GPT-5.4 vs Qwen3 32B
Updated October 21, 2026. 35 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 32B for coding: it scores 40.0 on the Vibe Coding Index against 37.7 for GPT-5.4.
Pick GPT-5.4 when the context window is larger, 1.05M against 131K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
- Shared results
- 35
- GPT-5.4 only
- 74
- Qwen3 32B only
- 7
- Like-for-like categories
- 7 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 32B
Qwen3 32B scores 40.0 against 37.7.
One benchmark behind each score
Intelligence
AA Intelligence Index
GPT-5.4
GPT-5.4 leads, 39.0 against 7.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.4 has a GPQA Diamond result, 91.7%.
Directional only
Math
AIME
No call
Only GPT-5.4 has a AIME result, 96.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 has a MMLU Pro result, 87.5%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.4 has a Design Arena: websites result, 1199.
Directional only
Long documents
Listed context window
GPT-5.4
GPT-5.4 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 32B
GPT-5.4 $0.010, Qwen3 32B $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 has the number, $1.02.
Directional only
At a glance
- Coding index
- GPT-5.4 37.7 from 1 benchmark, Qwen3 32B 40.0 from 1 benchmark.
- Widest category
- Agentic work, 57.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): GPT-5.4 82.0% against Qwen3 32B 0.0%, 82.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 $15.00 against Qwen3 32B $0.28 per million output tokens, 53.6x apart.
- Context window
- GPT-5.4 takes 1.05M tokens, Qwen3 32B 131K.
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-5.4 | Bars | Qwen3 32B | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 16 | 0 | ||
| All shared boards | 35 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index30
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 40.0% | Only Qwen3 32B measured |
| LMArena WebDev | 1464 | Not measured | Only GPT-5.4 measured |
| AA Coding Index | 71.1 | Not measured | Only GPT-5.4 measured |
| LiveCodeBench (Vals AI) | 84.1% | Not measured | Only GPT-5.4 measured |
| SWE-bench Verified (Vals AI) | 78.2% | Not measured | Only GPT-5.4 measured |
| Vibe Code Bench (Vals AI) | 67.4% | Not measured | Only GPT-5.4 measured |
| Code migration (Vals AI) | 35.0% | Not measured | Only GPT-5.4 measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.4 measured |
| SkillsBench (Vals AI) | 51.7% | Not measured | Only GPT-5.4 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 54.6% | Only Qwen3 32B measured |
| SciCode | Not measured | 36.0% | Only Qwen3 32B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 57.6% | 3.0% | GPT-5.4 |
| Terminal-Bench | 81.8% | Not measured | Only GPT-5.4 measured |
| GSO-Bench | 31.4% | Not measured | Only GPT-5.4 measured |
| WeirdML | 77.7% | Not measured | Only GPT-5.4 measured |
| MirrorCode | 15.6% | Not measured | Only GPT-5.4 measured |
| ALE-Bench | 1607.0 | Not measured | Only GPT-5.4 measured |
| LMArena Text: coding | 1496 | 1357 | GPT-5.4 |
| LMArena Text: software and IT | 1491 | 1366 | GPT-5.4 |
| LMArena WebDev: React | 1454 | Not measured | Only GPT-5.4 measured |
| LMArena WebDev: HTML | 1478 | Not measured | Only GPT-5.4 measured |
| LMArena WebDev: from an image | 1436 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.0 | 7.3 | GPT-5.4 |
| Epoch Capabilities Index | 157.3 | 138.4 | GPT-5.4 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1059 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building full-stack apps | 1017 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building mobile apps | 1087 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building Android apps | 1037 | Not measured | Only GPT-5.4 measured |
| Design Arena: agents building Godot games | 1135 | Not measured | Only GPT-5.4 measured |
| τ²-Bench Telecom | 87.1% | 29.8% | GPT-5.4 |
| APEX-Agents | 52.4% | Not measured | Only GPT-5.4 measured |
| METR time horizons | 74.3% | Not measured | Only GPT-5.4 measured |
| DeepResearch Bench | 35.1% | Not measured | Only GPT-5.4 measured |
| PostTrainBench | 19.0% | Not measured | Only GPT-5.4 measured |
| Vending-Bench 2 | $6,144 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | Not measured | Only GPT-5.4 measured |
| MMMU Pro (Vals AI) | 87.5% | Not measured | Only GPT-5.4 measured |
| GPQA Diamond (Artificial Analysis run) | 92.0% | 66.8% | GPT-5.4 |
| Humanity's Last Exam (Artificial Analysis run) | 43.7% | 7.4% | GPT-5.4 |
| GPQA Diamond (Epoch AI run) | 93.3% | 65.7% | GPT-5.4 |
| ARC-AGI | 93.7% | Not measured | Only GPT-5.4 measured |
| ARC-AGI-2 | 74.0% | Not measured | Only GPT-5.4 measured |
| Chess puzzles | 48.0% | Not measured | Only GPT-5.4 measured |
| Mystery game puzzles | 37.0% | Not measured | Only GPT-5.4 measured |
| EBR-bench | 25.4% | Not measured | Only GPT-5.4 measured |
| LMArena Text: hard prompts | 1485 | 1334 | GPT-5.4 |
| LMArena Text: expert | 1507 | 1362 | GPT-5.4 |
| LMArena Text: hard prompts in English | 1479 | 1350 | GPT-5.4 |
| LMArena Vision: diagrams | 1327 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: homework | 1336 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| AIME | 96.7% | Not measured | Only GPT-5.4 measured |
| AA Math Index | Not measured | 73.0 | Only Qwen3 32B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.0% | Only Qwen3 32B measured |
| OTIS Mock AIME | 97.8% | 66.9% | GPT-5.4 |
| FrontierMath, tiers 1 to 3 | 78.6% | Not measured | Only GPT-5.4 measured |
| FrontierMath, tier 4 | 49.0% | Not measured | Only GPT-5.4 measured |
| ProofBench | 56.0% | Not measured | Only GPT-5.4 measured |
| LMArena Text: math | 1488 | 1399 | GPT-5.4 |
| LMArena Text: mathematical work | 1497 | 1420 | GPT-5.4 |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| MMLU Pro | 87.5% | Not measured | Only GPT-5.4 measured |
| LegalBench (Vals AI) | 86.0% | Not measured | Only GPT-5.4 measured |
| CaseLaw (Vals AI) | 63.8% | Not measured | Only GPT-5.4 measured |
| CorpFin (Vals AI) | 65.3% | Not measured | Only GPT-5.4 measured |
| TaxEval (Vals AI) | 74.0% | Not measured | Only GPT-5.4 measured |
| MortgageTax (Vals AI) | 68.3% | Not measured | Only GPT-5.4 measured |
| MedQA (Vals AI) | 96.1% | Not measured | Only GPT-5.4 measured |
| MedCode (Vals AI) | 41.3% | Not measured | Only GPT-5.4 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 79.8% | Only Qwen3 32B measured |
| SimpleQA Verified | 45.1% | Not measured | Only GPT-5.4 measured |
| LMArena Text: science | 1479 | 1372 | GPT-5.4 |
| LMArena Text: medicine and healthcare | 1458 | 1368 | GPT-5.4 |
| LMArena Text: legal and government | 1486 | 1324 | GPT-5.4 |
| LMArena Text: business and finance | 1474 | 1318 | GPT-5.4 |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| Design Arena: websites | 1199 | Not measured | Only GPT-5.4 measured |
| Design Arena: UI components | 1215 | Not measured | Only GPT-5.4 measured |
| Design Arena: game dev | 1195 | Not measured | Only GPT-5.4 measured |
| Design Arena: data viz | 1196 | Not measured | Only GPT-5.4 measured |
| Design Arena: 3D | 1065 | Not measured | Only GPT-5.4 measured |
| Design Arena: all code categories | 1180 | Not measured | Only GPT-5.4 measured |
| Design Arena: SVG | 1141 | Not measured | Only GPT-5.4 measured |
| Design Arena: ASCII art | 1188 | Not measured | Only GPT-5.4 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index160
| Benchmark | GPT-5.4 | Qwen3 32B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 43.3% | Not measured | Only GPT-5.4 measured |
| MedScribe (Vals AI) | 77.5% | Not measured | Only GPT-5.4 measured |
| IFBench | 73.9% | 36.3% | GPT-5.4 |
| Long context reasoning (AA-LCR) | 82.0% | 0.0% | GPT-5.4 |
| DTBench | 94.4% | 67.5% | GPT-5.4 |
| LMCA | 52.0% | 17.3% | GPT-5.4 |
| Fiction.LiveBench | Not measured | 74.2% | Only Qwen3 32B measured |
| CL-bench | 27.9% | Not measured | Only GPT-5.4 measured |
| Furniture assembly | 37.5% | Not measured | Only GPT-5.4 measured |
| CL-bench Life | 21.7% | Not measured | Only GPT-5.4 measured |
| LMArena Text | 1469 | 1340 | GPT-5.4 |
| LMArena Text: instruction following | 1469 | 1305 | GPT-5.4 |
| LMArena Text: creative writing | 1439 | 1297 | GPT-5.4 |
| LMArena Vision | 1303 | Not measured | Only GPT-5.4 measured |
| LMArena Text: English | 1467 | 1359 | GPT-5.4 |
| LMArena Text: non-English | 1465 | 1317 | GPT-5.4 |
| LMArena Text: Chinese | 1520 | 1357 | GPT-5.4 |
| LMArena Text: German | 1472 | 1341 | GPT-5.4 |
| LMArena Text: Japanese | 1485 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Korean | 1449 | Not measured | Only GPT-5.4 measured |
| LMArena Text: French | 1493 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Spanish | 1452 | Not measured | Only GPT-5.4 measured |
| LMArena Text: Russian | 1480 | 1311 | GPT-5.4 |
| LMArena Text: Polish | 1472 | Not measured | Only GPT-5.4 measured |
| LMArena Text: multi-turn | 1482 | 1331 | GPT-5.4 |
| LMArena Text: longer queries | 1473 | 1327 | GPT-5.4 |
| LMArena Text: writing and language | 1458 | 1298 | GPT-5.4 |
| LMArena Text: entertainment and media | 1438 | 1279 | GPT-5.4 |
| LMArena Vision: English | 1301 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: Chinese | 1354 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: reading text | 1312 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: humor | 1284 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: recognizing things | 1251 | Not measured | Only GPT-5.4 measured |
| LMArena Vision: creative writing | 1283 | Not measured | Only GPT-5.4 measured |
| LMArena Document | 1471 | Not measured | Only GPT-5.4 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-5.4 | Qwen3 32B | 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 32B costs less
Repository review
50K input + 3K output tokens
Qwen3 32B costs less
Agent loop
200K input + 10K output tokens
Qwen3 32B 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-5.4 | Qwen3 32B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 5, 2026 | April 28, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $2.50 | $0.08 |
| Output $/Mtok | $15.00 | $0.28 |
| Coding index | 37.7 | 40.0 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $1.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 better than Qwen3 32B for coding?
Pick Qwen3 32B for coding: it scores 40.0 on the Vibe Coding Index against 37.7 for GPT-5.4. Pick GPT-5.4 when the context window is larger, 1.05M against 131K tokens, or when what matters is Terminal-Bench Hard (Artificial Analysis run) or LMArena Text: coding, where it leads.
Which is cheaper, GPT-5.4 or Qwen3 32B?
GPT-5.4 costs $2.50 per million input tokens and $15.00 per million output tokens; Qwen3 32B costs $0.08 and $0.28. Cost per solved task is known for GPT-5.4 only.
Which has the bigger context window, GPT-5.4 or Qwen3 32B?
GPT-5.4, with 1.05M tokens against 131K.
How many benchmarks is the GPT-5.4 vs Qwen3 32B comparison based on?
35 benchmarks have a result for both models as of October 21, 2026. GPT-5.4's coding index rests on 1 independent benchmark and Qwen3 32B's on 1. Where only one model has a result, the page says so instead of naming a winner.