gpt-oss-120b vs Qwen3.6 Plus
Updated October 21, 2026. 59 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3.6 Plus for coding: it scores 37.4 on the Vibe Coding Index against 34.5 for gpt-oss-120b, though on 1 benchmark against 2.
Pick gpt-oss-120b when output tokens cost 3.3x less, or when a solved task costs $0.51 against $1.19.
- Shared results
- 59
- gpt-oss-120b only
- 19
- Qwen3.6 Plus only
- 24
- Like-for-like categories
- 8 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
Qwen3.6 Plus
Qwen3.6 Plus scores 37.4 against 34.5.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.6 Plus
Qwen3.6 Plus leads, 27.0 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
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.4% against 78.5%.
Same board, both measured
Math
AIME
Qwen3.6 Plus
Qwen3.6 Plus leads, 94.6% against 92.6%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.7% against 79.2%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.6 Plus
Qwen3.6 Plus leads, 1243 against 968.
Same board, both measured
Long documents
Listed context window
Qwen3.6 Plus
Qwen3.6 Plus takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-120b
gpt-oss-120b $0.0004, Qwen3.6 Plus $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
gpt-oss-120b
gpt-oss-120b $0.51, Qwen3.6 Plus $1.19.
Published attempt cost and pass rate
At a glance
- Coding index
- gpt-oss-120b 34.5 from 2 benchmarks, Qwen3.6 Plus 37.4 from 1 benchmark.
- Widest category
- Web design, 33.6 points apart on average over 6 shared benchmarks.
- Widest single gap
- SWE-bench Verified (Vals AI): gpt-oss-120b 33.6% against Qwen3.6 Plus 73.4%, 39.8 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-120b $0.60 against Qwen3.6 Plus $1.95 per million output tokens, 3.3x apart.
- Context window
- gpt-oss-120b takes 131K tokens, Qwen3.6 Plus 1M.
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 | Qwen3.6 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 8 | ||
| Math | 0 | 4 | ||
| Knowledge | 0 | 9 | ||
| Web design | 0 | 6 | ||
| General | 0 | 21 | ||
| All shared boards | 0 | 59 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index07
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Aider polyglot | 41.8% | Not measured | Only gpt-oss-120b measured |
| SWE-bench Verified | 26.0% | Not measured | Only gpt-oss-120b measured |
| LMArena WebDev | Not measured | 1461 | Only Qwen3.6 Plus measured |
| AA Coding Index | 30.4 | 54.5 | Qwen3.6 Plus |
| LiveCodeBench (Vals AI) | 83.2% | 86.0% | Qwen3.6 Plus |
| SWE-bench Verified (Vals AI) | 33.6% | 73.4% | Qwen3.6 Plus |
| Vibe Code Bench (Vals AI) | Not measured | 25.6% | Only Qwen3.6 Plus measured |
| Code migration (Vals AI) | Not measured | 11.1% | Only Qwen3.6 Plus measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.6 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 53.2% | Only Qwen3.6 Plus measured |
| LiveCodeBench (Artificial Analysis run) | 87.8% | Not measured | Only gpt-oss-120b measured |
| SciCode | 34.0% | Not measured | Only gpt-oss-120b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | 43.9% | Qwen3.6 Plus |
| 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 | 670.1 | Qwen3.6 Plus |
| LMArena Text: coding | 1379 | 1467 | Qwen3.6 Plus |
| LMArena Text: software and IT | 1387 | 1462 | Qwen3.6 Plus |
| LMArena WebDev: React | Not measured | 1454 | Only Qwen3.6 Plus measured |
| LMArena WebDev: HTML | Not measured | 1463 | Only Qwen3.6 Plus measured |
| LMArena WebDev: from an image | Not measured | 1472 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.6 | 27.0 | Qwen3.6 Plus |
| Epoch Capabilities Index | 139.8 | 147.3 | Qwen3.6 Plus |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | 3.7 | Not measured | Only gpt-oss-120b measured |
| Finance Agent (Vals AI) | Not measured | 40.9% | Only Qwen3.6 Plus measured |
| Tax Agent Bench (Vals AI) | Not measured | 7.7% | Only Qwen3.6 Plus measured |
| Legal Research Bench (Vals AI) | Not measured | 14.9% | Only Qwen3.6 Plus measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 32.9% | Only Qwen3.6 Plus measured |
| τ²-Bench Telecom | 65.8% | 97.7% | Qwen3.6 Plus |
| 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 | $5,115 | Qwen3.6 Plus |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | 87.4% | Qwen3.6 Plus |
| MMMU Pro (Vals AI) | Not measured | 84.2% | Only Qwen3.6 Plus measured |
| GPQA Diamond (Artificial Analysis run) | 78.2% | 88.2% | Qwen3.6 Plus |
| Humanity's Last Exam (Artificial Analysis run) | 19.6% | 27.8% | Qwen3.6 Plus |
| GPQA Diamond (Epoch AI run) | 75.8% | 88.4% | Qwen3.6 Plus |
| SimpleBench | 22.1% | Not measured | Only gpt-oss-120b measured |
| Chess puzzles | Not measured | 14.0% | Only Qwen3.6 Plus measured |
| Mystery game puzzles | 2.0% | 12.0% | Qwen3.6 Plus |
| LMArena Text: hard prompts | 1364 | 1448 | Qwen3.6 Plus |
| LMArena Text: expert | 1356 | 1454 | Qwen3.6 Plus |
| LMArena Text: hard prompts in English | 1368 | 1455 | Qwen3.6 Plus |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AIME | 92.6% | 94.6% | Qwen3.6 Plus |
| 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% | 93.3% | Qwen3.6 Plus |
| FrontierMath, tiers 1 to 3 | Not measured | 38.2% | Only Qwen3.6 Plus measured |
| LMArena Text: math | 1389 | 1449 | Qwen3.6 Plus |
| LMArena Text: mathematical work | 1386 | 1448 | Qwen3.6 Plus |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index09
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 79.2% | 87.7% | Qwen3.6 Plus |
| LegalBench (Vals AI) | 75.9% | 84.2% | Qwen3.6 Plus |
| CaseLaw (Vals AI) | 48.8% | 51.5% | Qwen3.6 Plus |
| CorpFin (Vals AI) | 58.2% | 61.9% | Qwen3.6 Plus |
| TaxEval (Vals AI) | 71.6% | 74.7% | Qwen3.6 Plus |
| MortgageTax (Vals AI) | Not measured | 68.0% | Only Qwen3.6 Plus measured |
| MedQA (Vals AI) | 91.4% | Not measured | Only gpt-oss-120b measured |
| MedCode (Vals AI) | Not measured | 36.9% | Only Qwen3.6 Plus measured |
| MMLU Pro (Artificial Analysis run) | 80.8% | Not measured | Only gpt-oss-120b measured |
| SimpleQA Verified | Not measured | 44.1% | Only Qwen3.6 Plus measured |
| LMArena Text: science | 1382 | 1439 | Qwen3.6 Plus |
| LMArena Text: medicine and healthcare | 1388 | 1442 | Qwen3.6 Plus |
| LMArena Text: legal and government | 1355 | 1437 | Qwen3.6 Plus |
| LMArena Text: business and finance | 1359 | 1430 | Qwen3.6 Plus |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 968 | 1243 | Qwen3.6 Plus |
| Design Arena: UI components | 927 | 1233 | Qwen3.6 Plus |
| Design Arena: game dev | 992 | 1211 | Qwen3.6 Plus |
| Design Arena: data viz | 987 | 1228 | Qwen3.6 Plus |
| Design Arena: 3D | 901 | 1202 | Qwen3.6 Plus |
| Design Arena: all code categories | 963 | 1236 | Qwen3.6 Plus |
| Design Arena: SVG | Not measured | 1160 | Only Qwen3.6 Plus measured |
| Design Arena: ASCII art | Not measured | 1115 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 44.9% | Only Qwen3.6 Plus measured |
| MedScribe (Vals AI) | Not measured | 77.0% | Only Qwen3.6 Plus measured |
| Vals Multimodal Index | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| IFBench | 69.0% | 75.2% | Qwen3.6 Plus |
| Long context reasoning (AA-LCR) | 52.0% | 78.3% | Qwen3.6 Plus |
| DTBench | 76.3% | 81.9% | Qwen3.6 Plus |
| LMCA | 22.1% | 33.1% | Qwen3.6 Plus |
| Fiction.LiveBench | 44.4% | Not measured | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | 77.1% | Not measured | Only gpt-oss-120b measured |
| CL-bench | Not measured | 20.3% | Only Qwen3.6 Plus measured |
| Surface Evolver Bench | 25.0% | Not measured | Only gpt-oss-120b measured |
| LMArena Text | 1366 | 1436 | Qwen3.6 Plus |
| LMArena Text: instruction following | 1318 | 1424 | Qwen3.6 Plus |
| LMArena Text: creative writing | 1274 | 1404 | Qwen3.6 Plus |
| LMArena Text: English | 1375 | 1445 | Qwen3.6 Plus |
| LMArena Text: non-English | 1351 | 1424 | Qwen3.6 Plus |
| LMArena Text: Chinese | 1385 | 1477 | Qwen3.6 Plus |
| LMArena Text: German | 1353 | 1451 | Qwen3.6 Plus |
| LMArena Text: Japanese | 1331 | 1390 | Qwen3.6 Plus |
| LMArena Text: Korean | 1282 | 1379 | Qwen3.6 Plus |
| LMArena Text: French | 1370 | 1455 | Qwen3.6 Plus |
| LMArena Text: Spanish | 1389 | 1432 | Qwen3.6 Plus |
| LMArena Text: Russian | 1343 | 1434 | Qwen3.6 Plus |
| LMArena Text: Polish | 1353 | 1433 | Qwen3.6 Plus |
| LMArena Text: multi-turn | 1340 | 1438 | Qwen3.6 Plus |
| LMArena Text: longer queries | 1319 | 1439 | Qwen3.6 Plus |
| LMArena Text: writing and language | 1306 | 1418 | Qwen3.6 Plus |
| LMArena Text: entertainment and media | 1292 | 1402 | Qwen3.6 Plus |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-120b | Qwen3.6 Plus | 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
gpt-oss-120b costs less
Repository review
50K input + 3K output tokens
gpt-oss-120b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-120b 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 | Qwen3.6 Plus |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | Open weights | No public weights listed |
| Released | August 5, 2025 | April 2, 2026 |
| Context window | 131K | 1M |
| Input $/Mtok | $0.15 | $0.325 |
| Output $/Mtok | $0.60 | $1.95 |
| Coding index | 34.5 | 37.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.51 | $1.19 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-120b better than Qwen3.6 Plus for coding?
Pick Qwen3.6 Plus for coding: it scores 37.4 on the Vibe Coding Index against 34.5 for gpt-oss-120b, though on 1 benchmark against 2. Pick gpt-oss-120b when output tokens cost 3.3x less, or when a solved task costs $0.51 against $1.19.
Which is cheaper, gpt-oss-120b or Qwen3.6 Plus?
gpt-oss-120b costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.6 Plus costs $0.325 and $1.95. Per solved SWE-bench Verified task, gpt-oss-120b costs $0.51 and Qwen3.6 Plus $1.19.
Which has the bigger context window, gpt-oss-120b or Qwen3.6 Plus?
Qwen3.6 Plus, with 1M tokens against 131K.
How many benchmarks is the gpt-oss-120b vs Qwen3.6 Plus comparison based on?
59 benchmarks have a result for both models as of October 21, 2026. gpt-oss-120b's coding index rests on 2 independent benchmarks and Qwen3.6 Plus's on 1. Where only one model has a result, the page says so instead of naming a winner.