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BenchLM
Data

Ling 3.0 Flash vs Qwen3.8 Max

Updated October 29, 2026. Rank says Qwen3.8 Max is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Qwen3.8 Max has the higher public point estimate, 64.86 versus 45.33. Their conditional score ranges overlap. These ranges do not establish rank confidence. 14 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
InclusionAI logo
Ling 3.0 Flash

InclusionAI

45.33/100

Estimated · Public rank #116

Conditional range 31.0–59.7

Model B
Alibaba logo
Qwen3.8 Max

Alibaba

64.86/100

Supported · Public rank #33

90% interval 56.0–73.7

Shared results
14
Ling 3.0 Flash only
10
Qwen3.8 Max only
52
Like-for-like categories
4 / 8
Estimated: Ling 3.0 Flash · Supported: Qwen3.8 Max. Conditional ranges do not establish rank confidence.How the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Qwen3.8 Max

    Qwen3.8 Max has the higher public coding point estimate, 52.7 to 32.2, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Qwen3.8 Max

    Qwen3.8 Max has the higher public agentic point estimate, 66 to 34.3, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Qwen3.8 Max

    Qwen3.8 Max has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

32.2Ling 3.0 Flash52.7Qwen3.8 Max

Like-for-like · BenchAlign v5.8

Qwen3.8 Max has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like
Ling 3.0 Flash
34.3
Supported · #94/135
Qwen3.8 Max
66.0
Supported · #16/135
Basis
BenchAlign v5.8 lane · 9 vs 18 public rows
Reading
Qwen3.8 Max leads

Coding

Like-for-like
Ling 3.0 Flash
32.2
Supported · #97/156
Qwen3.8 Max
52.7
Supported · #38/156
Basis
BenchAlign v5.8 lane · 6 vs 13 public rows
Reading
Qwen3.8 Max leads · intervals overlap

Knowledge

Like-for-like
Ling 3.0 Flash
42.1
Supported · #108/179
Qwen3.8 Max
65.5
Supported · #28/179
Basis
BenchAlign v5.8 lane · 5 vs 6 public rows
Reading
Qwen3.8 Max leads

Instruction following

Like-for-like
Ling 3.0 Flash
75.2
#72/157
Qwen3.8 Max
94.7
#2/157
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Qwen3.8 Max leads

Reasoning

Not comparable
Ling 3.0 Flash
75.1
Unranked · 2 rankable rows
Qwen3.8 Max
87.0
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Ling 3.0 Flash
Not ranked
Qwen3.8 Max
91.9
#2/58
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Ling 3.0 Flash
Not ranked
Qwen3.8 Max
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Ling 3.0 Flash
81.1
Unranked · 3 rankable rows
Qwen3.8 Max
78.9
Unranked · 2 rankable rows
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Ling 3.0 Flash
API rate not published
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

Ling 3.0 Flash has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Ling 3.0 Flash
API rate not published
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

Ling 3.0 Flash has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Ling 3.0 Flash
API rate not published
Fits in one request
Cached-input rate unavailable
Qwen3.8 Max
API rate not published
Fits in one request
Cached-input rate unavailable

Ling 3.0 Flash has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Documented inputs

Ling 3.0 Flash

Not sourced

Qwen3.8 Max

Not sourced

Documented outputs

Ling 3.0 Flash

Not sourced

Qwen3.8 Max

Not sourced

Provider availability

Ling 3.0 Flash

Not sourced

Qwen3.8 Max

Not sourced

Reasoning profile

Ling 3.0 Flash

Reasoning

Qwen3.8 Max

Reasoning

Weight access

Ling 3.0 Flash

Open Weight

Qwen3.8 Max

Open Weight

License

Ling 3.0 Flash

Open Weight

Qwen3.8 Max

Open Weight

Release date

Ling 3.0 Flash

2026-07-23

Qwen3.8 Max

2026-08-03

If you already use one of these models

Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
Qwen3.8 Max has the higher public point estimate, 64.86 versus 45.33. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Qwen3.8 Max has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Ling 3.0 Flash or Qwen3.8 Max?

Qwen3.8 Max has the higher public point estimate, 64.86 versus 45.33. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Ling 3.0 Flash or Qwen3.8 Max?

Qwen3.8 Max has the higher public coding point estimate, 52.7 to 32.2, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Ling 3.0 Flash or Qwen3.8 Max?

Qwen3.8 Max has the higher public agentic tasks point estimate, 66 to 34.3, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Ling 3.0 Flash or Qwen3.8 Max?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Ling 3.0 Flash or Qwen3.8 Max?

Qwen3.8 Max has the larger documented context window: 1M, compared with 262K.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Ling 3.0 Flash
API / mo$0
Self-host / mo$6,990
Break-even—
Qwen3.8 Max
API / mo$0
Self-host / mo$57,606
Break-even—
Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence76 rows

Agentic

  • MCP Atlas

    Ling 3.0 Flash65.5%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • skillsBench

    Ling 3.0 Flash44.8%
    Source
    Qwen3.8 Max70.2%
    Source

    Qwen3.8 Max leads this result

  • BFCL v4

    Ling 3.0 Flash73.0%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • WideResearch

    Ling 3.0 Flash73.6%
    Source
    Qwen3.8 Max81.9%
    Source

    Qwen3.8 Max leads this result

  • BrowseComp

    Ling 3.0 Flash72.2%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • DRACO

    Ling 3.0 Flash70.4%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Ling 3.0 Flash50.2%
    Source
    Qwen3.8 Max67.4%
    Source

    Qwen3.8 Max leads this result

  • Hermes Index

    Shared source
    Ling 3.0 Flash21.6%
    Qwen3.8 Max36.2%

    Qwen3.8 Max leads this result

  • Hermes Bench

    Shared source
    Ling 3.0 Flash53.8%
    Qwen3.8 Max70.5%

    Qwen3.8 Max leads this result

  • Terminal-Bench 2.1

    Ling 3.0 Flash—
    Qwen3.8 Max86.6%
    Source

    Not directly comparable

  • CoWorkBench

    Ling 3.0 Flash—
    Qwen3.8 Max74.8%
    Source

    Not directly comparable

  • JobBench

    Ling 3.0 Flash—
    Qwen3.8 Max53.4%
    Source

    Not directly comparable

  • Agents' Last Exam

    Ling 3.0 Flash—
    Qwen3.8 Max52.4%
    Source

    Not directly comparable

  • AutomationBench

    Ling 3.0 Flash—
    Qwen3.8 Max27.3%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Ling 3.0 Flash—
    Qwen3.8 Max72.5%
    Source

    Not directly comparable

  • HLE w/ tools

    Ling 3.0 Flash—
    Qwen3.8 Max56.2%
    Source

    Not directly comparable

  • OSWorld-Verified

    Ling 3.0 Flash—
    Qwen3.8 Max86.1%
    Source

    Not directly comparable

  • OSWorld 2.0

    Ling 3.0 Flash—
    Qwen3.8 Max19.4%
    Source

    Not directly comparable

  • WebArena-Verified

    Ling 3.0 Flash—
    Qwen3.8 Max66.8%
    Source

    Not directly comparable

  • AndroidWorld

    Ling 3.0 Flash—
    Qwen3.8 Max85.3%
    Source

    Not directly comparable

  • MobileWorld

    Ling 3.0 Flash—
    Qwen3.8 Max77.8%
    Source

    Not directly comparable

  • MazeBench

    Ling 3.0 Flash—
    Qwen3.8 Max0%
    Source

    Not directly comparable

Coding

  • SWE-bench Pro

    Ling 3.0 Flash56.6%
    Source
    Qwen3.8 Max67.7%
    Source

    Qwen3.8 Max leads this result

  • SWE Multilingual

    Ling 3.0 Flash72.4%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • LiveCodeBench v5

    Ling 3.0 Flash82.8%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • SciCode

    Ling 3.0 Flash41.2%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • LiveCodeBench (Vals)

    Ling 3.0 Flash84.0%
    Source
    Qwen3.8 Max87.9%
    Source

    Qwen3.8 Max leads this result

  • SWE-bench (Vals)

    Ling 3.0 Flash65.2%
    Source
    Qwen3.8 Max85.6%
    Source

    Qwen3.8 Max leads this result

  • Terminal-Bench 2.1

    Ling 3.0 Flash—
    Qwen3.8 Max86.6%
    Source

    Not directly comparable

  • DeepSWE

    Ling 3.0 Flash—
    Qwen3.8 Max56.6%
    Source

    Not directly comparable

  • NL2Repo

    Ling 3.0 Flash—
    Qwen3.8 Max55.9%
    Source

    Not directly comparable

  • FrontierSWE

    Ling 3.0 Flash—
    Qwen3.8 Max73.5%
    Source

    Not directly comparable

  • MLS-Bench Lite

    Ling 3.0 Flash—
    Qwen3.8 Max41.0%
    Source

    Not directly comparable

  • PaperBench

    Ling 3.0 Flash—
    Qwen3.8 Max93.0%
    Source

    Not directly comparable

  • VulcanBench v3

    Ling 3.0 Flash—
    Qwen3.8 Max81.2%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Ling 3.0 Flash—
    Qwen3.8 Max60.8%
    Source

    Not directly comparable

  • FrontierSWE v2

    Ling 3.0 Flash—
    Qwen3.8 Max15.8%
    Source

    Not directly comparable

  • Bug Hunt Bench

    Ling 3.0 Flash—
    Qwen3.8 Max25.7 fixes
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Ling 3.0 Flash—
    Qwen3.8 Max92.9%
    Source

    Not directly comparable

  • LongBench v2

    Ling 3.0 Flash—
    Qwen3.8 Max66.3%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Ling 3.0 Flash—
    Qwen3.8 Max82.3%
    Source

    Not directly comparable

  • MathVision

    Ling 3.0 Flash—
    Qwen3.8 Max95.2%
    Source

    Not directly comparable

  • MathVision w/ Python

    Ling 3.0 Flash—
    Qwen3.8 Max97.7%
    Source

    Not directly comparable

  • BabyVision

    Ling 3.0 Flash—
    Qwen3.8 Max82.0%
    Source

    Not directly comparable

  • BabyVision w/ Python

    Ling 3.0 Flash—
    Qwen3.8 Max91.3%
    Source

    Not directly comparable

  • ZeroBench

    Ling 3.0 Flash—
    Qwen3.8 Max24.0%
    Source

    Not directly comparable

  • ZeroBench w/ Python

    Ling 3.0 Flash—
    Qwen3.8 Max49.0%
    Source

    Not directly comparable

  • MedXpertQA (MM)

    Ling 3.0 Flash—
    Qwen3.8 Max80.4%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Ling 3.0 Flash—
    Qwen3.8 Max84.5%
    Source

    Not directly comparable

  • Vision2Web

    Ling 3.0 Flash—
    Qwen3.8 Max69.0%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Ling 3.0 Flash—
    Qwen3.8 Max88.4%
    Source

    Not directly comparable

  • CharXiv

    Ling 3.0 Flash—
    Qwen3.8 Max93.5%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Ling 3.0 Flash—
    Qwen3.8 Max92.1%
    Source

    Not directly comparable

  • OCRBench V2

    Ling 3.0 Flash—
    Qwen3.8 Max74.2%
    Source

    Not directly comparable

  • CC-OCR

    Ling 3.0 Flash—
    Qwen3.8 Max79.6%
    Source

    Not directly comparable

  • RealWorldQA

    Ling 3.0 Flash—
    Qwen3.8 Max88.0%
    Source

    Not directly comparable

  • ERQA

    Ling 3.0 Flash—
    Qwen3.8 Max77.8%
    Source

    Not directly comparable

  • SimpleVQA

    Ling 3.0 Flash—
    Qwen3.8 Max75.0%
    Source

    Not directly comparable

  • PerceptionBench

    Ling 3.0 Flash—
    Qwen3.8 Max63.5%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Ling 3.0 Flash—
    Qwen3.8 Max90.4%
    Source

    Not directly comparable

  • VideoMMMU

    Ling 3.0 Flash—
    Qwen3.8 Max88.7%
    Source

    Not directly comparable

  • MMVU

    Ling 3.0 Flash—
    Qwen3.8 Max82.4%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Ling 3.0 Flash—
    Qwen3.8 Max90.8%
    Source

    Not directly comparable

  • LVBench

    Ling 3.0 Flash—
    Qwen3.8 Max81.8%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Ling 3.0 Flash85.0%
    Source
    Qwen3.8 Max92.6%
    Source

    Qwen3.8 Max leads this result

  • GPQA-D

    Ling 3.0 Flash85.0%
    Source
    Qwen3.8 Max92.6%
    Source

    Qwen3.8 Max leads this result

  • HLE

    Ling 3.0 Flash22.7%
    Source
    Qwen3.8 Max43.6%
    Source

    Qwen3.8 Max leads this result

  • GPQA Diamond (Vals)

    Ling 3.0 Flash84.8%
    Source
    Qwen3.8 Max93.7%
    Source

    Qwen3.8 Max leads this result

  • MMLU-Pro (Vals)

    Ling 3.0 Flash82.0%
    Source
    Qwen3.8 Max88.6%
    Source

    Qwen3.8 Max leads this result

  • HLE w/o tools

    Ling 3.0 Flash—
    Qwen3.8 Max43.6%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Ling 3.0 Flash74.5%
    Source
    Qwen3.8 Max82.8%
    Source

    Qwen3.8 Max leads this result

Math

  • AIME26

    Ling 3.0 Flash93.2%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • HMMT Feb 2026

    Ling 3.0 Flash87.0%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • IMOAnswerBench

    Ling 3.0 Flash83.7%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Ling 3.0 Flash—
    Qwen3.8 Max74.737%
    Source

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Ling 3.0 Flash—
    Qwen3.8 Max46.341%
    Source

    Not directly comparable

76 public results · 14 shared

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Last updated October 29, 2026