Ling 3.0 Flash vs Qwen3.6 Plus
Qwen3.6 Plus leads Ling 3.0 Flash on coding, 44.1 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 16.0x less per output token ($0.1215 vs $1.95 per million). Updated October 22, 2026; 20 benchmarks have a result for both.
Ling 3.0 Flash or Qwen3.6 Plus: which to pick
Pick Qwen3.6 Plus for coding: it scores 44.1 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.
Pick Ling 3.0 Flash for output tokens 16.0x cheaper ($0.1215 vs $1.95 per million) and a lower cost per solved task ($0.05 against $1.19).
- Shared results
- 20
- Ling 3.0 Flash only
- 4
- Qwen3.6 Plus only
- 63
- Like-for-like categories
- 6 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
Qwen3.6 Plus
Qwen3.6 Plus scores 44.1 against 29.6.
2 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.6 Plus
Qwen3.6 Plus leads, 27.0 against 20.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash has a AA Agentic Index result, 19.3.
Directional only
Reasoning
GPQA Diamond
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.4% against 84.8%.
Same board, both measured
Math
AIME
No call
Only Qwen3.6 Plus has a AIME result, 94.6%.
Directional only
Knowledge
MMLU Pro
Qwen3.6 Plus
Qwen3.6 Plus leads, 87.7% against 82.0%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Qwen3.6 Plus has a Design Arena: websites result, 1243.
Directional only
Long documents
Listed context window
Qwen3.6 Plus
Qwen3.6 Plus takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, Qwen3.6 Plus $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Ling 3.0 Flash
Ling 3.0 Flash $0.05, Qwen3.6 Plus $1.19.
Published attempt cost and pass rate
At a glance
- Coding index
- Ling 3.0 Flash 29.6 from 2 benchmarks, Qwen3.6 Plus 44.1 from 3 benchmarks.
- Widest category
- Agentic work, 11.1 points apart on average over 3 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Ling 3.0 Flash 2.9% against Qwen3.6 Plus 25.6%, 22.7 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash $0.1215 against Qwen3.6 Plus $1.95 per million output tokens, 16.0x apart.
- Context window
- Ling 3.0 Flash takes 262K tokens, Qwen3.6 Plus 1M.
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 | Ling 3.0 Flash | Bars | Qwen3.6 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 0 | 3 | ||
| Knowledge | 0 | 4 | 1 tie | |
| General | 1 | 1 | ||
| All shared boards | 1 | 18 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1461 | Only Qwen3.6 Plus measured |
| AA Coding Index | 50.6 | 54.5 | Qwen3.6 Plus |
| LiveCodeBench (Vals AI) | 84.0% | 86.0% | Qwen3.6 Plus |
| SWE-bench Verified (Vals AI) | 65.2% | 73.4% | Qwen3.6 Plus |
| Vibe Code Bench (Vals AI) | 2.9% | 25.6% | Qwen3.6 Plus |
| Code migration (Vals AI) | 0.0% | 11.1% | Qwen3.6 Plus |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.6 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | 53.2% | Qwen3.6 Plus |
| SkillsBench (Vals AI) | 27.9% | Not measured | Only Ling 3.0 Flash measured |
| SciCode | 42.0% | Not measured | Only Ling 3.0 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 43.9% | Only Qwen3.6 Plus measured |
| ALE-Bench | Not measured | 670.1 | Only Qwen3.6 Plus measured |
| LMArena Text: coding | Not measured | 1467 | Only Qwen3.6 Plus measured |
| LMArena Text: software and IT | Not measured | 1462 | Only Qwen3.6 Plus measured |
| LMArena WebDev: React | Not measured | 1454 | Only Qwen3.6 Plus measured |
| LMArena WebDev: HTML | Not measured | 1463 | Only Qwen3.6 Plus measured |
| LMArena WebDev: from an image | Not measured | 1472 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | 27.0 | Qwen3.6 Plus |
| Epoch Capabilities Index | Not measured | 147.3 | Only Qwen3.6 Plus measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | 19.3 | Not measured | Only Ling 3.0 Flash measured |
| Finance Agent (Vals AI) | 30.3% | 40.9% | Qwen3.6 Plus |
| Tax Agent Bench (Vals AI) | Not measured | 7.7% | Only Qwen3.6 Plus measured |
| Legal Research Bench (Vals AI) | 0.0% | 14.9% | Qwen3.6 Plus |
| Excel Modeling Benchmark (Vals AI) | 25.0% | 32.9% | Qwen3.6 Plus |
| τ²-Bench Telecom | Not measured | 97.7% | Only Qwen3.6 Plus measured |
| Vending-Bench 2 | Not measured | $5,115 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | 87.4% | Qwen3.6 Plus |
| MMMU Pro (Vals AI) | Not measured | 84.2% | Only Qwen3.6 Plus measured |
| GPQA Diamond (Artificial Analysis run) | 85.5% | 88.2% | Qwen3.6 Plus |
| Humanity's Last Exam (Artificial Analysis run) | 23.7% | 27.8% | Qwen3.6 Plus |
| GPQA Diamond (Epoch AI run) | Not measured | 88.4% | Only Qwen3.6 Plus measured |
| Chess puzzles | Not measured | 14.0% | Only Qwen3.6 Plus measured |
| Mystery game puzzles | Not measured | 12.0% | Only Qwen3.6 Plus measured |
| LMArena Text: hard prompts | Not measured | 1448 | Only Qwen3.6 Plus measured |
| LMArena Text: expert | Not measured | 1454 | Only Qwen3.6 Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1455 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| AIME | Not measured | 94.6% | Only Qwen3.6 Plus measured |
| OTIS Mock AIME | Not measured | 93.3% | Only Qwen3.6 Plus measured |
| FrontierMath, tiers 1 to 3 | Not measured | 38.2% | Only Qwen3.6 Plus measured |
| LMArena Text: math | Not measured | 1449 | Only Qwen3.6 Plus measured |
| LMArena Text: mathematical work | Not measured | 1448 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 82.0% | 87.7% | Qwen3.6 Plus |
| LegalBench (Vals AI) | 79.7% | 84.2% | Qwen3.6 Plus |
| CaseLaw (Vals AI) | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| CorpFin (Vals AI) | 61.9% | 61.9% | Tie |
| TaxEval (Vals AI) | 70.7% | 74.7% | Qwen3.6 Plus |
| MortgageTax (Vals AI) | Not measured | 68.0% | Only Qwen3.6 Plus measured |
| MedCode (Vals AI) | 32.3% | 36.9% | Qwen3.6 Plus |
| SimpleQA Verified | Not measured | 44.1% | Only Qwen3.6 Plus measured |
| LMArena Text: science | Not measured | 1439 | Only Qwen3.6 Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1442 | Only Qwen3.6 Plus measured |
| LMArena Text: legal and government | Not measured | 1437 | Only Qwen3.6 Plus measured |
| LMArena Text: business and finance | Not measured | 1430 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1243 | Only Qwen3.6 Plus measured |
| Design Arena: UI components | Not measured | 1230 | Only Qwen3.6 Plus measured |
| Design Arena: game dev | Not measured | 1211 | Only Qwen3.6 Plus measured |
| Design Arena: data viz | Not measured | 1228 | Only Qwen3.6 Plus measured |
| Design Arena: 3D | Not measured | 1202 | Only Qwen3.6 Plus measured |
| Design Arena: all code categories | Not measured | 1236 | Only Qwen3.6 Plus measured |
| Design Arena: SVG | Not measured | 1161 | Only Qwen3.6 Plus measured |
| Design Arena: ASCII art | Not measured | 1113 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 50.7% | Not measured | Only Ling 3.0 Flash measured |
| SAGE (Vals AI) | Not measured | 44.9% | Only Qwen3.6 Plus measured |
| MedScribe (Vals AI) | 80.9% | 77.0% | Ling 3.0 Flash |
| Vals Multimodal Index | Not measured | 51.5% | Only Qwen3.6 Plus measured |
| IFBench | Not measured | 75.2% | Only Qwen3.6 Plus measured |
| Long context reasoning (AA-LCR) | 73.0% | 78.3% | Qwen3.6 Plus |
| DTBench | Not measured | 81.9% | Only Qwen3.6 Plus measured |
| LMCA | Not measured | 33.1% | Only Qwen3.6 Plus measured |
| CL-bench | Not measured | 20.3% | Only Qwen3.6 Plus measured |
| LMArena Text | Not measured | 1436 | Only Qwen3.6 Plus measured |
| LMArena Text: instruction following | Not measured | 1424 | Only Qwen3.6 Plus measured |
| LMArena Text: creative writing | Not measured | 1404 | Only Qwen3.6 Plus measured |
| LMArena Text: English | Not measured | 1445 | Only Qwen3.6 Plus measured |
| LMArena Text: non-English | Not measured | 1424 | Only Qwen3.6 Plus measured |
| LMArena Text: Chinese | Not measured | 1477 | Only Qwen3.6 Plus measured |
| LMArena Text: German | Not measured | 1451 | Only Qwen3.6 Plus measured |
| LMArena Text: Japanese | Not measured | 1390 | Only Qwen3.6 Plus measured |
| LMArena Text: Korean | Not measured | 1379 | Only Qwen3.6 Plus measured |
| LMArena Text: French | Not measured | 1455 | Only Qwen3.6 Plus measured |
| LMArena Text: Spanish | Not measured | 1432 | Only Qwen3.6 Plus measured |
| LMArena Text: Russian | Not measured | 1434 | Only Qwen3.6 Plus measured |
| LMArena Text: Polish | Not measured | 1433 | Only Qwen3.6 Plus measured |
| LMArena Text: multi-turn | Not measured | 1438 | Only Qwen3.6 Plus measured |
| LMArena Text: longer queries | Not measured | 1439 | Only Qwen3.6 Plus measured |
| LMArena Text: writing and language | Not measured | 1418 | Only Qwen3.6 Plus measured |
| LMArena Text: entertainment and media | Not measured | 1402 | Only Qwen3.6 Plus measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash | Qwen3.6 Plus | 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 | inclusionAI Ling 3.0 Flash | Qwen3.6 Plus |
|---|---|---|
| Maker | inclusionAI | Qwen |
| Weights | Open weights | No public weights listed |
| Released | July 23, 2026 | April 2, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.0405 | $0.325 |
| Output $/Mtok | $0.1215 | $1.95 |
| Coding index | 29.6 | 44.1 |
| Independent measurements behind it | 2 | 3 |
| Cost per solved task | $0.05 | $1.19 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than Qwen3.6 Plus for coding?
Pick Qwen3.6 Plus for coding: it scores 44.1 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 16.0x cheaper ($0.1215 vs $1.95 per million) and a lower cost per solved task ($0.05 against $1.19).
Which is cheaper, Ling 3.0 Flash or Qwen3.6 Plus?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; Qwen3.6 Plus costs $0.325 and $1.95. Per solved SWE-bench Verified task, Ling 3.0 Flash costs $0.05 and Qwen3.6 Plus $1.19.
Which has the bigger context window, Ling 3.0 Flash or Qwen3.6 Plus?
Qwen3.6 Plus, with 1M tokens against 262K.
How many benchmarks is the Ling 3.0 Flash vs Qwen3.6 Plus comparison based on?
20 benchmarks have a result for both models as of October 22, 2026. Ling 3.0 Flash's coding index rests on 2 independent benchmarks and Qwen3.6 Plus's on 3. Where only one model has a result, the page says so instead of naming a winner.