Skip to main content
Radar

Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.

See the free Radar Brief
BenchLM
Alibaba logo
Model A
Qwen3.7 Max

Alibaba

68.56/100

Supported · Public rank #28

90% interval 62.5–74.6

Qwen3.7 Max vs Qwen3.7 Plus

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Alibaba logo
Model B
Qwen3.7 Plus

Alibaba

62.29/100

Supported · Public rank #60

90% interval 52.4–72.2

Decision reading

Qwen3.7 Max has the higher public score estimate, 68.56 versus 62.29, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

33 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Share or export

Share on XLinkedInSocial cardCSVJSON

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.

  • Agentic work

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

    Qwen3.7 Max

    Qwen3.7 Max leads on the public agentic lane, 42.8 to 37.7, with Supported evidence for both models, although the 90% intervals overlap.

    Confidence: limited

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Qwen3.7 Plus is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • 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
33
Qwen3.7 Max only
8
Qwen3.7 Plus only
19
Like-for-like categories
3 / 8

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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
Qwen3.7 Max
42.8
Supported · #110/151
Qwen3.7 Plus
37.7
Supported · #126/151
Basis
BenchAlign lane · 10 vs 11 public rows
Reading
Qwen3.7 Max leads · intervals overlap

Multilingual

Like-for-like
Qwen3.7 Max
100.0
#1/12
Qwen3.7 Plus
78.9
#3/12
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Qwen3.7 Max leads

Instruction following

Like-for-like
Qwen3.7 Max
91.1
#16/120
Qwen3.7 Plus
91.1
#17/120
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Tie

Coding

Directional only
Qwen3.7 Max
49.5
Supported · #77/183
Qwen3.7 Plus
53.1
Estimated · #51/183
Basis
BenchAlign lane · 10 vs 7 public rows
Reading
Directional only

Knowledge

Directional only
Qwen3.7 Max
62.4
Supported · #28/181
Qwen3.7 Plus
56.8
Estimated · #50/181
Basis
BenchAlign lane · 9 vs 7 public rows
Reading
Directional only

Reasoning

Not comparable
Qwen3.7 Max
74.8
Unranked · 3 rankable rows
Qwen3.7 Plus
73.7
Unranked · 3 rankable rows
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
Qwen3.7 Max
82.1
Unranked · 3 rankable rows
Qwen3.7 Plus
78.3
Unranked · 3 rankable rows
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Qwen3.7 Max
Not ranked
Qwen3.7 Plus
72.5
#18/48
Basis
Provisional lane · 0 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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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 Max
API rate not published
Fits in one request
Qwen3.7 Plus
API rate not published
Fits in one request

Qwen3.7 Max has no comparable published API token rate. Qwen3.7 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Qwen3.7 Max
API rate not published
Fits in one request
Qwen3.7 Plus
API rate not published
Fits in one request

Qwen3.7 Max has no comparable published API token rate. Qwen3.7 Plus has no comparable published API token rate.

Cache-heavy agent loop

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

Qwen3.7 Max
API rate not published
Fits in one request
Cached-input rate unavailable
Qwen3.7 Plus
API rate not published
Fits in one request
Cached-input rate unavailable

Qwen3.7 Max has no comparable published API token rate. Qwen3.7 Plus 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 Max

1M

Qwen3.7 Plus

1M

API model ID

Qwen3.7 Max

Not sourced

Qwen3.7 Plus

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 Max

No comparable hosted API rate

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

Qwen3.7 Max

Not sourced

Qwen3.7 Plus

Not sourced

Documented outputs

Qwen3.7 Max

Not sourced

Qwen3.7 Plus

Not sourced

Provider availability

Qwen3.7 Max

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

Qwen3.7 Max

Reasoning

Qwen3.7 Plus

Reasoning

Weight access

Qwen3.7 Max

Proprietary

Qwen3.7 Plus

Proprietary

License

Qwen3.7 Max

Proprietary

Qwen3.7 Plus

Proprietary

Release date

Qwen3.7 Max

2026-05-16

Qwen3.7 Plus

2026-06-03

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
Qwen3.7 Max has the higher public score estimate, 68.56 versus 62.29, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 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 evidence60 rows

Agentic

  • Terminal-Bench 2.0

    Qwen3.7 Max69.7%
    Source
    Qwen3.7 Plus70.3%
    Source

    Qwen3.7 Plus leads this result

  • QwenClawBench

    Qwen3.7 Max64.3%
    Source
    Qwen3.7 Plus61.8%
    Source

    Qwen3.7 Max leads this result

  • Claw-Eval

    Qwen3.7 Max65.2%
    Source
    Qwen3.7 Plus62.7%
    Source

    Qwen3.7 Max leads this result

  • BFCL v4

    Qwen3.7 Max75.0%
    Source
    Qwen3.7 Plus72.9%
    Source

    Qwen3.7 Max leads this result

  • MCP Atlas

    Qwen3.7 Max76.4%
    Source
    Qwen3.7 Plus73.2%
    Source

    Qwen3.7 Max leads this result

  • VITA-Bench

    Qwen3.7 Max47.9%
    Source
    Qwen3.7 Plus45.6%
    Source

    Qwen3.7 Max leads this result

  • HLE w/ tools

    Qwen3.7 Max53.5%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • Gert Labs

    Qwen3.7 Max64.27%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • ResearchClawBench

    Qwen3.7 Max18.7%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Qwen3.7 Max61.0%
    Source
    Qwen3.7 Plus52.8%
    Source

    Qwen3.7 Max leads this result

  • DeepPlanning

    Qwen3.7 Max—
    Qwen3.7 Plus62.3%
    Source

    Not directly comparable

  • OSWorld-Verified

    Qwen3.7 Max—
    Qwen3.7 Plus73.3%
    Source

    Not directly comparable

  • AndroidWorld

    Qwen3.7 Max—
    Qwen3.7 Plus81.0%
    Source

    Not directly comparable

  • OSWorld 2.0

    Qwen3.7 Max—
    Qwen3.7 Plus2.8%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Qwen3.7 Max80.4%
    Source
    Qwen3.7 Plus77.7%
    Source

    Qwen3.7 Max leads this result

  • SWE-bench Pro

    Qwen3.7 Max60.6%
    Source
    Qwen3.7 Plus57.6%
    Source

    Qwen3.7 Max leads this result

  • SWE Multilingual

    Qwen3.7 Max78.3%
    Source
    Qwen3.7 Plus75.8%
    Source

    Qwen3.7 Max leads this result

  • NL2Repo

    Qwen3.7 Max47.2%
    Source
    Qwen3.7 Plus41.1%
    Source

    Qwen3.7 Max leads this result

  • SciCode

    Qwen3.7 Max53.5%
    Source
    Qwen3.7 Plus51.3%
    Source

    Qwen3.7 Max leads this result

  • LiveCodeBench

    Qwen3.7 Max91.6%
    Source
    Qwen3.7 Plus89.6%
    Source

    Qwen3.7 Max leads this result

  • Terminal-Bench 2.0

    Qwen3.7 Max69.7%
    Source
    Qwen3.7 Plus70.3%
    Source

    Qwen3.7 Plus leads this result

  • OpenHarmony Bench

    Qwen3.7 Max53.4%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • LiveCodeBench (Vals)

    Qwen3.7 Max87.1%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • SWE-bench (Vals)

    Qwen3.7 Max68.8%
    Source
    Qwen3.7 Plus—

    Not directly comparable

Reasoning

  • MRCRv2

    Qwen3.7 Max90.4%
    Source
    Qwen3.7 Plus91.7%
    Source

    Qwen3.7 Plus leads this result

  • CritPt

    Qwen3.7 Max13.4%
    Source
    Qwen3.7 Plus9.1%
    Source

    Qwen3.7 Max leads this result

Knowledge

  • GPQA

    Qwen3.7 Max92.4%
    Source
    Qwen3.7 Plus90.3%
    Source

    Qwen3.7 Max leads this result

  • GPQA-D

    Qwen3.7 Max92.4%
    Source
    Qwen3.7 Plus90.3%
    Source

    Qwen3.7 Max leads this result

  • HLE

    Qwen3.7 Max41.4%
    Source
    Qwen3.7 Plus34.7%
    Source

    Qwen3.7 Max leads this result

  • MMLU-Pro

    Qwen3.7 Max89.6%
    Source
    Qwen3.7 Plus88.5%
    Source

    Qwen3.7 Max leads this result

  • MMLU-Redux

    Qwen3.7 Max95%
    Source
    Qwen3.7 Plus94.5%
    Source

    Qwen3.7 Max leads this result

  • SuperGPQA

    Qwen3.7 Max73.6%
    Source
    Qwen3.7 Plus71.4%
    Source

    Qwen3.7 Max leads this result

  • MMMLU

    Qwen3.7 Max90.3%
    Source
    Qwen3.7 Plus89.0%
    Source

    Qwen3.7 Max leads this result

  • GPQA Diamond (Vals)

    Qwen3.7 Max90.2%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • MMLU-Pro (Vals)

    Qwen3.7 Max89.3%
    Source
    Qwen3.7 Plus—

    Not directly comparable

Math

  • HMMT Feb 2026

    Qwen3.7 Max97.1%
    Source
    Qwen3.7 Plus92.9%
    Source

    Qwen3.7 Max leads this result

  • IMOAnswerBench

    Qwen3.7 Max90.0%
    Source
    Qwen3.7 Plus86.0%
    Source

    Qwen3.7 Max leads this result

  • Apex

    Qwen3.7 Max44.5%
    Source
    Qwen3.7 Plus22.7%
    Source

    Qwen3.7 Max leads this result

Multilingual

  • MMLU-ProX

    Qwen3.7 Max87%
    Source
    Qwen3.7 Plus85.4%
    Source

    Qwen3.7 Max leads this result

  • NOVA-63

    Qwen3.7 Max59.0%
    Source
    Qwen3.7 Plus58.8%
    Source

    Qwen3.7 Max leads this result

  • INCLUDE

    Qwen3.7 Max86.2%
    Source
    Qwen3.7 Plus83.0%
    Source

    Qwen3.7 Max leads this result

  • MAXIFE

    Qwen3.7 Max89.2%
    Source
    Qwen3.7 Plus88.8%
    Source

    Qwen3.7 Max leads this result

  • PolyMath

    Qwen3.7 Max86.5%
    Source
    Qwen3.7 Plus84.0%
    Source

    Qwen3.7 Max leads this result

Multimodal

  • MMMU-Pro

    Qwen3.7 Max—
    Qwen3.7 Plus79%
    Source

    Not directly comparable

  • MathVision

    Qwen3.7 Max—
    Qwen3.7 Plus90.3%
    Source

    Not directly comparable

  • CharXiv

    Qwen3.7 Max—
    Qwen3.7 Plus85.9%
    Source

    Not directly comparable

  • ERQA

    Qwen3.7 Max—
    Qwen3.7 Plus69.8%
    Source

    Not directly comparable

  • MedXpertQA (MM)

    Qwen3.7 Max—
    Qwen3.7 Plus71.0%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Qwen3.7 Max—
    Qwen3.7 Plus79.0%
    Source

    Not directly comparable

  • SimpleVQA

    Qwen3.7 Max—
    Qwen3.7 Plus81.7%
    Source

    Not directly comparable

  • MMSearch-Plus

    Qwen3.7 Max—
    Qwen3.7 Plus41.4%
    Source

    Not directly comparable

  • RealWorldQA

    Qwen3.7 Max—
    Qwen3.7 Plus86.9%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Qwen3.7 Max—
    Qwen3.7 Plus91.4%
    Source

    Not directly comparable

  • OCRBench V2

    Qwen3.7 Max—
    Qwen3.7 Plus70.7%
    Source

    Not directly comparable

  • ODINW13

    Qwen3.7 Max—
    Qwen3.7 Plus51.1%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Qwen3.7 Max—
    Qwen3.7 Plus88.0%
    Source

    Not directly comparable

  • VideoMMMU

    Qwen3.7 Max—
    Qwen3.7 Plus85.4%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Qwen3.7 Max—
    Qwen3.7 Plus87.4%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Qwen3.7 Max94.3%
    Source
    Qwen3.7 Plus94.6%
    Source

    Qwen3.7 Plus leads this result

  • IFBench

    Qwen3.7 Max79.1%
    Source
    Qwen3.7 Plus79.1%
    Source

    Tie

Frequently asked questions

Which is better, Qwen3.7 Max or Qwen3.7 Plus?

Qwen3.7 Max has the higher public score estimate, 68.56 versus 62.29, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Qwen3.7 Max or Qwen3.7 Plus?

Qwen3.7 Plus scores higher for coding on the public lane, 53.1 to 49.5. Qwen3.7 Plus is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Qwen3.7 Max or Qwen3.7 Plus?

Qwen3.7 Max leads the public agentic tasks lane, 42.8 to 37.7, with Supported evidence for both models, although the 90% intervals overlap.

Which costs less, Qwen3.7 Max or Qwen3.7 Plus?

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 Max or Qwen3.7 Plus?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 4, 2026

Watch Qwen3.7 Max vs Qwen3.7 Plus

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.