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BenchLM

Claude Sonnet 5 vs Qwen 3.6 Max (preview)

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.

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Decision reading

Claude Sonnet 5 has the higher public score estimate, 66.99 versus 54.98, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Anthropic logo

Anthropic

66.99/100

Supported · Public rank #23

90% interval 62.7–71.3

Model B
Alibaba logo

Alibaba

54.98/100

Estimated · Public rank #60

90% interval 45.8–64.2

Shared results
2
Claude Sonnet 5 only
24
Qwen 3.6 Max (preview) only
8
Like-for-like categories
1 / 8
Supported: Claude Sonnet 5 · Estimated: Qwen 3.6 Max (preview)How 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 46.9, with Supported evidence for both models, although the 90% intervals overlap.

    Confidence: limited
  • Long documents

    Prompts that approach the documented context limit

    Claude Sonnet 5

    Claude Sonnet 5 has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls
  • Agentic work

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

    Not enough matched evidence

    Qwen 3.6 Max (preview) is not ranked on the public lane for agentic, so no winner is named for agentic.

    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

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.

59.8Claude Sonnet 546.9Qwen 3.6 Max (preview)

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.

Same basis rules as the category table below

What is actually comparable

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

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.

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.

Coding

Like-for-like
Claude Sonnet 5
59.8
Supported · #19/142
Qwen 3.6 Max (preview)
46.9
Supported · #47/142
Basis
BenchAlign v5.7 lane · 11 vs 5 public rows
Reading
Claude Sonnet 5 leads · intervals overlap

Agentic

Not comparable
Claude Sonnet 5
64.6
Supported · #12/117
Qwen 3.6 Max (preview)
Not ranked
Basis
BenchAlign v5.7 lane · 7 vs 2 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Sonnet 5
78.7
Unranked · 2 rankable rows
Qwen 3.6 Max (preview)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Sonnet 5
78.4
#15/50
Qwen 3.6 Max (preview)
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Sonnet 5
64.5
Supported · #26/168
Qwen 3.6 Max (preview)
Not ranked
Basis
BenchAlign v5.7 lane · 6 vs 1 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 5
Not ranked
Qwen 3.6 Max (preview)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 5
Not ranked
Qwen 3.6 Max (preview)
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 5
Not ranked
Qwen 3.6 Max (preview)
41.3
Unranked · 2 rankable rows
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 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
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Qwen 3.6 Max (preview) has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 5
$0.13
Fits in one request
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Qwen 3.6 Max (preview) 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
Qwen 3.6 Max (preview)
API rate not published
Fits in one request
Cached-input rate unavailable

Qwen 3.6 Max (preview) 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.

Context window

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

Claude Sonnet 5

Qwen 3.6 Max (preview)

256K

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

Qwen 3.6 Max (preview)

No comparable hosted API rate

Provider availability

Claude Sonnet 5

Generally Available · Claude API

Anthropic model overview

Qwen 3.6 Max (preview)

Not sourced

Reasoning profile

Claude Sonnet 5

Reasoning

Qwen 3.6 Max (preview)

Reasoning

Weight access

Claude Sonnet 5

Proprietary

Qwen 3.6 Max (preview)

Proprietary

License

Claude Sonnet 5

Proprietary

Qwen 3.6 Max (preview)

Proprietary

Release date

Claude Sonnet 5

2026-06-30

Qwen 3.6 Max (preview)

2026-04-20

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 54.98, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Claude Sonnet 5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Sonnet 5 or Qwen 3.6 Max (preview)?

Claude Sonnet 5 has the higher public score estimate, 66.99 versus 54.98, 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 Qwen 3.6 Max (preview)?

Claude Sonnet 5 leads the public coding lane, 59.8 to 46.9, with Supported evidence for both models, although the 90% intervals overlap.

Which is better for agentic tasks, Claude Sonnet 5 or Qwen 3.6 Max (preview)?

Qwen 3.6 Max (preview) is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Sonnet 5 or Qwen 3.6 Max (preview)?

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 Qwen 3.6 Max (preview)?

Claude Sonnet 5 has the larger documented context window: 1M, compared with 256K.

Benchmark evidence

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

Browse raw public benchmark evidence34 rows

Agentic

  • Terminal-Bench 3.0

    Claude Sonnet 514.6%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 580.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • BrowseComp

    Claude Sonnet 584.7%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • HLE w/ tools

    Claude Sonnet 557.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • OSWorld-Verified

    Claude Sonnet 581.2%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Sonnet 574.5%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • ApprenticeBench

    Claude Sonnet 516%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)65.4%
    Source

    Not directly comparable

  • QwenClawBench

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)59.0%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Sonnet 585.2%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SWE-bench Pro

    Claude Sonnet 563.2%
    Source
    Qwen 3.6 Max (preview)57.3%
    Source

    Claude Sonnet 5 leads this result

  • SWE Multilingual

    Claude Sonnet 578.3%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SWE Multimodal

    Claude Sonnet 528.1%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 580.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Sonnet 542.7%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • cursorBench32

    Claude Sonnet 561.5%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • VulcanBench CII v1

    Claude Sonnet 589.2%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Sonnet 582.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SWE-bench (Vals)

    Claude Sonnet 579.6%
    Source
    Qwen 3.6 Max (preview)72.8%
    Source

    Claude Sonnet 5 leads this result

  • cursorBench40

    Claude Sonnet 534.1%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SciCode

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)47%
    Source

    Not directly comparable

  • NL2Repo

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)42.9%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)65.4%
    Source

    Not directly comparable

Multimodal

  • CharXiv

    Claude Sonnet 588.3%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • CharXiv w/o tools

    Claude Sonnet 577%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

Knowledge

  • HLE

    Claude Sonnet 557.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • HLE w/o tools

    Claude Sonnet 543.2%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • HLE-Verified

    Claude Sonnet 531.0%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • LABBench2

    Claude Sonnet 580.1%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Sonnet 588.9%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Sonnet 587.5%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SuperGPQA

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)73.9%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)23.103%
    Source

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Sonnet 5—
    Qwen 3.6 Max (preview)4.167%
    Source

    Not directly comparable

34 public results · 2 shared

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Last updated September 29, 2026