GPT-6 Sol vs Qwen2.5 Coder 32B Instruct
Updated October 21, 2026. 25 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 25 shared
Decision reading
Pick GPT-6 Sol for coding: it scores 82.8 on the Vibe Coding Index against 30.5 for Qwen2.5 Coder 32B Instruct.
Pick Qwen2.5 Coder 32B Instruct when output tokens cost 10.0x less.
Model AGPT-6 SolOpenAI82.8/1002 independent benchmarksNo cost per solved taskModel BQwen2.5 Coder 32B InstructQwen30.5/1002 independent benchmarksNo cost per solved task
- Shared results
- 25
- GPT-6 Sol only
- 75
- Qwen2.5 Coder 32B Instruct only
- 10
- Like-for-like categories
- 6 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
GPT-6 Sol
GPT-6 Sol scores 82.8 against 30.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-6 Sol
GPT-6 Sol leads, 47.6 against 6.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-6 Sol has a Design Arena: websites result, 1292.
Directional only
Long documents
Listed context window
GPT-6 Sol
GPT-6 Sol takes 1.05M tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 Coder 32B Instruct
GPT-6 Sol $0.0070, Qwen2.5 Coder 32B Instruct $0.0012 per turn.
List prices
At a glance
- Coding index
- GPT-6 Sol 82.8 from 2 benchmarks, Qwen2.5 Coder 32B Instruct 30.5 from 2 benchmarks.
- Widest category
- Intelligence, 48.1 points apart on average over 2 shared benchmarks.
- Widest single gap
- Epoch Capabilities Index: GPT-6 Sol 163.7 against Qwen2.5 Coder 32B Instruct 119.5, 55.3 points apart on a 0 to 100 scale.
- Output price
- GPT-6 Sol $10.00 against Qwen2.5 Coder 32B Instruct $1.00 per million output tokens, 10.0x apart.
- Context window
- GPT-6 Sol takes 1.05M tokens, Qwen2.5 Coder 32B Instruct 33K.
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-6 Sol | Bars | Qwen2.5 Coder 32B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 11 | 0 | ||
| All shared boards | 25 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index20
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 16.4% | Only Qwen2.5 Coder 32B Instruct measured |
| SWE-bench Verified | Not measured | 47.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LiveBench coding | 93.1% | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev | 1683 | Not measured | Only GPT-6 Sol measured |
| Terminal-Bench 4 (Vals AI) | 44.4% | Not measured | Only GPT-6 Sol measured |
| Vibe Code Bench (Vals AI) | 87.8% | Not measured | Only GPT-6 Sol measured |
| Code migration (Vals AI) | 57.2% | Not measured | Only GPT-6 Sol measured |
| ProgramBench (Vals AI) | 2.0% | Not measured | Only GPT-6 Sol measured |
| IOI (Vals AI) | 82.6% | Not measured | Only GPT-6 Sol measured |
| Terminal-Bench 2.1 (Vals AI) | 83.2% | Not measured | Only GPT-6 Sol measured |
| CyberBench (Vals AI) | 78.0% | Not measured | Only GPT-6 Sol measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 29.5% | Only Qwen2.5 Coder 32B Instruct measured |
| SciCode | 57.6% | Not measured | Only GPT-6 Sol measured |
| FrontierCode | 49.3% | Not measured | Only GPT-6 Sol measured |
| ALE-Bench | 2462.0 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: coding | 1448 | 1276 | GPT-6 Sol |
| LMArena Text: software and IT | 1433 | 1261 | GPT-6 Sol |
| LMArena WebDev: React | 1685 | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev: HTML | 1685 | Not measured | Only GPT-6 Sol measured |
| LMArena WebDev: from an image | 1660 | Not measured | Only GPT-6 Sol 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-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 47.6 | 6.7 | GPT-6 Sol |
| Epoch Capabilities Index | 163.7 | 119.5 | GPT-6 Sol |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1232 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building full-stack apps | 1238 | Not measured | Only GPT-6 Sol measured |
| Design Arena: agents building mobile apps | 1216 | Not measured | Only GPT-6 Sol measured |
| LiveBench research | 69.3% | Not measured | Only GPT-6 Sol measured |
| LiveBench browser | 92.0% | Not measured | Only GPT-6 Sol measured |
| LiveBench long agentic | 66.9% | Not measured | Only GPT-6 Sol measured |
| SREBench (Vals AI) | 30.5% | Not measured | Only GPT-6 Sol measured |
| Finance Agent (Vals AI) | 49.0% | Not measured | Only GPT-6 Sol measured |
| Tax Agent Bench (Vals AI) | 15.0% | Not measured | Only GPT-6 Sol measured |
| Legal Research Bench (Vals AI) | 28.9% | Not measured | Only GPT-6 Sol measured |
| Excel Modeling Benchmark (Vals AI) | 71.5% | Not measured | Only GPT-6 Sol measured |
| BioMysteryBench (Vals AI) | 74.8% | Not measured | Only GPT-6 Sol measured |
| Terminal-Bench-Science (Vals AI) | 30.0% | Not measured | Only GPT-6 Sol measured |
| Vals Science Index | 45.0% | Not measured | Only GPT-6 Sol measured |
| APEX-Agents | 54.3% | Not measured | Only GPT-6 Sol measured |
| SpireClimb | 7.5% | Not measured | Only GPT-6 Sol measured |
| Vending-Bench 2 | $14,428 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| LiveBench reasoning | 88.7% | Not measured | Only GPT-6 Sol measured |
| MysteryMechanism (Vals AI) | 30.2% | Not measured | Only GPT-6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 41.7% | Only Qwen2.5 Coder 32B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | 3.5% | GPT-6 Sol |
| GPQA Diamond (Epoch AI run) | 94.3% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI | 95.5% | Not measured | Only GPT-6 Sol measured |
| ARC-AGI-2 | 89.6% | Not measured | Only GPT-6 Sol measured |
| Chess puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| Mystery game puzzles | 56.0% | Not measured | Only GPT-6 Sol measured |
| EBR-bench | 53.3% | Not measured | Only GPT-6 Sol measured |
| LMArena Text: hard prompts | 1422 | 1251 | GPT-6 Sol |
| LMArena Text: expert | 1437 | 1221 | GPT-6 Sol |
| LMArena Text: hard prompts in English | 1420 | 1269 | GPT-6 Sol |
| LMArena Vision: diagrams | 1270 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: homework | 1286 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tiers 1 to 3 | 89.8% | Not measured | Only GPT-6 Sol measured |
| FrontierMath, tier 4 | 90.0% | Not measured | Only GPT-6 Sol measured |
| ProofBench | 83.0% | Not measured | Only GPT-6 Sol measured |
| GSM8K | Not measured | 93.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1407 | 1251 | GPT-6 Sol |
| LMArena Text: mathematical work | 1424 | 1243 | GPT-6 Sol |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 47.1% | Not measured | Only GPT-6 Sol measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 63.5% | Only Qwen2.5 Coder 32B Instruct measured |
| SimpleQA Verified | 60.7% | Not measured | Only GPT-6 Sol measured |
| MMLU | Not measured | 79.1% | Only Qwen2.5 Coder 32B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 70.5% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: science | 1389 | 1221 | GPT-6 Sol |
| LMArena Text: medicine and healthcare | 1366 | 1187 | GPT-6 Sol |
| LMArena Text: legal and government | 1396 | 1257 | GPT-6 Sol |
| LMArena Text: business and finance | 1380 | 1224 | GPT-6 Sol |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1292 | Not measured | Only GPT-6 Sol measured |
| Design Arena: UI components | 1292 | Not measured | Only GPT-6 Sol measured |
| Design Arena: game dev | 1313 | Not measured | Only GPT-6 Sol measured |
| Design Arena: data viz | 1269 | Not measured | Only GPT-6 Sol measured |
| Design Arena: 3D | 1322 | Not measured | Only GPT-6 Sol measured |
| Design Arena: all code categories | 1301 | Not measured | Only GPT-6 Sol measured |
| Design Arena: SVG | 1318 | Not measured | Only GPT-6 Sol measured |
| Design Arena: ASCII art | 1226 | Not measured | Only GPT-6 Sol measured |
| LiveBench design | 82.2% | Not measured | Only GPT-6 Sol measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| LiveBench data analysis | 81.2% | Not measured | Only GPT-6 Sol measured |
| Public Benefits Bench (Vals AI) | 56.6% | Not measured | Only GPT-6 Sol measured |
| SAGE (Vals AI) | 44.8% | Not measured | Only GPT-6 Sol measured |
| MedScribe (Vals AI) | 82.0% | Not measured | Only GPT-6 Sol measured |
| Long context reasoning (AA-LCR) | 83.7% | Not measured | Only GPT-6 Sol measured |
| DTBench | 97.3% | Not measured | Only GPT-6 Sol measured |
| LMCA | 59.1% | Not measured | Only GPT-6 Sol measured |
| Furniture assembly | 58.3% | Not measured | Only GPT-6 Sol measured |
| HellaSwag | Not measured | 83.0% | Only Qwen2.5 Coder 32B Instruct measured |
| WinoGrande | Not measured | 80.8% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text | 1398 | 1230 | GPT-6 Sol |
| LMArena Text: instruction following | 1413 | 1223 | GPT-6 Sol |
| LMArena Text: creative writing | 1378 | 1174 | GPT-6 Sol |
| LMArena Vision | 1240 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: English | 1396 | 1248 | GPT-6 Sol |
| LMArena Text: non-English | 1388 | 1205 | GPT-6 Sol |
| LMArena Text: Chinese | 1412 | 1222 | GPT-6 Sol |
| LMArena Text: German | 1379 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Japanese | 1377 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Korean | 1336 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: French | 1399 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Spanish | 1387 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: Russian | 1402 | 1228 | GPT-6 Sol |
| LMArena Text: Polish | 1372 | Not measured | Only GPT-6 Sol measured |
| LMArena Text: multi-turn | 1414 | 1222 | GPT-6 Sol |
| LMArena Text: longer queries | 1416 | 1251 | GPT-6 Sol |
| LMArena Text: writing and language | 1389 | 1191 | GPT-6 Sol |
| LMArena Text: entertainment and media | 1373 | 1150 | GPT-6 Sol |
| LMArena Vision: English | 1229 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: reading text | 1258 | Not measured | Only GPT-6 Sol measured |
| LMArena Vision: creative writing | 1219 | Not measured | Only GPT-6 Sol measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6 Sol | Qwen2.5 Coder 32B Instruct | 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-6 Sol$0.0070Fits in one request
Qwen2.5 Coder 32B Instruct$0.0012Fits in one request
Qwen2.5 Coder 32B Instruct costs less
Repository review
50K input + 3K output tokens
GPT-6 Sol$0.130Fits in one request
Qwen2.5 Coder 32B Instruct$0.036Exceeds the context window
Qwen2.5 Coder 32B Instruct costs less
Agent loop
200K input + 10K output tokens
GPT-6 Sol$0.500Fits in one request
Qwen2.5 Coder 32B Instruct$0.142Exceeds the context window
Qwen2.5 Coder 32B Instruct 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-6 Sol | Qwen2.5 Coder 32B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | September 22, 2026 | November 11, 2024 |
| Context window | 1.05M | 33K |
| Input $/Mtok | $2.00 | $0.66 |
| Output $/Mtok | $10.00 | $1.00 |
| Coding index | 82.8 | 30.5 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6 Sol better than Qwen2.5 Coder 32B Instruct for coding?
Pick GPT-6 Sol for coding: it scores 82.8 on the Vibe Coding Index against 30.5 for Qwen2.5 Coder 32B Instruct. Pick Qwen2.5 Coder 32B Instruct when output tokens cost 10.0x less.
Which is cheaper, GPT-6 Sol or Qwen2.5 Coder 32B Instruct?
GPT-6 Sol costs $2.00 per million input tokens and $10.00 per million output tokens; Qwen2.5 Coder 32B Instruct costs $0.66 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-6 Sol or Qwen2.5 Coder 32B Instruct?
GPT-6 Sol, with 1.05M tokens against 33K.
How many benchmarks is the GPT-6 Sol vs Qwen2.5 Coder 32B Instruct comparison based on?
25 benchmarks have a result for both models as of October 21, 2026. GPT-6 Sol's coding index rests on 2 independent benchmarks and Qwen2.5 Coder 32B Instruct's on 2. Where only one model has a result, the page says so instead of naming a winner.