GPT-5.2 vs Qwen3.6 Plus
GPT-5.2 leads Qwen3.6 Plus on coding, 55.9 to 44.1 on the Vibe Coding Index, and Qwen3.6 Plus costs 7.2x less per output token ($1.95 vs $14.00 per million). Updated October 21, 2026; 72 benchmarks have a result for both.
GPT-5.2 or Qwen3.6 Plus: which to pick
Pick GPT-5.2 for coding: it scores 55.9 on the Vibe Coding Index against 44.1 for Qwen3.6 Plus.
Pick Qwen3.6 Plus for output tokens 7.2x cheaper ($1.95 vs $14.00 per million) and a lower cost per solved task ($1.19 against $1.91).
- Shared results
- 72
- GPT-5.2 only
- 42
- Qwen3.6 Plus only
- 11
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
GPT-5.2
GPT-5.2 scores 55.9 against 44.1.
3 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.2
GPT-5.2 leads, 30.4 against 27.0.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.2
GPT-5.2 leads, 91.7% against 87.4%.
Same board, both measured
Math
AIME
GPT-5.2
GPT-5.2 leads, 96.9% against 94.6%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.7% against 86.2%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.6 Plus
Qwen3.6 Plus leads, 1243 against 1195.
Same board, both measured
Long documents
Listed context window
Qwen3.6 Plus
Qwen3.6 Plus takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 Plus
GPT-5.2 $0.0088, Qwen3.6 Plus $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Qwen3.6 Plus
GPT-5.2 $1.91, Qwen3.6 Plus $1.19.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.2 55.9 from 3 benchmarks, Qwen3.6 Plus 44.1 from 3 benchmarks.
- Widest category
- Agentic work, 11.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- Chess puzzles: GPT-5.2 48.0% against Qwen3.6 Plus 14.0%, 34.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2 $14.00 against Qwen3.6 Plus $1.95 per million output tokens, 7.2x apart.
- Context window
- GPT-5.2 takes 400K 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-5.2 | Bars | Qwen3.6 Plus | Ties |
|---|---|---|---|---|
| Coding | 4 | 5 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 7 | 3 | ||
| Math | 3 | 2 | ||
| Knowledge | 4 | 8 | ||
| Web design | 1 | 7 | ||
| General | 7 | 17 | ||
| All shared boards | 28 | 44 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index45
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GPT-5.2 measured |
| SWE-bench Multilingual | 66.7% | Not measured | Only GPT-5.2 measured |
| LMArena WebDev | 1417 | 1461 | Qwen3.6 Plus |
| AA Coding Index | Not measured | 54.5 | Only Qwen3.6 Plus measured |
| LiveCodeBench (Vals AI) | 85.4% | 86.0% | Qwen3.6 Plus |
| SWE-bench Verified (Vals AI) | 75.8% | 73.4% | GPT-5.2 |
| Vibe Code Bench (Vals AI) | 53.5% | 25.6% | GPT-5.2 |
| 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) | 89.4% | Not measured | Only GPT-5.2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 47.0% | 43.9% | GPT-5.2 |
| Terminal-Bench | 64.9% | Not measured | Only GPT-5.2 measured |
| GSO-Bench | 27.5% | Not measured | Only GPT-5.2 measured |
| WeirdML | 72.2% | Not measured | Only GPT-5.2 measured |
| ALE-Bench | 1293.5 | 670.1 | GPT-5.2 |
| LMArena Text: coding | 1442 | 1467 | Qwen3.6 Plus |
| LMArena Text: software and IT | 1434 | 1462 | Qwen3.6 Plus |
| LMArena WebDev: React | Not measured | 1454 | Only Qwen3.6 Plus measured |
| LMArena WebDev: HTML | 1427 | 1463 | Qwen3.6 Plus |
| LMArena WebDev: from an image | Not measured | 1472 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 30.4 | 27.0 | GPT-5.2 |
| Epoch Capabilities Index | 153.7 | 147.3 | GPT-5.2 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1086 | Not measured | Only GPT-5.2 measured |
| Design Arena: agents building full-stack apps | 1043 | Not measured | Only GPT-5.2 measured |
| Design Arena: agents building mobile apps | 1093 | Not measured | Only GPT-5.2 measured |
| Design Arena: agents building Android apps | 1058 | Not measured | Only GPT-5.2 measured |
| Design Arena: agents building Godot games | 1142 | Not measured | Only GPT-5.2 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 | 84.8% | 97.7% | Qwen3.6 Plus |
| METR time horizons | 75.3% | Not measured | Only GPT-5.2 measured |
| Remote Labor Index | 2.5% | Not measured | Only GPT-5.2 measured |
| GDPval | 49.7% | Not measured | Only GPT-5.2 measured |
| DeepResearch Bench | 41.1% | Not measured | Only GPT-5.2 measured |
| Vending-Bench 2 | $3,591 | $5,115 | Qwen3.6 Plus |
| Berkeley Function Calling Leaderboard (BFCL) | 55.9% | Not measured | Only GPT-5.2 measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index73
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | 87.4% | GPT-5.2 |
| MMMU Pro (Vals AI) | 86.7% | 84.2% | GPT-5.2 |
| GPQA Diamond (Artificial Analysis run) | 90.3% | 88.2% | GPT-5.2 |
| Humanity's Last Exam (Artificial Analysis run) | 37.7% | 27.8% | GPT-5.2 |
| GPQA Diamond (Epoch AI run) | 91.4% | 88.4% | GPT-5.2 |
| ARC-AGI | 86.2% | Not measured | Only GPT-5.2 measured |
| ARC-AGI-2 | 52.9% | Not measured | Only GPT-5.2 measured |
| SimpleBench | 45.8% | Not measured | Only GPT-5.2 measured |
| Chess puzzles | 48.0% | 14.0% | GPT-5.2 |
| Mystery game puzzles | 23.0% | 12.0% | GPT-5.2 |
| EBR-bench | 23.0% | Not measured | Only GPT-5.2 measured |
| VPCT | 84.0% | Not measured | Only GPT-5.2 measured |
| LMArena Text: hard prompts | 1428 | 1448 | Qwen3.6 Plus |
| LMArena Text: expert | 1445 | 1454 | Qwen3.6 Plus |
| LMArena Text: hard prompts in English | 1431 | 1455 | Qwen3.6 Plus |
| LMArena Vision: diagrams | 1265 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: homework | 1276 | Not measured | Only GPT-5.2 measured |
| Kagi LLM Benchmark | 73.3% | Not measured | Only GPT-5.2 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AIME | 96.9% | 94.6% | GPT-5.2 |
| MGSM (Vals AI) | 94.0% | Not measured | Only GPT-5.2 measured |
| AA Math Index | 99.0 | Not measured | Only GPT-5.2 measured |
| AIME 2025 (Artificial Analysis run) | 99.0% | Not measured | Only GPT-5.2 measured |
| OTIS Mock AIME | 96.1% | 93.3% | GPT-5.2 |
| FrontierMath, tiers 1 to 3 | 67.4% | 38.2% | GPT-5.2 |
| FrontierMath, tier 4 | 31.7% | Not measured | Only GPT-5.2 measured |
| ProofBench | 15.0% | Not measured | Only GPT-5.2 measured |
| LMArena Text: math | 1440 | 1449 | Qwen3.6 Plus |
| LMArena Text: mathematical work | 1442 | 1448 | Qwen3.6 Plus |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index48
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 86.2% | 87.7% | Qwen3.6 Plus |
| LegalBench (Vals AI) | 82.8% | 84.2% | Qwen3.6 Plus |
| CaseLaw (Vals AI) | 66.0% | 51.5% | GPT-5.2 |
| CorpFin (Vals AI) | 65.9% | 61.9% | GPT-5.2 |
| TaxEval (Vals AI) | 75.8% | 74.7% | GPT-5.2 |
| MortgageTax (Vals AI) | 67.1% | 68.0% | Qwen3.6 Plus |
| MedQA (Vals AI) | 94.1% | Not measured | Only GPT-5.2 measured |
| MedCode (Vals AI) | 49.8% | 36.9% | GPT-5.2 |
| MMLU Pro (Artificial Analysis run) | 87.4% | Not measured | Only GPT-5.2 measured |
| SimpleQA Verified | 37.1% | 44.1% | Qwen3.6 Plus |
| LMArena Text: science | 1425 | 1439 | Qwen3.6 Plus |
| LMArena Text: medicine and healthcare | 1425 | 1442 | Qwen3.6 Plus |
| LMArena Text: legal and government | 1427 | 1437 | Qwen3.6 Plus |
| LMArena Text: business and finance | 1414 | 1430 | Qwen3.6 Plus |
| FACTS Benchmark Suite | 48.5% | Not measured | Only GPT-5.2 measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 1195 | 1243 | Qwen3.6 Plus |
| Design Arena: UI components | 1190 | 1233 | Qwen3.6 Plus |
| Design Arena: game dev | 1195 | 1211 | Qwen3.6 Plus |
| Design Arena: data viz | 1202 | 1228 | Qwen3.6 Plus |
| Design Arena: 3D | 1079 | 1202 | Qwen3.6 Plus |
| Design Arena: all code categories | 1170 | 1236 | Qwen3.6 Plus |
| Design Arena: SVG | 1139 | 1161 | Qwen3.6 Plus |
| Design Arena: ASCII art | 1152 | 1113 | GPT-5.2 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index717
| Benchmark | GPT-5.2 | Qwen3.6 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 49.3% | 44.9% | GPT-5.2 |
| MedScribe (Vals AI) | 84.4% | 77.0% | GPT-5.2 |
| Vals Multimodal Index | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| IFBench | 75.4% | 75.2% | GPT-5.2 |
| Long context reasoning (AA-LCR) | 82.7% | 78.3% | GPT-5.2 |
| DTBench | 90.9% | 81.9% | GPT-5.2 |
| LMCA | 43.9% | 33.1% | GPT-5.2 |
| CL-bench | 18.2% | 20.3% | Qwen3.6 Plus |
| Furniture assembly | 38.3% | Not measured | Only GPT-5.2 measured |
| LMArena Text | 1416 | 1436 | Qwen3.6 Plus |
| LMArena Text: instruction following | 1409 | 1424 | Qwen3.6 Plus |
| LMArena Text: creative writing | 1376 | 1404 | Qwen3.6 Plus |
| LMArena Vision | 1246 | Not measured | Only GPT-5.2 measured |
| LMArena Text: English | 1422 | 1445 | Qwen3.6 Plus |
| LMArena Text: non-English | 1405 | 1424 | Qwen3.6 Plus |
| LMArena Text: Chinese | 1447 | 1477 | Qwen3.6 Plus |
| LMArena Text: German | 1444 | 1451 | Qwen3.6 Plus |
| LMArena Text: Japanese | 1420 | 1390 | GPT-5.2 |
| LMArena Text: Korean | 1374 | 1379 | Qwen3.6 Plus |
| LMArena Text: French | 1454 | 1455 | Qwen3.6 Plus |
| LMArena Text: Spanish | 1413 | 1432 | Qwen3.6 Plus |
| LMArena Text: Russian | 1415 | 1434 | Qwen3.6 Plus |
| LMArena Text: Polish | 1426 | 1433 | Qwen3.6 Plus |
| LMArena Text: multi-turn | 1419 | 1438 | Qwen3.6 Plus |
| LMArena Text: longer queries | 1413 | 1439 | Qwen3.6 Plus |
| LMArena Text: writing and language | 1392 | 1418 | Qwen3.6 Plus |
| LMArena Text: entertainment and media | 1378 | 1402 | Qwen3.6 Plus |
| LMArena Vision: English | 1243 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: Chinese | 1305 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: reading text | 1257 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: humor | 1227 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: captioning | 1267 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: recognizing things | 1232 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: creative writing | 1225 | Not measured | Only GPT-5.2 measured |
| LMArena Document | 1405 | Not measured | Only GPT-5.2 measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2 | 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
Qwen3.6 Plus costs less
Repository review
50K input + 3K output tokens
Qwen3.6 Plus costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 Plus 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-5.2 | Qwen3.6 Plus |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | December 10, 2025 | April 2, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $1.75 | $0.325 |
| Output $/Mtok | $14.00 | $1.95 |
| Coding index | 55.9 | 44.1 |
| Independent measurements behind it | 3 | 3 |
| Cost per solved task | $1.91 | $1.19 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2 better than Qwen3.6 Plus for coding?
Pick GPT-5.2 for coding: it scores 55.9 on the Vibe Coding Index against 44.1 for Qwen3.6 Plus. Pick Qwen3.6 Plus for output tokens 7.2x cheaper ($1.95 vs $14.00 per million) and a lower cost per solved task ($1.19 against $1.91).
Which is cheaper, GPT-5.2 or Qwen3.6 Plus?
GPT-5.2 costs $1.75 per million input tokens and $14.00 per million output tokens; Qwen3.6 Plus costs $0.325 and $1.95. Per solved SWE-bench Verified task, GPT-5.2 costs $1.91 and Qwen3.6 Plus $1.19.
Which has the bigger context window, GPT-5.2 or Qwen3.6 Plus?
Qwen3.6 Plus, with 1M tokens against 400K.
How many benchmarks is the GPT-5.2 vs Qwen3.6 Plus comparison based on?
72 benchmarks have a result for both models as of October 21, 2026. GPT-5.2's coding index rests on 3 independent benchmarks and Qwen3.6 Plus's on 3. Where only one model has a result, the page says so instead of naming a winner.