Only gpt-oss-120b measured |
| MGSM (Vals AI) | 92.0% | Not measured | Only gpt-oss-120b measured |
| AA Math Index | 93.4 | Not measured | Only gpt-oss-120b measured |
| AIME 2025 (Artificial Analysis run) | 93.4% | Not measured | Only gpt-oss-120b measured |
| OTIS Mock AIME | 88.9% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: math | 1389 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: mathematical work | 1386 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| MMLU Pro | 79.2% | Not measured | Only gpt-oss-120b measured |
| LegalBench (Vals AI) | 75.9% | Not measured | Only gpt-oss-120b measured |
| CaseLaw (Vals AI) | 48.8% | Not measured | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 58.2% | Not measured | Only gpt-oss-120b measured |
| TaxEval (Vals AI) | 71.6% | Not measured | Only gpt-oss-120b measured |
| MedQA (Vals AI) | 91.4% | Not measured | Only gpt-oss-120b measured |
| MMLU Pro (Artificial Analysis run) | 80.8% | Not measured | Only gpt-oss-120b measured |
| LMArena Text: science | 1382 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: medicine and healthcare | 1388 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: legal and government | 1355 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: business and finance | 1359 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Design Arena: websites | 968 | 1171 | Nemotron 3.5 Super VL |
| Design Arena: UI components | 927 | 1148 | Nemotron 3.5 Super VL |
| Design Arena: game dev | 992 | 1108 | Nemotron 3.5 Super VL |
| Design Arena: data viz | 987 | Not measured | Only gpt-oss-120b measured |
| Design Arena: 3D | 901 | 1132 | Nemotron 3.5 Super VL |
| Design Arena: all code categories | 963 | 1155 | Nemotron 3.5 Super VL |
| LiveBench design | Not measured | 60.7% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| IFBench | 69.0% | Not measured | Only gpt-oss-120b measured |
| Long context reasoning (AA-LCR) | 52.0% | 69.0% | Nemotron 3.5 Super VL |
| DTBench | 76.3% | Not measured | Only gpt-oss-120b measured |
| LMCA | 22.1% | Not measured | Only gpt-oss-120b measured |
| Fiction.LiveBench | 44.4% | Not measured | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | 77.1% | Not measured | Only gpt-oss-120b measured |
| Surface Evolver Bench | 25.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text | 1366 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: instruction following | 1318 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: creative writing | 1274 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: English | 1375 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: non-English | 1351 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Chinese | 1385 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: German | 1353 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Japanese | 1331 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Korean | 1282 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: French | 1370 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Spanish | 1389 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Russian | 1343 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: Polish | 1353 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: multi-turn | 1340 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: longer queries | 1319 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: writing and language | 1306 | Not measured | Only gpt-oss-120b measured |
| LMArena Text: entertainment and media | 1292 | Not measured | Only gpt-oss-120b measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-120b | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Nemotron 3.5 Super VL costs less
Repository review
50K input + 3K output tokens
Nemotron 3.5 Super VL costs less
Agent loop
200K input + 10K output tokens
Nemotron 3.5 Super VL costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI gpt-oss-120b | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | OpenAI | NVIDIA |
| Weights | Open weights | Open weights |
| Released | August 5, 2025 | October 15, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.15 | $0.15 |
| Output $/Mtok | $0.60 | $0.50 |
| Coding index | 34.5 | 65.5 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.51 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-120b better than Nemotron 3.5 Super VL for coding?
Pick Nemotron 3.5 Super VL for coding: it scores 65.5 on the Vibe Coding Index against 34.5 for gpt-oss-120b, though on 1 benchmark against 2. gpt-oss-120b is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, gpt-oss-120b or Nemotron 3.5 Super VL?
gpt-oss-120b costs $0.15 per million input tokens and $0.60 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, gpt-oss-120b or Nemotron 3.5 Super VL?
Nemotron 3.5 Super VL, with 1.05M tokens against 131K.
How many benchmarks is the gpt-oss-120b vs Nemotron 3.5 Super VL comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. gpt-oss-120b's coding index rests on 2 independent benchmarks and Nemotron 3.5 Super VL's on 1. Where only one model has a result, the page says so instead of naming a winner.