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BenchLM

Claude Sonnet 4.5 vs Qwen3.7 Plus

Decision reading

Qwen3.7 Plus has the higher public score estimate, 61.6 versus 54.01, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

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

Anthropic logo
Model A
Claude Sonnet 4.5

Anthropic

54.01/100

Supported · Public rank #104

90% interval 50.2–57.8

Alibaba logo
Model B
Qwen3.7 Plus

Alibaba

61.6/100

Supported · Public rank #54

90% interval 50.6–72.6

Updated September 18, 2026. Rank says Qwen3.7 Plus is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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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

    Claude Sonnet 4.5 and Qwen3.7 Plus are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Claude Sonnet 4.5 is scored on Estimated evidence for agentic, so the reading is 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

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Sonnet 4.5 does not fit this workload in one request. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.7 Plus has no comparable published API token rate.

    Confidence: rate-fallback

  • 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.

50.8Claude Sonnet 4.552.6Qwen3.7 Plus

Directional only · BenchAlign

Qwen3.7 Plus scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.

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

Open the coding leaderboardShortlist models for this job

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
5
Claude Sonnet 4.5 only
6
Qwen3.7 Plus only
47
Like-for-like categories
0 / 8

3 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

Directional only
Claude Sonnet 4.5
44.3
Estimated · #93/154
Qwen3.7 Plus
36.7
Supported · #133/154
Basis
BenchAlign lane · 5 vs 11 public rows
Reading
Directional only

Coding

Directional only
Claude Sonnet 4.5
50.8
Estimated · #56/154
Qwen3.7 Plus
52.6
Estimated · #48/154
Basis
BenchAlign lane · 1 vs 7 public rows
Reading
Directional only

Knowledge

Directional only
Claude Sonnet 4.5
51.4
Estimated · #72/184
Qwen3.7 Plus
56.2
Estimated · #49/184
Basis
BenchAlign lane · 1 vs 7 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Sonnet 4.5
19.1
Unranked · 1 rankable row
Qwen3.7 Plus
74.0
Unranked · 3 rankable rows
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 4.5
34.6
Unranked · 2 rankable rows
Qwen3.7 Plus
78.2
Unranked · 3 rankable rows
Basis
Provisional lane · 2 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 4.5
Not ranked
Qwen3.7 Plus
78.9
#3/12
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Sonnet 4.5
Not ranked
Qwen3.7 Plus
72.4
#18/48
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 4.5
Not ranked
Qwen3.7 Plus
89.2
#18/124
Basis
Provisional lane · 0 vs 1 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

Claude Sonnet 4.5
$0.0105
Fits in one request
Qwen3.7 Plus
API rate not published
Fits in one request

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

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 4.5
$0.195
Fits in one request
Qwen3.7 Plus
API rate not published
Fits in one request

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

Cache-heavy agent loop

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

Claude Sonnet 4.5
$0.81
Does not fit in one request
Cached input priced at the published list-input rate
Qwen3.7 Plus
API rate not published
Fits in one request
Cached-input rate unavailable

Claude Sonnet 4.5 does not fit this workload in one request. Claude Sonnet 4.5 has no published cached-input rate, so cached tokens use its listed input 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.

Claude Sonnet 4.5

200K

Qwen3.7 Plus

1M

API model ID

Claude Sonnet 4.5

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.

Claude Sonnet 4.5

Not published

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

Claude Sonnet 4.5

Not sourced

Qwen3.7 Plus

Not sourced

Documented outputs

Claude Sonnet 4.5

Not sourced

Qwen3.7 Plus

Not sourced

Provider availability

Claude Sonnet 4.5

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

Claude Sonnet 4.5

Non-Reasoning

Qwen3.7 Plus

Reasoning

Weight access

Claude Sonnet 4.5

Proprietary

Qwen3.7 Plus

Proprietary

License

Claude Sonnet 4.5

Proprietary

Qwen3.7 Plus

Proprietary

Release date

Claude Sonnet 4.5

2025-09-01

Qwen3.7 Plus

2026-06-03

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
Qwen3.7 Plus has the higher public score estimate, 61.6 versus 54.01, but the 90% score intervals overlap.
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 evidence58 rows

Agentic

  • Terminal-Bench 2.0

    Claude Sonnet 4.550%
    Source
    Qwen3.7 Plus70.3%
    Source

    Qwen3.7 Plus leads this result

  • OSWorld-Verified

    Claude Sonnet 4.561.4%
    Source
    Qwen3.7 Plus73.3%
    Source

    Qwen3.7 Plus leads this result

  • VITA-Bench

    Claude Sonnet 4.517.0%
    Source
    Qwen3.7 Plus45.6%
    Source

    Qwen3.7 Plus leads this result

  • Gert Labs

    Claude Sonnet 4.548.51%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • JobBench

    Claude Sonnet 4.527.7%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • QwenClawBench

    Claude Sonnet 4.5—
    Qwen3.7 Plus61.8%
    Source

    Not directly comparable

  • Claw-Eval

    Claude Sonnet 4.5—
    Qwen3.7 Plus62.7%
    Source

    Not directly comparable

  • BFCL v4

    Claude Sonnet 4.5—
    Qwen3.7 Plus72.9%
    Source

    Not directly comparable

  • MCP Atlas

    Claude Sonnet 4.5—
    Qwen3.7 Plus73.2%
    Source

    Not directly comparable

  • DeepPlanning

    Claude Sonnet 4.5—
    Qwen3.7 Plus62.3%
    Source

    Not directly comparable

  • AndroidWorld

    Claude Sonnet 4.5—
    Qwen3.7 Plus81.0%
    Source

    Not directly comparable

  • OSWorld 2.0

    Claude Sonnet 4.5—
    Qwen3.7 Plus2.8%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Sonnet 4.5—
    Qwen3.7 Plus52.8%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Sonnet 4.577.2%
    Source
    Qwen3.7 Plus77.7%
    Source

    Qwen3.7 Plus leads this result

  • Terminal-Bench 2.0

    Claude Sonnet 4.5—
    Qwen3.7 Plus70.3%
    Source

    Not directly comparable

  • SWE-bench Pro

    Claude Sonnet 4.5—
    Qwen3.7 Plus57.6%
    Source

    Not directly comparable

  • SWE Multilingual

    Claude Sonnet 4.5—
    Qwen3.7 Plus75.8%
    Source

    Not directly comparable

  • NL2Repo

    Claude Sonnet 4.5—
    Qwen3.7 Plus41.1%
    Source

    Not directly comparable

  • SciCode

    Claude Sonnet 4.5—
    Qwen3.7 Plus51.3%
    Source

    Not directly comparable

  • LiveCodeBench

    Claude Sonnet 4.5—
    Qwen3.7 Plus89.6%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Claude Sonnet 4.513.6%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • CritPt

    Claude Sonnet 4.5—
    Qwen3.7 Plus9.1%
    Source

    Not directly comparable

  • MRCRv2

    Claude Sonnet 4.5—
    Qwen3.7 Plus91.7%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Claude Sonnet 4.583.4%
    Source
    Qwen3.7 Plus90.3%
    Source

    Qwen3.7 Plus leads this result

  • GPQA-D

    Claude Sonnet 4.5—
    Qwen3.7 Plus90.3%
    Source

    Not directly comparable

  • HLE

    Claude Sonnet 4.5—
    Qwen3.7 Plus34.7%
    Source

    Not directly comparable

  • MMLU-Pro

    Claude Sonnet 4.5—
    Qwen3.7 Plus88.5%
    Source

    Not directly comparable

  • MMLU-Redux

    Claude Sonnet 4.5—
    Qwen3.7 Plus94.5%
    Source

    Not directly comparable

  • SuperGPQA

    Claude Sonnet 4.5—
    Qwen3.7 Plus71.4%
    Source

    Not directly comparable

  • MMMLU

    Claude Sonnet 4.5—
    Qwen3.7 Plus89.0%
    Source

    Not directly comparable

Math

  • AIME 2025

    Claude Sonnet 4.587%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Sonnet 4.513.495%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Sonnet 4.54.167%
    Source
    Qwen3.7 Plus—

    Not directly comparable

  • HMMT Feb 2026

    Claude Sonnet 4.5—
    Qwen3.7 Plus92.9%
    Source

    Not directly comparable

  • IMOAnswerBench

    Claude Sonnet 4.5—
    Qwen3.7 Plus86.0%
    Source

    Not directly comparable

  • Apex

    Claude Sonnet 4.5—
    Qwen3.7 Plus22.7%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Claude Sonnet 4.5—
    Qwen3.7 Plus85.4%
    Source

    Not directly comparable

  • NOVA-63

    Claude Sonnet 4.5—
    Qwen3.7 Plus58.8%
    Source

    Not directly comparable

  • INCLUDE

    Claude Sonnet 4.5—
    Qwen3.7 Plus83.0%
    Source

    Not directly comparable

  • MAXIFE

    Claude Sonnet 4.5—
    Qwen3.7 Plus88.8%
    Source

    Not directly comparable

  • PolyMath

    Claude Sonnet 4.5—
    Qwen3.7 Plus84.0%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Claude Sonnet 4.5—
    Qwen3.7 Plus79%
    Source

    Not directly comparable

  • MathVision

    Claude Sonnet 4.5—
    Qwen3.7 Plus90.3%
    Source

    Not directly comparable

  • CharXiv

    Claude Sonnet 4.5—
    Qwen3.7 Plus85.9%
    Source

    Not directly comparable

  • ERQA

    Claude Sonnet 4.5—
    Qwen3.7 Plus69.8%
    Source

    Not directly comparable

  • MedXpertQA (MM)

    Claude Sonnet 4.5—
    Qwen3.7 Plus71.0%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Claude Sonnet 4.5—
    Qwen3.7 Plus79.0%
    Source

    Not directly comparable

  • SimpleVQA

    Claude Sonnet 4.5—
    Qwen3.7 Plus81.7%
    Source

    Not directly comparable

  • MMSearch-Plus

    Claude Sonnet 4.5—
    Qwen3.7 Plus41.4%
    Source

    Not directly comparable

  • RealWorldQA

    Claude Sonnet 4.5—
    Qwen3.7 Plus86.9%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Claude Sonnet 4.5—
    Qwen3.7 Plus91.4%
    Source

    Not directly comparable

  • OCRBench V2

    Claude Sonnet 4.5—
    Qwen3.7 Plus70.7%
    Source

    Not directly comparable

  • ODINW13

    Claude Sonnet 4.5—
    Qwen3.7 Plus51.1%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Claude Sonnet 4.5—
    Qwen3.7 Plus88.0%
    Source

    Not directly comparable

  • VideoMMMU

    Claude Sonnet 4.5—
    Qwen3.7 Plus85.4%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Claude Sonnet 4.5—
    Qwen3.7 Plus87.4%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Claude Sonnet 4.5—
    Qwen3.7 Plus94.6%
    Source

    Not directly comparable

  • IFBench

    Claude Sonnet 4.5—
    Qwen3.7 Plus79.1%
    Source

    Not directly comparable

Questions

Which is better, Claude Sonnet 4.5 or Qwen3.7 Plus?

Qwen3.7 Plus has the higher public score estimate, 61.6 versus 54.01, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Sonnet 4.5 or Qwen3.7 Plus?

Qwen3.7 Plus scores higher for coding on the public lane, 52.6 to 50.8. Claude Sonnet 4.5 and Qwen3.7 Plus are 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, Claude Sonnet 4.5 or Qwen3.7 Plus?

Claude Sonnet 4.5 scores higher for agentic tasks on the public lane, 44.3 to 36.7. Claude Sonnet 4.5 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Sonnet 4.5 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, Claude Sonnet 4.5 or Qwen3.7 Plus?

Qwen3.7 Plus has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 18, 2026

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