Claude Sonnet 5 vs Qwen3.7 Max

Updated September 29, 2026. Rank says Claude Sonnet 5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Claude Sonnet 5 has the higher public score estimate, 66.99 versus 63.32, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 10 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Claude Sonnet 5

Anthropic

66.99/100

Supported · Public rank #23

90% interval 62.7–71.3

Model B

Qwen3.7 Max

Alibaba

63.32/100

Supported · Public rank #38

90% interval 54.1–72.5

Shared results: 10
Claude Sonnet 5 only: 16
Qwen3.7 Max only: 31
Like-for-like categories: 3 / 8

Supported: Claude Sonnet 5 and Qwen3.7 MaxHow 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
Claude Sonnet 5
Claude Sonnet 5 leads on the public coding lane, 59.8 to 45.7, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Claude Sonnet 5
Claude Sonnet 5 leads on the public agentic lane, 64.6 to 39.6, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger

Show secondary and unsupported calls

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

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.

Pick the job you would use them for

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

59.8Claude Sonnet 545.7Qwen3.7 Max

Like-for-like · BenchAlign v5.7

Claude Sonnet 5 leads the like-for-like coding row, although the 90% intervals overlap.

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

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

HLEKnowledge
Normalized gap 16.0
Claude Sonnet 5:57.4%
Qwen3.7 Max:41.4%
Claude Sonnet 5 source Qwen3.7 Max source
SWE-bench VerifiedCoding
Normalized gap 4.8
Claude Sonnet 5:85.2%
Qwen3.7 Max:80.4%
Claude Sonnet 5 source Qwen3.7 Max source
LiveCodeBench (Vals)Coding
Normalized gap 4.7
Claude Sonnet 5:82.4%
Qwen3.7 Max:87.1%
Claude Sonnet 5 source Qwen3.7 Max source
SWE-bench ProCoding
Normalized gap 2.6
Claude Sonnet 5:63.2%
Qwen3.7 Max:60.6%
Claude Sonnet 5 source Qwen3.7 Max source
MMLU-Pro (Vals)Knowledge
Normalized gap 1.8
Claude Sonnet 5:87.5%
Qwen3.7 Max:89.3%
Claude Sonnet 5 source Qwen3.7 Max source

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 v5.7 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

Claude Sonnet 5: 64.6; Supported · #12/117
Qwen3.7 Max: 39.6; Supported · #57/117
Basis: BenchAlign v5.7 lane · 7 vs 10 public rows
Reading: Claude Sonnet 5 leads

Coding

Like-for-like

Claude Sonnet 5: 59.8; Supported · #19/142
Qwen3.7 Max: 45.7; Supported · #49/142
Basis: BenchAlign v5.7 lane · 11 vs 10 public rows
Reading: Claude Sonnet 5 leads · intervals overlap

Knowledge

Like-for-like

Claude Sonnet 5: 64.5; Supported · #26/168
Qwen3.7 Max: 60.8; Supported · #39/168
Basis: BenchAlign v5.7 lane · 6 vs 9 public rows
Reading: Claude Sonnet 5 leads · intervals overlap

Reasoning

Not comparable

Claude Sonnet 5: 78.7; Unranked · 2 rankable rows
Qwen3.7 Max: 76.3; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Claude Sonnet 5: 78.4; #15/50
Qwen3.7 Max: Not ranked
Basis: Provisional lane · 1 vs 0 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Claude Sonnet 5: Not ranked
Qwen3.7 Max: 100.0; #1/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Claude Sonnet 5: Not ranked
Qwen3.7 Max: 89.2; #17/124
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Sonnet 5: Not ranked
Qwen3.7 Max: 81.9; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Sonnet 5 and Qwen3.7 Max
Category	Claude Sonnet 5	Qwen3.7 Max	Basis	Reading
Agentic	64.6Supported · #12/117	39.6Supported · #57/117	Like-for-likeBenchAlign v5.7 lane · 7 vs 10 public rows	Claude Sonnet 5 leads
Coding	59.8Supported · #19/142	45.7Supported · #49/142	Like-for-likeBenchAlign v5.7 lane · 11 vs 10 public rows	Claude Sonnet 5 leads · intervals overlap
Knowledge	64.5Supported · #26/168	60.8Supported · #39/168	Like-for-likeBenchAlign v5.7 lane · 6 vs 9 public rows	Claude Sonnet 5 leads · intervals overlap
Reasoning	78.7Unranked · 2 rankable rows	76.3Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	78.4#15/50	Not ranked	Not comparableProvisional lane · 1 vs 0 weighted rows	Not comparable
Multilingual	Not ranked	100.0#1/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Instruction following	Not ranked	89.2#17/124	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	81.9Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) 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

Claude Sonnet 5: $0.007; Fits in one request
Qwen3.7 Max: API rate not published; Fits in one request

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

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 5: $0.13; Fits in one request
Qwen3.7 Max: API rate not published; Fits in one request

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

Cache-heavy agent loop

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

Claude Sonnet 5: $0.18; Fits in one request
Qwen3.7 Max: API rate not published; Fits in one request; Cached-input rate unavailable

Qwen3.7 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.

SpecificationClaude Sonnet 5Qwen3.7 Max

Context window

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

Claude Sonnet 5

Anthropic model overview

Qwen3.7 Max

API model ID

Claude Sonnet 5

claude-sonnet-5

Anthropic model overview

Qwen3.7 Max

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 5

$0.2 per 1M cached input tokens

Claude API pricing

Qwen3.7 Max

No comparable hosted API rate

Documented inputs

Claude Sonnet 5

text, image

Anthropic model overview

Qwen3.7 Max

Not sourced

Documented outputs

Claude Sonnet 5

text

Anthropic model overview

Qwen3.7 Max

Not sourced

Provider availability

Claude Sonnet 5

Generally Available · Claude API

Anthropic model overview

Qwen3.7 Max

Not sourced

Reasoning profile

Claude Sonnet 5

Reasoning

Qwen3.7 Max

Reasoning

Weight access

Claude Sonnet 5

Proprietary

Qwen3.7 Max

Proprietary

License

Claude Sonnet 5

Proprietary

Qwen3.7 Max

Proprietary

Release date

Claude Sonnet 5

2026-06-30

Qwen3.7 Max

2026-05-16

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: Claude Sonnet 5 has the higher public score estimate, 66.99 versus 63.32, 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.

Questions

Which is better, Claude Sonnet 5 or Qwen3.7 Max?

Claude Sonnet 5 has the higher public score estimate, 66.99 versus 63.32, 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 5 or Qwen3.7 Max?

Claude Sonnet 5 leads the public coding lane, 59.8 to 45.7, with Supported evidence for both models, although the 90% intervals overlap.

Which is better for agentic tasks, Claude Sonnet 5 or Qwen3.7 Max?

Claude Sonnet 5 leads the public agentic tasks lane, 64.6 to 39.6, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Claude Sonnet 5 or Qwen3.7 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, Claude Sonnet 5 or Qwen3.7 Max?

Both models list the same context window, 1M.

Benchmark evidence

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

Browse raw public benchmark evidence57 rows

Agentic

Terminal-Bench 3.0
Claude Sonnet 514.6%
Source
Qwen3.7 Max—
Not directly comparable
Terminal-Bench 2.1
Claude Sonnet 580.4%
Source
Qwen3.7 Max—
Not directly comparable
BrowseComp
Claude Sonnet 584.7%
Source
Qwen3.7 Max—
Not directly comparable
HLE w/ tools
Claude Sonnet 557.4%
Source
Qwen3.7 Max53.5%
Source
Claude Sonnet 5 leads this result
OSWorld-Verified
Claude Sonnet 581.2%
Source
Qwen3.7 Max—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Sonnet 574.5%
Source
Qwen3.7 Max61.0%
Source
Claude Sonnet 5 leads this result
ApprenticeBench
Claude Sonnet 516%
Source
Qwen3.7 Max—
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 5—
Qwen3.7 Max69.7%
Source
Not directly comparable
QwenClawBench
Claude Sonnet 5—
Qwen3.7 Max64.3%
Source
Not directly comparable
Claw-Eval
Claude Sonnet 5—
Qwen3.7 Max65.2%
Source
Not directly comparable
BFCL v4
Claude Sonnet 5—
Qwen3.7 Max75.0%
Source
Not directly comparable
MCP Atlas
Claude Sonnet 5—
Qwen3.7 Max76.4%
Source
Not directly comparable
VITA-Bench
Claude Sonnet 5—
Qwen3.7 Max47.9%
Source
Not directly comparable
Gert Labs
Claude Sonnet 5—
Qwen3.7 Max64.27%
Source
Not directly comparable
ResearchClawBench
Claude Sonnet 5—
Qwen3.7 Max18.7%
Source
Not directly comparable

Coding

SWE-bench Verified
Claude Sonnet 585.2%
Source
Qwen3.7 Max80.4%
Source
Claude Sonnet 5 leads this result
SWE-bench Pro
Claude Sonnet 563.2%
Source
Qwen3.7 Max60.6%
Source
Claude Sonnet 5 leads this result
SWE Multilingual
Claude Sonnet 578.3%
Source
Qwen3.7 Max78.3%
Source
Tie
SWE Multimodal
Claude Sonnet 528.1%
Source
Qwen3.7 Max—
Not directly comparable
Terminal-Bench 2.1
Claude Sonnet 580.4%
Source
Qwen3.7 Max—
Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 542.7%
Source
Qwen3.7 Max—
Not directly comparable
cursorBench32
Claude Sonnet 561.5%
Source
Qwen3.7 Max—
Not directly comparable
VulcanBench CII v1
Claude Sonnet 589.2%
Source
Qwen3.7 Max—
Not directly comparable
LiveCodeBench (Vals)
Claude Sonnet 582.4%
Source
Qwen3.7 Max87.1%
Source
Qwen3.7 Max leads this result
SWE-bench (Vals)
Claude Sonnet 579.6%
Source
Qwen3.7 Max68.8%
Source
Claude Sonnet 5 leads this result
cursorBench40
Claude Sonnet 534.1%
Source
Qwen3.7 Max—
Not directly comparable
NL2Repo
Claude Sonnet 5—
Qwen3.7 Max47.2%
Source
Not directly comparable
SciCode
Claude Sonnet 5—
Qwen3.7 Max53.5%
Source
Not directly comparable
LiveCodeBench
Claude Sonnet 5—
Qwen3.7 Max91.6%
Source
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 5—
Qwen3.7 Max69.7%
Source
Not directly comparable
OpenHarmony Bench
Claude Sonnet 5—
Qwen3.7 Max53.4%
Source
Not directly comparable

Reasoning

MRCRv2
Claude Sonnet 5—
Qwen3.7 Max90.4%
Source
Not directly comparable
CritPt
Claude Sonnet 5—
Qwen3.7 Max13.4%
Source
Not directly comparable

Multimodal

CharXiv
Claude Sonnet 588.3%
Source
Qwen3.7 Max—
Not directly comparable
CharXiv w/o tools
Claude Sonnet 577%
Source
Qwen3.7 Max—
Not directly comparable

Knowledge

HLE
Claude Sonnet 557.4%
Source
Qwen3.7 Max41.4%
Source
Claude Sonnet 5 leads this result
HLE w/o tools
Claude Sonnet 543.2%
Source
Qwen3.7 Max—
Not directly comparable
HLE-Verified
Claude Sonnet 531.0%
Source
Qwen3.7 Max—
Not directly comparable
LABBench2
Claude Sonnet 580.1%
Source
Qwen3.7 Max—
Not directly comparable
GPQA Diamond (Vals)
Claude Sonnet 588.9%
Source
Qwen3.7 Max90.2%
Source
Qwen3.7 Max leads this result
MMLU-Pro (Vals)
Claude Sonnet 587.5%
Source
Qwen3.7 Max89.3%
Source
Qwen3.7 Max leads this result
GPQA
Claude Sonnet 5—
Qwen3.7 Max92.4%
Source
Not directly comparable
GPQA-D
Claude Sonnet 5—
Qwen3.7 Max92.4%
Source
Not directly comparable
MMLU-Pro
Claude Sonnet 5—
Qwen3.7 Max89.6%
Source
Not directly comparable
MMLU-Redux
Claude Sonnet 5—
Qwen3.7 Max95%
Source
Not directly comparable
SuperGPQA
Claude Sonnet 5—
Qwen3.7 Max73.6%
Source
Not directly comparable
MMMLU
Claude Sonnet 5—
Qwen3.7 Max90.3%
Source
Not directly comparable

Multilingual

MMLU-ProX
Claude Sonnet 5—
Qwen3.7 Max87%
Source
Not directly comparable
NOVA-63
Claude Sonnet 5—
Qwen3.7 Max59.0%
Source
Not directly comparable
INCLUDE
Claude Sonnet 5—
Qwen3.7 Max86.2%
Source
Not directly comparable
MAXIFE
Claude Sonnet 5—
Qwen3.7 Max89.2%
Source
Not directly comparable
PolyMath
Claude Sonnet 5—
Qwen3.7 Max86.5%
Source
Not directly comparable

Instruction following

IFEval
Claude Sonnet 5—
Qwen3.7 Max94.3%
Source
Not directly comparable
IFBench
Claude Sonnet 5—
Qwen3.7 Max79.1%
Source
Not directly comparable

Math

HMMT Feb 2026
Claude Sonnet 5—
Qwen3.7 Max97.1%
Source
Not directly comparable
IMOAnswerBench
Claude Sonnet 5—
Qwen3.7 Max90.0%
Source
Not directly comparable
Apex
Claude Sonnet 5—
Qwen3.7 Max44.5%
Source
Not directly comparable

57 public results · 10 shared

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Last updated September 29, 2026

Claude Sonnet 5 vs Qwen3.7 Max

Decision reading

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Knowledge

Reasoning

Multimodal

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Claude Sonnet 5 or Qwen3.7 Max?

Which is better for coding, Claude Sonnet 5 or Qwen3.7 Max?

Which is better for agentic tasks, Claude Sonnet 5 or Qwen3.7 Max?

Which costs less, Claude Sonnet 5 or Qwen3.7 Max?

Which has the larger context window, Claude Sonnet 5 or Qwen3.7 Max?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Related comparisons

Watch Claude Sonnet 5 vs Qwen3.7 Max