DeepSeek V3.1 vs Qwen3 235B A22B Thinking 2507
DeepSeek V3.1 leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 13.7 to 12.7, and DeepSeek V3.1 costs 2.3x less per output token ($1.50 vs $3.50 per million). Updated October 22, 2026; 9 benchmarks have a result for both.
DeepSeek V3.1 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 V3.1 for output tokens 2.3x cheaper ($1.50 vs $3.50 per million) and a larger context window (164K against 128K tokens).
- Shared results
- 9
- DeepSeek V3.1 only
- 2
- Qwen3 235B A22B Thinking 2507 only
- 37
- Like-for-like categories
- 3 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 V3.1
DeepSeek V3.1 leads, 13.7 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 V3.1
DeepSeek V3.1 leads, 1122 against 1052.
Same board, both measured
Long documents
Listed context window
DeepSeek V3.1
DeepSeek V3.1 takes 164K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1
DeepSeek V3.1 $0.0013, Qwen3 235B A22B Thinking 2507 $0.0022 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, Qwen3 235B A22B Thinking 2507 not benchmarked.
- Widest category
- Web design, 13.4 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: data viz: DeepSeek V3.1 1096 against Qwen3 235B A22B Thinking 2507 950, 18.3 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 2.3x apart.
- Context window
- DeepSeek V3.1 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 V3.1 | Bars | Qwen3 235B A22B Thinking 2507 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Web design | 6 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 8 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | DeepSeek V3.1 | 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 39 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3.1 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 12.7 | DeepSeek V3.1 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V3.1 | 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 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| 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 | 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 |
| Kagi LLM Benchmark | 53.2% | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3 235B A22B Thinking 2507 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 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | DeepSeek V3.1 | 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 15 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | DeepSeek V3.1 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| Design Arena: websites | 1122 | 1052 | DeepSeek V3.1 |
| Design Arena: UI components | 1083 | 942 | DeepSeek V3.1 |
| Design Arena: game dev | 1084 | 956 | DeepSeek V3.1 |
| Design Arena: data viz | 1096 | 950 | DeepSeek V3.1 |
| Design Arena: 3D | 1077 | 997 | DeepSeek V3.1 |
| Design Arena: all code categories | 1112 | 1032 | DeepSeek V3.1 |
| Design Arena: SVG | 967 | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | DeepSeek V3.1 | Qwen3 235B A22B Thinking 2507 | Leader |
|---|---|---|---|
| DTBench | 82.7% | 80.3% | DeepSeek V3.1 |
| LMCA | 24.3% | 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 |
| 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 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | 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 V3.1 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 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 | DeepSeek V3.1 | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | Open weights |
| Released | August 21, 2025 | July 25, 2025 |
| Context window | 164K | 128K |
| Input $/Mtok | $0.55 | $0.45 |
| Output $/Mtok | $1.50 | $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 DeepSeek V3.1 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 V3.1 for output tokens 2.3x cheaper ($1.50 vs $3.50 per million) and a larger context window (164K against 128K tokens).
Which is cheaper, DeepSeek V3.1 or Qwen3 235B A22B Thinking 2507?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 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 V3.1 or Qwen3 235B A22B Thinking 2507?
DeepSeek V3.1, with 164K tokens against 128K.
How many benchmarks is the DeepSeek V3.1 vs Qwen3 235B A22B Thinking 2507 comparison based on?
9 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.1'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.