DeepSeek V3.1 vs Qwen3.5 397B A17B
Qwen3.5 397B A17B leads DeepSeek V3.1 on the Artificial Analysis Intelligence Index, 21.4 to 13.7, and DeepSeek V3.1 costs 1.6x less per output token ($1.50 vs $2.34 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
DeepSeek V3.1 or Qwen3.5 397B A17B: 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 1.6x cheaper ($1.50 vs $2.34 per million) and work measured by AA Intelligence Index or Design Arena: websites, where it leads.
- Shared results
- 10
- DeepSeek V3.1 only
- 1
- Qwen3.5 397B A17B only
- 55
- 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
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 21.4 against 13.7.
Same board, both measured
Web design
Design Arena: websites
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 1190 against 1122.
Same board, both measured
Long documents
Listed context window
Qwen3.5 397B A17B
Qwen3.5 397B A17B takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1
DeepSeek V3.1 $0.0013, Qwen3.5 397B A17B $0.0016 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, Qwen3.5 397B A17B not benchmarked.
- Widest category
- Web design, 10.7 points apart on average over 7 shared benchmarks.
- Widest single gap
- Design Arena: SVG: DeepSeek V3.1 967 against Qwen3.5 397B A17B 1139, 21.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.6x apart.
- Context window
- DeepSeek V3.1 takes 164K tokens, Qwen3.5 397B A17B 262K.
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 | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Web design | 0 | 7 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 10 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1400 | Only Qwen3.5 397B A17B measured |
| SciCode | Not measured | 44.8% | Only Qwen3.5 397B A17B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 40.9% | Only Qwen3.5 397B A17B measured |
| ALE-Bench | Not measured | 621.9 | Only Qwen3.5 397B A17B measured |
| LMArena Text: coding | Not measured | 1464 | Only Qwen3.5 397B A17B measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: React | Not measured | 1388 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: HTML | Not measured | 1410 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 21.4 | Qwen3.5 397B A17B |
| Epoch Capabilities Index | Not measured | 146.8 | Only Qwen3.5 397B A17B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 95.6% | Only Qwen3.5 397B A17B measured |
| APEX-Agents | Not measured | 24.9% | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.3% | Only Qwen3.5 397B A17B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 29.0% | Only Qwen3.5 397B A17B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 86.4% | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | Not measured | 1448 | Only Qwen3.5 397B A17B measured |
| LMArena Text: expert | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts in English | Not measured | 1450 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B measured |
| Kagi LLM Benchmark | 53.2% | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 88.9% | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 31.2% | Only Qwen3.5 397B A17B measured |
| LMArena Text: math | Not measured | 1453 | Only Qwen3.5 397B A17B measured |
| LMArena Text: mathematical work | Not measured | 1454 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1457 | Only Qwen3.5 397B A17B measured |
| LMArena Text: medicine and healthcare | Not measured | 1455 | Only Qwen3.5 397B A17B measured |
| LMArena Text: legal and government | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1122 | 1190 | Qwen3.5 397B A17B |
| Design Arena: UI components | 1085 | 1160 | Qwen3.5 397B A17B |
| Design Arena: game dev | 1084 | 1140 | Qwen3.5 397B A17B |
| Design Arena: data viz | 1096 | 1175 | Qwen3.5 397B A17B |
| Design Arena: 3D | 1077 | 1160 | Qwen3.5 397B A17B |
| Design Arena: all code categories | 1112 | 1179 | Qwen3.5 397B A17B |
| Design Arena: SVG | 967 | 1139 | Qwen3.5 397B A17B |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| IFBench | Not measured | 78.8% | Only Qwen3.5 397B A17B measured |
| Long context reasoning (AA-LCR) | Not measured | 77.3% | Only Qwen3.5 397B A17B measured |
| DTBench | 82.7% | 87.5% | Qwen3.5 397B A17B |
| LMCA | 24.3% | 37.9% | Qwen3.5 397B A17B |
| LMArena Text | Not measured | 1437 | Only Qwen3.5 397B A17B measured |
| LMArena Text: instruction following | Not measured | 1424 | Only Qwen3.5 397B A17B measured |
| LMArena Text: creative writing | Not measured | 1402 | Only Qwen3.5 397B A17B measured |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | Not measured | 1443 | Only Qwen3.5 397B A17B measured |
| LMArena Text: non-English | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Chinese | Not measured | 1498 | Only Qwen3.5 397B A17B measured |
| LMArena Text: German | Not measured | 1445 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Japanese | Not measured | 1429 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.5 397B A17B measured |
| LMArena Text: French | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Spanish | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Russian | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Polish | Not measured | 1447 | Only Qwen3.5 397B A17B measured |
| LMArena Text: multi-turn | Not measured | 1446 | Only Qwen3.5 397B A17B measured |
| LMArena Text: longer queries | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: writing and language | Not measured | 1415 | Only Qwen3.5 397B A17B measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | Qwen3.5 397B A17B | 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
Qwen3.5 397B A17B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | Open weights |
| Released | August 21, 2025 | February 16, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.55 | $0.39 |
| Output $/Mtok | $1.50 | $2.34 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 better than Qwen3.5 397B A17B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.1 for output tokens 1.6x cheaper ($1.50 vs $2.34 per million) and work measured by AA Intelligence Index or Design Arena: websites, where it leads.
Which is cheaper, DeepSeek V3.1 or Qwen3.5 397B A17B?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.1 or Qwen3.5 397B A17B?
Qwen3.5 397B A17B, with 262K tokens against 164K.
How many benchmarks is the DeepSeek V3.1 vs Qwen3.5 397B A17B comparison based on?
10 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.1's coding index rests on 0 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.