Ling 3.0 Flash vs Qwen3.7 Max

Qwen3.7 Max leads Ling 3.0 Flash on coding, 54.1 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 36.4x less per output token ($0.1215 vs $4.425 per million). Updated October 22, 2026; 22 benchmarks have a result for both.

Replace Ling 3.0 Flash Replace Qwen3.7 Max

Ling 3.0 FlashinclusionAI

Coding: 29.6
Overall: No data
Output $/M: $0.1215

Qwen3.7 MaxQwen

Coding: 54.1
Overall: 61.7
Output $/M: $4.425

vs boards won of 22 shared

Ling 3.0 Flash or Qwen3.7 Max: which to pick

Pick Qwen3.7 Max for coding: it scores 54.1 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.

Pick Ling 3.0 Flash for output tokens 36.4x cheaper ($0.1215 vs $4.425 per million) and a lower cost per solved task ($0.05 against $4.69).

Model ALing 3.0 FlashinclusionAI29.6/1002 independent benchmarks$0.05 per solved task Model BQwen3.7 MaxQwen54.1/1003 independent benchmarks$4.69 per solved task

22237

Shared results: 22
Ling 3.0 Flash only: 2
Qwen3.7 Max only: 37
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
Qwen3.7 Max
Qwen3.7 Max scores 54.1 against 29.6.
2 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.7 Max
Qwen3.7 Max leads, 29.5 against 20.1.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.7 Max
Qwen3.7 Max leads, 22.5 against 19.3.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.7 Max
Qwen3.7 Max leads, 90.2% against 84.8%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.7 Max
Qwen3.7 Max leads, 89.3% against 82.0%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Qwen3.7 Max has a Design Arena: websites result, 1274.
Directional only
Long documents
Listed context window
Qwen3.7 Max
Qwen3.7 Max 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, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Ling 3.0 Flash
Ling 3.0 Flash $0.05, Qwen3.7 Max $4.69.
Published attempt cost and pass rate

At a glance

Coding index: Ling 3.0 Flash 29.6 from 2 benchmarks, Qwen3.7 Max 54.1 from 3 benchmarks.
Widest category: Agentic work, 19.5 points apart on average over 4 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): Ling 3.0 Flash 2.9% against Qwen3.7 Max 47.7%, 44.8 points apart on a 0 to 100 scale.
Output price: Ling 3.0 Flash $0.1215 against Qwen3.7 Max $4.425 per million output tokens, 36.4x apart.
Context window: Ling 3.0 Flash takes 262K tokens, Qwen3.7 Max 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.

Boards won, where both have a result
Category	Ling 3.0 Flash	Qwen3.7 Max
Coding	0	7
Intelligence	0	1
Agentic work	0	4
Reasoning	0	3
Knowledge	0	5
General	1	1
All shared boards	1	21

CodingLike-for-likeSix of these boards feed the Vibe Coding Index07

Coding benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
LMArena WebDev	Not measured	1515	Only Qwen3.7 Max measured
AA Coding Index	50.6	66.0	Qwen3.7 Max
LiveCodeBench (Vals AI)	84.0%	87.1%	Qwen3.7 Max
SWE-bench Verified (Vals AI)	65.2%	68.8%	Qwen3.7 Max
Vibe Code Bench (Vals AI)	2.9%	47.7%	Qwen3.7 Max
Code migration (Vals AI)	0.0%	13.1%	Qwen3.7 Max
Terminal-Bench 2.1 (Vals AI)	50.2%	61.0%	Qwen3.7 Max
SkillsBench (Vals AI)	27.9%	Not measured	Only Ling 3.0 Flash measured
SciCode	42.0%	49.5%	Qwen3.7 Max
Terminal-Bench Hard (Artificial Analysis run)	Not measured	50.8%	Only Qwen3.7 Max measured
ALE-Bench	Not measured	1189.4	Only Qwen3.7 Max measured
LMArena WebDev: React	Not measured	1514	Only Qwen3.7 Max measured
LMArena WebDev: HTML	Not measured	1512	Only Qwen3.7 Max measured
Neither model has a result on the other 26 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01

Intelligence benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
AA Intelligence Index	20.1	29.5	Qwen3.7 Max
Epoch Capabilities Index	Not measured	154.0	Only Qwen3.7 Max measured

Agentic workLike-for-likePublic boards, shown as published, kept out of the index04

Agentic work benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
AA Agentic Index	19.3	22.5	Qwen3.7 Max
Design Arena: agents building web apps	Not measured	1208	Only Qwen3.7 Max measured
Design Arena: agents building full-stack apps	Not measured	1191	Only Qwen3.7 Max measured
Design Arena: agents building mobile apps	Not measured	1155	Only Qwen3.7 Max measured
Design Arena: agents building Android apps	Not measured	1159	Only Qwen3.7 Max measured
Design Arena: agents building Godot games	Not measured	1187	Only Qwen3.7 Max measured
Design Arena: agents building games	Not measured	1161	Only Qwen3.7 Max measured
Design Arena: HTML slides	Not measured	1108	Only Qwen3.7 Max measured
Design Arena: PowerPoint slides	Not measured	1171	Only Qwen3.7 Max measured
Finance Agent (Vals AI)	30.3%	47.8%	Qwen3.7 Max
Tax Agent Bench (Vals AI)	Not measured	15.8%	Only Qwen3.7 Max measured
Legal Research Bench (Vals AI)	0.0%	25.5%	Qwen3.7 Max
Excel Modeling Benchmark (Vals AI)	25.0%	57.0%	Qwen3.7 Max
τ²-Bench Telecom	Not measured	94.7%	Only Qwen3.7 Max measured
Neither model has a result on the other 27 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index03

Reasoning benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
GPQA Diamond	84.8%	90.2%	Qwen3.7 Max
GPQA Diamond (Artificial Analysis run)	85.5%	92.3%	Qwen3.7 Max
Humanity's Last Exam (Artificial Analysis run)	23.7%	40.5%	Qwen3.7 Max
GPQA Diamond (Epoch AI run)	Not measured	90.9%	Only Qwen3.7 Max measured
SimpleBench	Not measured	70.4%	Only Qwen3.7 Max measured
Chess puzzles	Not measured	26.0%	Only Qwen3.7 Max measured
Mystery game puzzles	Not measured	32.0%	Only Qwen3.7 Max measured
EBR-bench	Not measured	9.5%	Only Qwen3.7 Max measured
Neither model has a result on the other 14 boards here

MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared

Math benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
OTIS Mock AIME	Not measured	95.6%	Only Qwen3.7 Max measured
FrontierMath, tiers 1 to 3	Not measured	64.6%	Only Qwen3.7 Max measured
FrontierMath, tier 4	Not measured	34.1%	Only Qwen3.7 Max measured
ProofBench	Not measured	26.0%	Only Qwen3.7 Max measured
Neither model has a result on the other 9 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05

Knowledge benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
MMLU Pro	82.0%	89.3%	Qwen3.7 Max
LegalBench (Vals AI)	79.7%	84.9%	Qwen3.7 Max
CorpFin (Vals AI)	61.9%	63.7%	Qwen3.7 Max
TaxEval (Vals AI)	70.7%	75.3%	Qwen3.7 Max
MedCode (Vals AI)	32.3%	38.8%	Qwen3.7 Max
SimpleQA Verified	Not measured	55.8%	Only Qwen3.7 Max measured
Neither model has a result on the other 12 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared

Web design benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
Design Arena: websites	Not measured	1274	Only Qwen3.7 Max measured
Design Arena: UI components	Not measured	1267	Only Qwen3.7 Max measured
Design Arena: game dev	Not measured	1264	Only Qwen3.7 Max measured
Design Arena: data viz	Not measured	1275	Only Qwen3.7 Max measured
Design Arena: 3D	Not measured	1265	Only Qwen3.7 Max measured
Design Arena: all code categories	Not measured	1275	Only Qwen3.7 Max measured
Design Arena: SVG	Not measured	1216	Only Qwen3.7 Max measured
Design Arena: ASCII art	Not measured	1211	Only Qwen3.7 Max measured
Neither model has a result on the other 1 board here

GeneralLike-for-likePublic boards, shown as published, kept out of the index11

General benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	Leader
Public Benefits Bench (Vals AI)	50.7%	Not measured	Only Ling 3.0 Flash measured
MedScribe (Vals AI)	80.9%	79.4%	Ling 3.0 Flash
IFBench	Not measured	80.5%	Only Qwen3.7 Max measured
Long context reasoning (AA-LCR)	73.0%	79.0%	Qwen3.7 Max
DTBench	Not measured	92.3%	Only Qwen3.7 Max measured
LMCA	Not measured	44.0%	Only Qwen3.7 Max measured
Neither model has a result on the other 40 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for Ling 3.0 Flash and Qwen3.7 Max
Benchmark	Ling 3.0 Flash	Qwen3.7 Max	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$0.0001Fits in one request

Qwen3.7 Max$0.0037Fits in one request

Ling 3.0 Flash costs less

Repository review

50K input + 3K output tokens

Ling 3.0 Flash$0.0024Fits in one request

Qwen3.7 Max$0.087Fits in one request

Ling 3.0 Flash costs less

Agent loop

200K input + 10K output tokens

Ling 3.0 Flash$0.0093Fits in one request

Qwen3.7 Max$0.339Fits in one request

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.

Specifications of Ling 3.0 Flash and Qwen3.7 Max
Specification	inclusionAI Ling 3.0 Flash	Qwen3.7 Max
Maker	inclusionAI	Qwen
Weights	Open weights	No public weights listed
Released	July 23, 2026	May 21, 2026
Context window	262K	1M
Input $/Mtok	$0.0405	$1.475
Output $/Mtok	$0.1215	$4.425
Coding index	29.6	54.1
Independent measurements behind it	2	3
Cost per solved task	$0.05	$4.69
Source	OpenRouter listing	OpenRouter listing

Questions

Is Ling 3.0 Flash better than Qwen3.7 Max for coding?

Pick Qwen3.7 Max for coding: it scores 54.1 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 36.4x cheaper ($0.1215 vs $4.425 per million) and a lower cost per solved task ($0.05 against $4.69).

Which is cheaper, Ling 3.0 Flash or Qwen3.7 Max?

Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Per solved SWE-bench Verified task, Ling 3.0 Flash costs $0.05 and Qwen3.7 Max $4.69.

Which has the bigger context window, Ling 3.0 Flash or Qwen3.7 Max?

Qwen3.7 Max, with 1M tokens against 262K.

How many benchmarks is the Ling 3.0 Flash vs Qwen3.7 Max comparison based on?

22 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 Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/inclusionai-ling-3-0-flash-vs-qwen3-7-max" title="Ling 3.0 Flash vs Qwen3.7 Max, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/inclusionai-ling-3-0-flash-vs-qwen3-7-max">LLMBenchmark.ai, Ling 3.0 Flash vs Qwen3.7 Max</a></p>

Ling 3.0 Flash or Qwen3.7 Max: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next