GPT-4 vs Qwen3 235B A22B Thinking 2507
Qwen3 235B A22B Thinking 2507 leads GPT-4 on the Artificial Analysis Intelligence Index, 12.7 to 6.7, and Qwen3 235B A22B Thinking 2507 costs 17.1x less per output token ($3.50 vs $60.00 per million). Updated October 22, 2026; 31 benchmarks have a result for both.
GPT-4 or Qwen3 235B A22B Thinking 2507: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4 for work measured by AA Coding Index or LMArena Text: coding, where it leads.
- Shared results
- 31
- GPT-4 only
- 14
- Qwen3 235B A22B Thinking 2507 only
- 15
- Like-for-like categories
- 6 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Qwen3 235B A22B Thinking 2507
Qwen3 235B A22B Thinking 2507 leads, 12.7 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3 235B A22B Thinking 2507 has a AA Agentic Index result, 1.3.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3 235B A22B Thinking 2507 has a Design Arena: websites result, 1052.
Directional only
Long documents
Listed context window
Qwen3 235B A22B Thinking 2507
Qwen3 235B A22B Thinking 2507 takes 128K tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 235B A22B Thinking 2507
GPT-4 $0.060, Qwen3 235B A22B Thinking 2507 $0.0022 per turn.
List prices
At a glance
- Coding index
- GPT-4 not benchmarked, Qwen3 235B A22B Thinking 2507 not benchmarked.
- Widest category
- Knowledge, 44.1 points apart on average over 4 shared benchmarks.
- Widest single gap
- LMArena Text: expert: GPT-4 1149 against Qwen3 235B A22B Thinking 2507 1463, 52.4 points apart on a 0 to 100 scale.
- Output price
- GPT-4 $60.00 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 17.1x apart.
- Context window
- GPT-4 takes 8K tokens, Qwen3 235B A22B Thinking 2507 128K.
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-4 | Bars | Qwen3 235B A22B Thinking 2507 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 18 | ||
| All shared boards | 0 | 31 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| SWE-bench Verified | 22.4% | Not measured | Only GPT-4 measured |
| SWE-bench Lite | 39.7% | Not measured | Only GPT-4 measured |
| SWE-bench (full test set) | 12.5% | Not measured | Only GPT-4 measured |
| AA Coding Index | 13.1 | 22.1 | Qwen3 235B A22B Thinking 2507 |
| WeirdML | Not measured | 41.0% | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: coding | 1209 | 1424 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: software and IT | 1195 | 1431 | Qwen3 235B A22B Thinking 2507 |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 12.7 | Qwen3 235B A22B Thinking 2507 |
| Epoch Capabilities Index | 125.7 | Not measured | Only GPT-4 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.3 | Only Qwen3 235B A22B Thinking 2507 measured |
| Vending-Bench 2 | Not measured | -$11 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 34.9% | Not measured | Only GPT-4 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 80.1% | Only Qwen3 235B A22B Thinking 2507 measured |
| Mystery game puzzles | Not measured | 9.0% | Only Qwen3 235B A22B Thinking 2507 measured |
| BIG-Bench Hard | 75.1% | Not measured | Only GPT-4 measured |
| LMArena Text: hard prompts | 1200 | 1416 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: expert | 1149 | 1463 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: hard prompts in English | 1209 | 1432 | Qwen3 235B A22B Thinking 2507 |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3 235B A22B Thinking 2507 measured |
| GSM8K | 92.0% | Not measured | Only GPT-4 measured |
| LMArena Text: math | 1230 | 1412 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: mathematical work | 1228 | 1435 | Qwen3 235B A22B Thinking 2507 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 56.2% | Not measured | Only GPT-4 measured |
| SimpleQA Verified | Not measured | 40.4% | Only Qwen3 235B A22B Thinking 2507 measured |
| MMLU | 86.4% | Not measured | Only GPT-4 measured |
| AI2 Reasoning Challenge | 96.3% | Not measured | Only GPT-4 measured |
| LMArena Text: science | 1177 | 1433 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: medicine and healthcare | 1145 | 1456 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: legal and government | 1191 | 1415 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: business and finance | 1145 | 1413 | Qwen3 235B A22B Thinking 2507 |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1052 | Only Qwen3 235B A22B Thinking 2507 measured |
| Design Arena: UI components | Not measured | 942 | Only Qwen3 235B A22B Thinking 2507 measured |
| Design Arena: game dev | Not measured | 956 | Only Qwen3 235B A22B Thinking 2507 measured |
| Design Arena: data viz | Not measured | 950 | Only Qwen3 235B A22B Thinking 2507 measured |
| Design Arena: 3D | Not measured | 997 | Only Qwen3 235B A22B Thinking 2507 measured |
| Design Arena: all code categories | Not measured | 1032 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| IFBench | 33.2% | Not measured | Only GPT-4 measured |
| DTBench | 62.7% | 80.3% | Qwen3 235B A22B Thinking 2507 |
| LMCA | 17.1% | 29.3% | Qwen3 235B A22B Thinking 2507 |
| Fiction.LiveBench | Not measured | 75.0% | Only Qwen3 235B A22B Thinking 2507 measured |
| Creative writing (Lech Mazur) | Not measured | 82.4% | Only Qwen3 235B A22B Thinking 2507 measured |
| HellaSwag | 95.3% | Not measured | Only GPT-4 measured |
| WinoGrande | 87.5% | Not measured | Only GPT-4 measured |
| LMArena Text | 1206 | 1415 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: instruction following | 1201 | 1386 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: creative writing | 1191 | 1384 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: English | 1220 | 1429 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: non-English | 1194 | 1397 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: Chinese | 1184 | 1481 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: German | 1198 | 1408 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: Japanese | 1137 | 1386 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: Korean | 1087 | 1375 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: French | 1220 | Not measured | Only GPT-4 measured |
| LMArena Text: Spanish | 1197 | 1389 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: Russian | 1195 | 1401 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: Polish | 1265 | 1390 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: multi-turn | 1206 | 1406 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: longer queries | 1190 | 1400 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: writing and language | 1219 | 1388 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: entertainment and media | 1184 | 1370 | Qwen3 235B A22B Thinking 2507 |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 | Qwen3 235B A22B Thinking 2507 | 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 235B A22B Thinking 2507 costs less
Repository review
50K input + 3K output tokens
Qwen3 235B A22B Thinking 2507 costs less
Agent loop
200K input + 10K output tokens
Qwen3 235B A22B Thinking 2507 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-4 | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | May 28, 2023 | July 25, 2025 |
| Context window | 8K | 128K |
| Input $/Mtok | $30.00 | $0.45 |
| Output $/Mtok | $60.00 | $3.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4 better than Qwen3 235B A22B Thinking 2507 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4 for work measured by AA Coding Index or LMArena Text: coding, where it leads.
Which is cheaper, GPT-4 or Qwen3 235B A22B Thinking 2507?
GPT-4 costs $30.00 per million input tokens and $60.00 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4 or Qwen3 235B A22B Thinking 2507?
Qwen3 235B A22B Thinking 2507, with 128K tokens against 8K.
How many benchmarks is the GPT-4 vs Qwen3 235B A22B Thinking 2507 comparison based on?
31 benchmarks have a result for both models as of October 22, 2026. GPT-4's coding index rests on 0 independent benchmarks and Qwen3 235B A22B Thinking 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.