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BenchLM
Model A
Qwen3.8-27B

Alibaba

—

Evidence status unavailable

90% interval unavailable

Qwen3.8-27B vs Qwen3.8 Max

Updated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Qwen3.8 Max

Alibaba

79.8/100

Supported · Public rank #6

90% interval 77.6–82.0

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

26 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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 leads on the same 1 weighted benchmark row.

    Confidence: limited

  • Agentic work

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

    Qwen3.8 Max

    Qwen3.8 Max leads on the same 1 weighted benchmark row.

    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

What is actually comparable

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

Shared results
26
Qwen3.8-27B only
1
Qwen3.8 Max only
26
Like-for-like categories
4 / 8

1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Like-for-like
Qwen3.8-27B
84.3
Qwen3.8 Max
86.1
Weighted basis
1 vs 1 rows
Reading
Qwen3.8 Max leads

Coding

Like-for-like
Qwen3.8-27B
61.7
Qwen3.8 Max
67.7
Weighted basis
1 vs 1 rows
Reading
Qwen3.8 Max leads

Knowledge

Like-for-like
Qwen3.8-27B
38.7
Qwen3.8 Max
50.2
Weighted basis
2 vs 2 rows
Reading
Qwen3.8 Max leads

Instruction following

Like-for-like
Qwen3.8-27B
79.5
Qwen3.8 Max
82.8
Weighted basis
1 vs 1 rows
Reading
Qwen3.8 Max leads

Multimodal

Directional only
Qwen3.8-27B
90.2
Qwen3.8 Max
86.3
Weighted basis
1 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Qwen3.8-27B
Not measured
Qwen3.8 Max
78.3
Weighted basis
0 vs 2 rows
Reading
Not comparable

Math

Not comparable
Qwen3.8-27B
Not measured
Qwen3.8 Max
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Qwen3.8-27B
Not measured
Qwen3.8 Max
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

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.

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

Qwen3.8-27B
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

Qwen3.8-27B 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

Qwen3.8-27B
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.8 Max
API rate not published
Fits in one request

Qwen3.8-27B 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

Qwen3.8-27B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Qwen3.8 Max
API rate not published
Fits in one request
Cached-input rate unavailable

Qwen3.8-27B has no comparable published API token rate. Qwen3.8 Max has no comparable published API token rate.

Specification differences

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

Documented inputs

Qwen3.8-27B

Not sourced

Qwen3.8 Max

Not sourced

Documented outputs

Qwen3.8-27B

Not sourced

Qwen3.8 Max

Not sourced

Provider availability

Qwen3.8-27B

Not sourced

Qwen3.8 Max

Not sourced

Reasoning profile

Qwen3.8-27B

Reasoning

Qwen3.8 Max

Reasoning

Weight access

Qwen3.8-27B

Open Weight

Qwen3.8 Max

Open Weight

License

Qwen3.8-27B

Open Weight

Qwen3.8 Max

Open Weight

Release date

Qwen3.8-27B

2026-08-05

Qwen3.8 Max

2026-08-03

If you already use one of these models
Deployment change
Both entries list Alibaba as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
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.

Benchmark evidence

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

Browse raw public benchmark evidence53 rows

Agentic

  • Terminal-Bench 2.1

    Qwen3.8-27B73.0%
    Source
    Qwen3.8 Max86.6%
    Source

    Qwen3.8 Max leads this result

  • CoWorkBench

    Qwen3.8-27B70.7%
    Source
    Qwen3.8 Max74.8%
    Source

    Qwen3.8 Max leads this result

  • JobBench

    Qwen3.8-27B33.4%
    Source
    Qwen3.8 Max53.4%
    Source

    Qwen3.8 Max leads this result

  • Agents' Last Exam

    Qwen3.8-27B42.9%
    Source
    Qwen3.8 Max52.4%
    Source

    Qwen3.8 Max leads this result

  • OSWorld-Verified

    Qwen3.8-27B84.3%
    Source
    Qwen3.8 Max86.1%
    Source

    Qwen3.8 Max leads this result

  • WebArena-Verified

    Qwen3.8-27B64.8%
    Source
    Qwen3.8 Max66.8%
    Source

    Qwen3.8 Max leads this result

  • AndroidWorld

    Qwen3.8-27B81.9%
    Source
    Qwen3.8 Max85.3%
    Source

    Qwen3.8 Max leads this result

  • skillsBench

    Qwen3.8-27B—
    Qwen3.8 Max70.2%
    Source

    Not directly comparable

  • AutomationBench

    Qwen3.8-27B—
    Qwen3.8 Max27.3%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Qwen3.8-27B—
    Qwen3.8 Max72.5%
    Source

    Not directly comparable

  • WideResearch

    Qwen3.8-27B—
    Qwen3.8 Max81.9%
    Source

    Not directly comparable

  • HLE w/ tools

    Qwen3.8-27B—
    Qwen3.8 Max56.2%
    Source

    Not directly comparable

  • OSWorld 2.0

    Qwen3.8-27B—
    Qwen3.8 Max19.4%
    Source

    Not directly comparable

  • MobileWorld

    Qwen3.8-27B—
    Qwen3.8 Max77.8%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Qwen3.8-27B73.0%
    Source
    Qwen3.8 Max86.6%
    Source

    Qwen3.8 Max leads this result

  • SWE-bench Pro

    Qwen3.8-27B61.7%
    Source
    Qwen3.8 Max67.7%
    Source

    Qwen3.8 Max leads this result

  • NL2Repo

    Qwen3.8-27B42.3%
    Source
    Qwen3.8 Max55.9%
    Source

    Qwen3.8 Max leads this result

  • deepSwe

    Qwen3.8-27B42.2%
    Source
    Qwen3.8 Max56.6%
    Source

    Qwen3.8 Max leads this result

  • LiveCodeBench v6

    Qwen3.8-27B90.3%
    Source
    Qwen3.8 Max—

    Not directly comparable

  • FrontierSWE

    Qwen3.8-27B—
    Qwen3.8 Max73.5%
    Source

    Not directly comparable

  • MLS-Bench Lite

    Qwen3.8-27B—
    Qwen3.8 Max41.0%
    Source

    Not directly comparable

  • PaperBench

    Qwen3.8-27B—
    Qwen3.8 Max93.0%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Qwen3.8-27B—
    Qwen3.8 Max92.9%
    Source

    Not directly comparable

  • LongBench v2

    Qwen3.8-27B—
    Qwen3.8 Max66.3%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Qwen3.8-27B89.2%
    Source
    Qwen3.8 Max92.6%
    Source

    Qwen3.8 Max leads this result

  • GPQA-D

    Qwen3.8-27B89.2%
    Source
    Qwen3.8 Max92.6%
    Source

    Qwen3.8 Max leads this result

  • HLE

    Qwen3.8-27B30.8%
    Source
    Qwen3.8 Max43.6%
    Source

    Qwen3.8 Max leads this result

  • HLE w/o tools

    Qwen3.8-27B30.8%
    Source
    Qwen3.8 Max43.6%
    Source

    Qwen3.8 Max leads this result

Multimodal

  • MathVision

    Qwen3.8-27B90.0%
    Source
    Qwen3.8 Max95.2%
    Source

    Qwen3.8 Max leads this result

  • MathVision w/ Python

    Qwen3.8-27B94.6%
    Source
    Qwen3.8 Max97.7%
    Source

    Qwen3.8 Max leads this result

  • BabyVision

    Qwen3.8-27B65.7%
    Source
    Qwen3.8 Max82.0%
    Source

    Qwen3.8 Max leads this result

  • BabyVision w/ Python

    Qwen3.8-27B85.6%
    Source
    Qwen3.8 Max91.3%
    Source

    Qwen3.8 Max leads this result

  • Vision2Web

    Qwen3.8-27B62.9%
    Source
    Qwen3.8 Max69.0%
    Source

    Qwen3.8 Max leads this result

  • CharXiv w/o tools

    Qwen3.8-27B83.7%
    Source
    Qwen3.8 Max88.4%
    Source

    Qwen3.8 Max leads this result

  • CharXiv

    Qwen3.8-27B90.2%
    Source
    Qwen3.8 Max93.5%
    Source

    Qwen3.8 Max leads this result

  • OmniDocBench 1.5

    Qwen3.8-27B91.1%
    Source
    Qwen3.8 Max92.1%
    Source

    Qwen3.8 Max leads this result

  • RealWorldQA

    Qwen3.8-27B85.9%
    Source
    Qwen3.8 Max88.0%
    Source

    Qwen3.8 Max leads this result

  • ERQA

    Qwen3.8-27B65.5%
    Source
    Qwen3.8 Max77.8%
    Source

    Qwen3.8 Max leads this result

  • MMMU-Pro

    Qwen3.8-27B—
    Qwen3.8 Max82.3%
    Source

    Not directly comparable

  • ZeroBench

    Qwen3.8-27B—
    Qwen3.8 Max24.0%
    Source

    Not directly comparable

  • ZeroBench w/ Python

    Qwen3.8-27B—
    Qwen3.8 Max49.0%
    Source

    Not directly comparable

  • MedXpertQA (MM)

    Qwen3.8-27B—
    Qwen3.8 Max80.4%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Qwen3.8-27B—
    Qwen3.8 Max84.5%
    Source

    Not directly comparable

  • OCRBench V2

    Qwen3.8-27B—
    Qwen3.8 Max74.2%
    Source

    Not directly comparable

  • CC-OCR

    Qwen3.8-27B—
    Qwen3.8 Max79.6%
    Source

    Not directly comparable

  • SimpleVQA

    Qwen3.8-27B—
    Qwen3.8 Max75.0%
    Source

    Not directly comparable

  • PerceptionBench

    Qwen3.8-27B—
    Qwen3.8 Max63.5%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Qwen3.8-27B—
    Qwen3.8 Max90.4%
    Source

    Not directly comparable

  • VideoMMMU

    Qwen3.8-27B—
    Qwen3.8 Max88.7%
    Source

    Not directly comparable

  • MMVU

    Qwen3.8-27B—
    Qwen3.8 Max82.4%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Qwen3.8-27B—
    Qwen3.8 Max90.8%
    Source

    Not directly comparable

  • LVBench

    Qwen3.8-27B—
    Qwen3.8 Max81.8%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Qwen3.8-27B79.5%
    Source
    Qwen3.8 Max82.8%
    Source

    Qwen3.8 Max leads this result

Frequently asked questions

Which is better, Qwen3.8-27B or Qwen3.8 Max?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Qwen3.8-27B or Qwen3.8 Max?

Qwen3.8 Max leads the like-for-like coding comparison across 1 shared weighted benchmark row.

Which is better for agentic tasks, Qwen3.8-27B or Qwen3.8 Max?

Qwen3.8 Max leads the like-for-like agentic tasks comparison across 1 shared weighted benchmark row.

Which costs less, Qwen3.8-27B 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, Qwen3.8-27B or Qwen3.8 Max?

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

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 14, 2026

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