DeepSeek V3.2 Exp vs Qwen3 235B A22B Thinking 2507
DeepSeek V3.2 Exp leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 16.6 to 12.7, and DeepSeek V3.2 Exp costs 8.5x less per output token ($0.41 vs $3.50 per million). Updated October 22, 2026; 38 benchmarks have a result for both.
DeepSeek V3.2 Exp 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 DeepSeek V3.2 Exp for output tokens 8.5x cheaper ($0.41 vs $3.50 per million) and a larger context window (164K against 128K tokens).
- Shared results
- 38
- DeepSeek V3.2 Exp only
- 22
- Qwen3 235B A22B Thinking 2507 only
- 8
- Like-for-like categories
- 7 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
DeepSeek V3.2 Exp
DeepSeek V3.2 Exp leads, 16.6 against 12.7.
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
DeepSeek V3.2 Exp
DeepSeek V3.2 Exp leads, 1179 against 1052.
Same board, both measured
Long documents
Listed context window
DeepSeek V3.2 Exp
DeepSeek V3.2 Exp takes 164K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.2 Exp
DeepSeek V3.2 Exp $0.0005, Qwen3 235B A22B Thinking 2507 $0.0022 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.2 Exp not benchmarked, Qwen3 235B A22B Thinking 2507 not benchmarked.
- Widest category
- Web design, 21.4 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: UI components: DeepSeek V3.2 Exp 1164 against Qwen3 235B A22B Thinking 2507 942, 27.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.2 Exp $0.41 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 8.5x apart.
- Context window
- DeepSeek V3.2 Exp takes 164K 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 | DeepSeek V3.2 Exp | Bars | Qwen3 235B A22B Thinking 2507 | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 1 | ||
| Math | 1 | 1 | ||
| Knowledge | 3 | 1 | ||
| Web design | 6 | 0 | ||
| General | 15 | 4 | ||
| All shared boards | 30 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| Aider polyglot | 74.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena WebDev | 1272 | Not measured | Only DeepSeek V3.2 Exp measured |
| AA Coding Index | Not measured | 22.1 | Only Qwen3 235B A22B Thinking 2507 measured |
| LiveCodeBench (Artificial Analysis run) | 78.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.1% | Not measured | Only DeepSeek V3.2 Exp measured |
| WeirdML | 39.5% | 41.0% | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: coding | 1438 | 1424 | DeepSeek V3.2 Exp |
| LMArena Text: software and IT | 1438 | 1431 | DeepSeek V3.2 Exp |
| LMArena WebDev: HTML | 1281 | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.6 | 12.7 | DeepSeek V3.2 Exp |
| Epoch Capabilities Index | 144.9 | Not measured | Only DeepSeek V3.2 Exp measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.3 | Only Qwen3 235B A22B Thinking 2507 measured |
| τ²-Bench Telecom | 33.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| TheAgentCompany | 42.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| Vending-Bench 2 | Not measured | -$11 | Only Qwen3 235B A22B Thinking 2507 measured |
| Berkeley Function Calling Leaderboard (BFCL) | 56.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| Humanity's Last Exam (Artificial Analysis run) | 14.9% | Not measured | Only DeepSeek V3.2 Exp 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 |
| LMArena Text: hard prompts | 1429 | 1416 | DeepSeek V3.2 Exp |
| LMArena Text: expert | 1422 | 1463 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: hard prompts in English | 1444 | 1432 | DeepSeek V3.2 Exp |
| Kagi LLM Benchmark | 52.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only DeepSeek V3.2 Exp measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: math | 1422 | 1412 | DeepSeek V3.2 Exp |
| LMArena Text: mathematical work | 1433 | 1435 | Qwen3 235B A22B Thinking 2507 |
| MathArena | 14.4% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 85.0% | Not measured | Only DeepSeek V3.2 Exp measured |
| SimpleQA Verified | Not measured | 40.4% | Only Qwen3 235B A22B Thinking 2507 measured |
| LMArena Text: science | 1443 | 1433 | DeepSeek V3.2 Exp |
| LMArena Text: medicine and healthcare | 1468 | 1456 | DeepSeek V3.2 Exp |
| LMArena Text: legal and government | 1419 | 1415 | DeepSeek V3.2 Exp |
| LMArena Text: business and finance | 1412 | 1413 | Qwen3 235B A22B Thinking 2507 |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | 1179 | 1052 | DeepSeek V3.2 Exp |
| Design Arena: UI components | 1164 | 942 | DeepSeek V3.2 Exp |
| Design Arena: game dev | 1143 | 956 | DeepSeek V3.2 Exp |
| Design Arena: data viz | 1152 | 950 | DeepSeek V3.2 Exp |
| Design Arena: 3D | 1148 | 997 | DeepSeek V3.2 Exp |
| Design Arena: all code categories | 1170 | 1032 | DeepSeek V3.2 Exp |
| Design Arena: SVG | 1031 | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index154
| Benchmark | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| IFBench | 54.1% | Not measured | Only DeepSeek V3.2 Exp measured |
| Long context reasoning (AA-LCR) | 72.3% | Not measured | Only DeepSeek V3.2 Exp measured |
| DTBench | 87.7% | 80.3% | DeepSeek V3.2 Exp |
| LMCA | 29.1% | 29.3% | Qwen3 235B A22B Thinking 2507 |
| Fiction.LiveBench | 83.3% | 75.0% | DeepSeek V3.2 Exp |
| Creative writing (Lech Mazur) | Not measured | 82.4% | Only Qwen3 235B A22B Thinking 2507 measured |
| CL-bench | 13.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| CL-bench Life | 9.5% | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text | 1425 | 1415 | DeepSeek V3.2 Exp |
| LMArena Text: instruction following | 1401 | 1386 | DeepSeek V3.2 Exp |
| LMArena Text: creative writing | 1404 | 1384 | DeepSeek V3.2 Exp |
| LMArena Text: English | 1441 | 1429 | DeepSeek V3.2 Exp |
| LMArena Text: non-English | 1404 | 1397 | DeepSeek V3.2 Exp |
| LMArena Text: Chinese | 1461 | 1481 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: German | 1440 | 1408 | DeepSeek V3.2 Exp |
| LMArena Text: Japanese | 1331 | 1386 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: Korean | 1372 | 1375 | Qwen3 235B A22B Thinking 2507 |
| LMArena Text: French | 1434 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Spanish | 1441 | 1389 | DeepSeek V3.2 Exp |
| LMArena Text: Russian | 1412 | 1401 | DeepSeek V3.2 Exp |
| LMArena Text: Polish | 1435 | 1390 | DeepSeek V3.2 Exp |
| LMArena Text: multi-turn | 1422 | 1406 | DeepSeek V3.2 Exp |
| LMArena Text: longer queries | 1418 | 1400 | DeepSeek V3.2 Exp |
| LMArena Text: writing and language | 1407 | 1388 | DeepSeek V3.2 Exp |
| LMArena Text: entertainment and media | 1407 | 1370 | DeepSeek V3.2 Exp |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.2 Exp | 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
DeepSeek V3.2 Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.2 Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.2 Exp 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 | DeepSeek V3.2 Exp | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | Open weights |
| Released | September 29, 2025 | July 25, 2025 |
| Context window | 164K | 128K |
| Input $/Mtok | $0.27 | $0.45 |
| Output $/Mtok | $0.41 | $3.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.2 Exp 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 DeepSeek V3.2 Exp for output tokens 8.5x cheaper ($0.41 vs $3.50 per million) and a larger context window (164K against 128K tokens).
Which is cheaper, DeepSeek V3.2 Exp or Qwen3 235B A22B Thinking 2507?
DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 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, DeepSeek V3.2 Exp or Qwen3 235B A22B Thinking 2507?
DeepSeek V3.2 Exp, with 164K tokens against 128K.
How many benchmarks is the DeepSeek V3.2 Exp vs Qwen3 235B A22B Thinking 2507 comparison based on?
38 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark 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.