DeepSeek V3.2 Exp vs Qwen3 Coder 30B A3B Instruct
DeepSeek V3.2 Exp leads Qwen3 Coder 30B A3B Instruct on the Artificial Analysis Intelligence Index, 16.6 to 9.6, at about the same output price ($0.41 vs $0.44 per million). Updated October 22, 2026; 14 benchmarks have a result for both.
DeepSeek V3.2 Exp or Qwen3 Coder 30B A3B Instruct: 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 1.1x cheaper ($0.41 vs $0.44 per million) and work measured by τ²-Bench Telecom, where it leads.
- Shared results
- 14
- DeepSeek V3.2 Exp only
- 45
- Qwen3 Coder 30B A3B Instruct only
- 2
- Like-for-like categories
- 8 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 9.6.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V3.2 Exp
DeepSeek V3.2 Exp leads, 1178 against 1087.
Same board, both measured
Long documents
Listed context window
Qwen3 Coder 30B A3B Instruct
Qwen3 Coder 30B A3B Instruct takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder 30B A3B Instruct
DeepSeek V3.2 Exp $0.0005, Qwen3 Coder 30B A3B Instruct $0.0003 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.2 Exp not benchmarked, Qwen3 Coder 30B A3B Instruct not benchmarked.
- Widest category
- Math, 58.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: DeepSeek V3.2 Exp 87.7 against Qwen3 Coder 30B A3B Instruct 29.0, 58.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.2 Exp $0.41 against Qwen3 Coder 30B A3B Instruct $0.44 per million output tokens, 1.1x apart.
- Context window
- DeepSeek V3.2 Exp takes 164K tokens, Qwen3 Coder 30B A3B Instruct 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 V3.2 Exp | Bars | Qwen3 Coder 30B A3B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 3 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 13 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | 74.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| SWE-bench Verified | Not measured | 60.4% | Only Qwen3 Coder 30B A3B Instruct measured |
| SWE-bench Lite | Not measured | 49.7% | Only Qwen3 Coder 30B A3B Instruct measured |
| LMArena WebDev | 1272 | Not measured | Only DeepSeek V3.2 Exp measured |
| LiveCodeBench (Artificial Analysis run) | 78.9% | 40.3% | DeepSeek V3.2 Exp |
| Terminal-Bench Hard (Artificial Analysis run) | 31.1% | 15.2% | DeepSeek V3.2 Exp |
| WeirdML | 39.5% | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: coding | 1438 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: software and IT | 1438 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena WebDev: HTML | 1281 | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.6 | 9.6 | DeepSeek V3.2 Exp |
| Epoch Capabilities Index | 144.9 | Not measured | Only DeepSeek V3.2 Exp measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 33.9% | 34.5% | Qwen3 Coder 30B A3B Instruct |
| TheAgentCompany | 42.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| Berkeley Function Calling Leaderboard (BFCL) | 56.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 79.7% | 51.6% | DeepSeek V3.2 Exp |
| Humanity's Last Exam (Artificial Analysis run) | 14.9% | 3.8% | DeepSeek V3.2 Exp |
| LMArena Text: hard prompts | 1429 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: expert | 1422 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: hard prompts in English | 1444 | Not measured | Only DeepSeek V3.2 Exp measured |
| Kagi LLM Benchmark | 52.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | 29.0 | DeepSeek V3.2 Exp |
| AIME 2025 (Artificial Analysis run) | 87.7% | 29.0% | DeepSeek V3.2 Exp |
| LMArena Text: math | 1422 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: mathematical work | 1433 | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 85.0% | 70.6% | DeepSeek V3.2 Exp |
| LMArena Text: science | 1443 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: medicine and healthcare | 1468 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: legal and government | 1419 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: business and finance | 1412 | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1178 | 1087 | DeepSeek V3.2 Exp |
| Design Arena: UI components | 1164 | 1043 | DeepSeek V3.2 Exp |
| Design Arena: game dev | 1144 | Not measured | Only DeepSeek V3.2 Exp measured |
| Design Arena: data viz | 1152 | 1085 | DeepSeek V3.2 Exp |
| Design Arena: 3D | 1148 | Not measured | Only DeepSeek V3.2 Exp measured |
| Design Arena: all code categories | 1170 | Not measured | Only DeepSeek V3.2 Exp measured |
| 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 index20
| Benchmark | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | Leader |
|---|---|---|---|
| IFBench | 54.1% | 32.7% | DeepSeek V3.2 Exp |
| Long context reasoning (AA-LCR) | 72.3% | 32.7% | DeepSeek V3.2 Exp |
| DTBench | 87.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| LMCA | 29.1% | Not measured | Only DeepSeek V3.2 Exp measured |
| Fiction.LiveBench | 83.3% | Not measured | Only DeepSeek V3.2 Exp 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 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: instruction following | 1401 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: creative writing | 1404 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: English | 1441 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: non-English | 1404 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Chinese | 1461 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: German | 1440 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Japanese | 1331 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Korean | 1372 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: French | 1434 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Spanish | 1441 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Russian | 1412 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Polish | 1435 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: multi-turn | 1422 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: longer queries | 1418 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: writing and language | 1407 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: entertainment and media | 1407 | Not measured | Only DeepSeek V3.2 Exp measured |
| 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 | DeepSeek V3.2 Exp | Qwen3 Coder 30B A3B Instruct | 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 Coder 30B A3B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen3 Coder 30B A3B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen3 Coder 30B A3B Instruct 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 Coder 30B A3B Instruct |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | Open weights |
| Released | September 29, 2025 | July 31, 2025 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.27 | $0.11 |
| Output $/Mtok | $0.41 | $0.44 |
| 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 Coder 30B A3B Instruct 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 1.1x cheaper ($0.41 vs $0.44 per million) and work measured by τ²-Bench Telecom, where it leads.
Which is cheaper, DeepSeek V3.2 Exp or Qwen3 Coder 30B A3B Instruct?
DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Qwen3 Coder 30B A3B Instruct costs $0.11 and $0.44. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.2 Exp or Qwen3 Coder 30B A3B Instruct?
Qwen3 Coder 30B A3B Instruct, with 262K tokens against 164K.
How many benchmarks is the DeepSeek V3.2 Exp vs Qwen3 Coder 30B A3B Instruct comparison based on?
14 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 Coder 30B A3B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.