GPT-5.2 Pro vs Qwen3 235B A22B Thinking 2507
Qwen3 235B A22B Thinking 2507 costs 48.0x less per output token than GPT-5.2 Pro ($3.50 vs $168.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $168.00
- Coding
- No data
- Overall
- 52.9
- Output $/M
- $3.50
GPT-5.2 Pro 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-5.2 Pro for a larger context window (400K against 128K tokens).
No benchmark has tested both yet. GPT-5.2 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; Qwen3 235B A22B Thinking 2507 on AA Coding Index, WeirdML and LMArena Text: coding. Compare them on price and context instead.
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
No call
Only Qwen3 235B A22B Thinking 2507 has a AA Intelligence Index result, 12.7.
Directional only
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
GPT-5.2 Pro
GPT-5.2 Pro takes 400K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 235B A22B Thinking 2507
GPT-5.2 Pro $0.105, Qwen3 235B A22B Thinking 2507 $0.0022 per turn.
List prices
At a glance
- Coding index
- GPT-5.2 Pro not benchmarked, Qwen3 235B A22B Thinking 2507 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-5.2 Pro $168.00 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 48.0x apart.
- Context window
- GPT-5.2 Pro takes 400K tokens, Qwen3 235B A22B Thinking 2507 128K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 22.1 | Only Qwen3 235B A22B Thinking 2507 measured |
| WeirdML | Not measured | 41.0% | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: coding | Not measured | 1424 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: software and IT | Not measured | 1431 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.7 | Only Qwen3 235B A22B Thinking 2507 measured |
| Epoch Capabilities Index | 156.3 | Not measured | Only GPT-5.2 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.2 Pro | 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 | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | Not measured | 80.1% | Only Qwen3 235B A22B Thinking 2507 measured |
| ARC-AGI | 90.5% | Not measured | Only GPT-5.2 Pro measured |
| ARC-AGI-2 | 54.2% | Not measured | Only GPT-5.2 Pro measured |
| SimpleBench | 57.4% | Not measured | Only GPT-5.2 Pro measured |
| Chess puzzles | 60.0% | Not measured | Only GPT-5.2 Pro measured |
| Mystery game puzzles | Not measured | 9.0% | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: hard prompts | Not measured | 1416 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: expert | Not measured | 1463 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: hard prompts in English | Not measured | 1432 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3 235B A22B Thinking 2507 measured |
| FrontierMath, tiers 1 to 3 | 74.0% | Not measured | Only GPT-5.2 Pro measured |
| FrontierMath, tier 4 | 46.0% | Not measured | Only GPT-5.2 Pro measured |
| LMArena Text: math | Not measured | 1412 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: mathematical work | Not measured | 1435 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| SimpleQA Verified | Not measured | 40.4% | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: science | Not measured | 1433 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: medicine and healthcare | Not measured | 1456 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: legal and government | Not measured | 1415 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: business and finance | Not measured | 1413 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | GPT-5.2 Pro | 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 | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| DTBench | Not measured | 80.3% | Only Qwen3 235B A22B Thinking 2507 measured |
| LMCA | Not measured | 29.3% | Only Qwen3 235B A22B Thinking 2507 measured |
| 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 |
| LMArena Text | Not measured | 1415 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: instruction following | Not measured | 1386 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: creative writing | Not measured | 1384 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: English | Not measured | 1429 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: non-English | Not measured | 1397 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: Chinese | Not measured | 1481 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: German | Not measured | 1408 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: Japanese | Not measured | 1386 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: Korean | Not measured | 1375 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: Spanish | Not measured | 1389 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: Russian | Not measured | 1401 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: Polish | Not measured | 1390 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: multi-turn | Not measured | 1406 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: longer queries | Not measured | 1400 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: writing and language | Not measured | 1388 | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: entertainment and media | Not measured | 1370 | Only Qwen3 235B A22B Thinking 2507 measured |
| Neither model has a result on the other 26 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-5.2 Pro | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | December 10, 2025 | July 25, 2025 |
| Context window | 400K | 128K |
| Input $/Mtok | $21.00 | $0.45 |
| Output $/Mtok | $168.00 | $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-5.2 Pro 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-5.2 Pro for a larger context window (400K against 128K tokens).
Which is cheaper, GPT-5.2 Pro or Qwen3 235B A22B Thinking 2507?
GPT-5.2 Pro costs $21.00 per million input tokens and $168.00 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-5.2 Pro or Qwen3 235B A22B Thinking 2507?
GPT-5.2 Pro, with 400K tokens against 128K.
Has any benchmark tested both GPT-5.2 Pro and Qwen3 235B A22B Thinking 2507?
No benchmark has tested both yet. GPT-5.2 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; Qwen3 235B A22B Thinking 2507 on AA Coding Index, WeirdML and LMArena Text: coding. Compare them on price and context instead. Data as of October 22, 2026.