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BenchLM
Model A
Qwen3.7 Plus

Alibaba

65.9/100

Supported · Public rank #30

90% interval 55.8–76.0

Qwen3.7 Plus vs Qwen3.8-27B

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

Model B
Qwen3.8-27B

Alibaba

—

Evidence status unavailable

90% interval unavailable

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.

13 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.

  • Long documents

    Prompts that approach the documented context limit

    Qwen3.7 Plus

    Qwen3.7 Plus has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    Confidence: limited

  • 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
13
Qwen3.7 Plus only
38
Qwen3.8-27B only
14
Like-for-like categories
0 / 8

5 categories use 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

Directional only
Qwen3.7 Plus
71.7
Qwen3.8-27B
84.3
Weighted basis
2 vs 1 rows
Reading
Directional only

Coding

Directional only
Qwen3.7 Plus
75.6
Qwen3.8-27B
61.7
Weighted basis
4 vs 1 rows
Reading
Directional only

Knowledge

Directional only
Qwen3.7 Plus
60.1
Qwen3.8-27B
38.7
Weighted basis
4 vs 2 rows
Reading
Directional only

Multimodal

Directional only
Qwen3.7 Plus
81.5
Qwen3.8-27B
90.2
Weighted basis
2 vs 1 rows
Reading
Directional only

Instruction following

Directional only
Qwen3.7 Plus
84.5
Qwen3.8-27B
79.5
Weighted basis
2 vs 1 rows
Reading
Directional only

Reasoning

Not comparable
Qwen3.7 Plus
91.7
Qwen3.8-27B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Qwen3.7 Plus
92.9
Qwen3.8-27B
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Qwen3.7 Plus
85.4
Qwen3.8-27B
Not measured
Weighted basis
1 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

Qwen3.7 Plus
API rate not published
Fits in one request
Qwen3.8-27B
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.7 Plus has no comparable published API token rate. Qwen3.8-27B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Qwen3.7 Plus
API rate not published
Fits in one request
Qwen3.8-27B
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.7 Plus has no comparable published API token rate. Qwen3.8-27B has no comparable published API token rate.

Cache-heavy agent loop

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

Qwen3.7 Plus
API rate not published
Fits in one request
Cached-input rate unavailable
Qwen3.8-27B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Qwen3.7 Plus has no comparable published API token rate. Qwen3.8-27B 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.

Context window

Maximum documented context; output-token limits may be lower.

Qwen3.7 Plus

1M

Qwen3.8-27B

262K

Qwen3.8-27B model card

API model ID

Qwen3.7 Plus

Not sourced

Qwen3.8-27B

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Qwen3.7 Plus

No comparable hosted API rate

Qwen3.8-27B

No comparable hosted API rate

Qwen3.8-27B model card

Documented inputs

Qwen3.7 Plus

Not sourced

Qwen3.8-27B

Not sourced

Documented outputs

Qwen3.7 Plus

Not sourced

Qwen3.8-27B

Not sourced

Provider availability

Qwen3.7 Plus

Not sourced

Qwen3.8-27B

Not sourced

Reasoning profile

Qwen3.7 Plus

Reasoning

Qwen3.8-27B

Reasoning

Weight access

Qwen3.7 Plus

Proprietary

Qwen3.8-27B

Open Weight

License

Qwen3.7 Plus

Proprietary

Qwen3.8-27B

Open Weight

Release date

Qwen3.7 Plus

2026-06-03

Qwen3.8-27B

2026-08-05

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
Qwen3.7 Plus 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 evidence65 rows

Agentic

  • Terminal-Bench 2.0

    Qwen3.7 Plus70.3%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • QwenClawBench

    Qwen3.7 Plus61.8%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • Claw-Eval

    Qwen3.7 Plus62.7%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • BFCL v4

    Qwen3.7 Plus72.9%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MCP Atlas

    Qwen3.7 Plus73.2%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • VITA-Bench

    Qwen3.7 Plus45.6%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • DeepPlanning

    Qwen3.7 Plus62.3%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • OSWorld-Verified

    Qwen3.7 Plus73.3%
    Source
    Qwen3.8-27B84.3%
    Source

    Qwen3.8-27B leads this result

  • AndroidWorld

    Qwen3.7 Plus81.0%
    Source
    Qwen3.8-27B81.9%
    Source

    Qwen3.8-27B leads this result

  • OSWorld 2.0

    Qwen3.7 Plus2.8%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • Terminal-Bench 2.1

    Qwen3.7 Plus—
    Qwen3.8-27B73.0%
    Source

    Not directly comparable

  • CoWorkBench

    Qwen3.7 Plus—
    Qwen3.8-27B70.7%
    Source

    Not directly comparable

  • JobBench

    Qwen3.7 Plus—
    Qwen3.8-27B33.4%
    Source

    Not directly comparable

  • Agents' Last Exam

    Qwen3.7 Plus—
    Qwen3.8-27B42.9%
    Source

    Not directly comparable

  • WebArena-Verified

    Qwen3.7 Plus—
    Qwen3.8-27B64.8%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.0

    Qwen3.7 Plus70.3%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • SWE-bench Verified

    Qwen3.7 Plus77.7%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • SWE-bench Pro

    Qwen3.7 Plus57.6%
    Source
    Qwen3.8-27B61.7%
    Source

    Qwen3.8-27B leads this result

  • SWE Multilingual

    Qwen3.7 Plus75.8%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • NL2Repo

    Qwen3.7 Plus41.1%
    Source
    Qwen3.8-27B42.3%
    Source

    Qwen3.8-27B leads this result

  • SciCode

    Qwen3.7 Plus51.3%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • LiveCodeBench

    Qwen3.7 Plus89.6%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • Terminal-Bench 2.1

    Qwen3.7 Plus—
    Qwen3.8-27B73.0%
    Source

    Not directly comparable

  • deepSwe

    Qwen3.7 Plus—
    Qwen3.8-27B42.2%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Qwen3.7 Plus—
    Qwen3.8-27B90.3%
    Source

    Not directly comparable

Reasoning

  • CritPt

    Qwen3.7 Plus9.1%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MRCRv2

    Qwen3.7 Plus91.7%
    Source
    Qwen3.8-27B—

    Not directly comparable

Knowledge

  • GPQA

    Qwen3.7 Plus90.3%
    Source
    Qwen3.8-27B89.2%
    Source

    Qwen3.7 Plus leads this result

  • GPQA-D

    Qwen3.7 Plus90.3%
    Source
    Qwen3.8-27B89.2%
    Source

    Qwen3.7 Plus leads this result

  • HLE

    Qwen3.7 Plus34.7%
    Source
    Qwen3.8-27B30.8%
    Source

    Qwen3.7 Plus leads this result

  • MMLU-Pro

    Qwen3.7 Plus88.5%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MMLU-Redux

    Qwen3.7 Plus94.5%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • SuperGPQA

    Qwen3.7 Plus71.4%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MMMLU

    Qwen3.7 Plus89.0%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • HLE w/o tools

    Qwen3.7 Plus—
    Qwen3.8-27B30.8%
    Source

    Not directly comparable

Math

  • HMMT Feb 2026

    Qwen3.7 Plus92.9%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • IMOAnswerBench

    Qwen3.7 Plus86.0%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • Apex

    Qwen3.7 Plus22.7%
    Source
    Qwen3.8-27B—

    Not directly comparable

Multilingual

  • MMLU-ProX

    Qwen3.7 Plus85.4%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • NOVA-63

    Qwen3.7 Plus58.8%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • INCLUDE

    Qwen3.7 Plus83.0%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MAXIFE

    Qwen3.7 Plus88.8%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • PolyMath

    Qwen3.7 Plus84.0%
    Source
    Qwen3.8-27B—

    Not directly comparable

Multimodal

  • MMMU-Pro

    Qwen3.7 Plus79%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MathVision

    Qwen3.7 Plus90.3%
    Source
    Qwen3.8-27B90.0%
    Source

    Qwen3.7 Plus leads this result

  • CharXiv

    Qwen3.7 Plus85.9%
    Source
    Qwen3.8-27B90.2%
    Source

    Qwen3.8-27B leads this result

  • ERQA

    Qwen3.7 Plus69.8%
    Source
    Qwen3.8-27B65.5%
    Source

    Qwen3.7 Plus leads this result

  • MedXpertQA (MM)

    Qwen3.7 Plus71.0%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • ScreenSpot Pro

    Qwen3.7 Plus79.0%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • SimpleVQA

    Qwen3.7 Plus81.7%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MMSearch-Plus

    Qwen3.7 Plus41.4%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • RealWorldQA

    Qwen3.7 Plus86.9%
    Source
    Qwen3.8-27B85.9%
    Source

    Qwen3.7 Plus leads this result

  • OmniDocBench 1.5

    Qwen3.7 Plus91.4%
    Source
    Qwen3.8-27B91.1%
    Source

    Qwen3.7 Plus leads this result

  • OCRBench V2

    Qwen3.7 Plus70.7%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • ODINW13

    Qwen3.7 Plus51.1%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • Video-MME (with subtitle)

    Qwen3.7 Plus88.0%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • VideoMMMU

    Qwen3.7 Plus85.4%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MLVU (M-Avg)

    Qwen3.7 Plus87.4%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • MathVision w/ Python

    Qwen3.7 Plus—
    Qwen3.8-27B94.6%
    Source

    Not directly comparable

  • BabyVision

    Qwen3.7 Plus—
    Qwen3.8-27B65.7%
    Source

    Not directly comparable

  • BabyVision w/ Python

    Qwen3.7 Plus—
    Qwen3.8-27B85.6%
    Source

    Not directly comparable

  • Vision2Web

    Qwen3.7 Plus—
    Qwen3.8-27B62.9%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Qwen3.7 Plus—
    Qwen3.8-27B83.7%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Qwen3.7 Plus94.6%
    Source
    Qwen3.8-27B—

    Not directly comparable

  • IFBench

    Qwen3.7 Plus79.1%
    Source
    Qwen3.8-27B79.5%
    Source

    Qwen3.8-27B leads this result

Frequently asked questions

Which is better, Qwen3.7 Plus or Qwen3.8-27B?

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, Qwen3.7 Plus or Qwen3.8-27B?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Qwen3.7 Plus or Qwen3.8-27B?

The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Qwen3.7 Plus or Qwen3.8-27B?

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, Qwen3.7 Plus or Qwen3.8-27B?

Qwen3.7 Plus 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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