Model A

Anthropic

64.8/100

Estimated · Public rank #37

90% interval 50.5–79.1

Claude Sonnet 5 vs Qwen3.5 397B

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

Model B

Qwen3.5 397B

Alibaba

57.5/100

Estimated · Public rank #82

90% interval 45.9–69.0

Decision reading

Claude Sonnet 5 has the higher public score estimate, 64.78 versus 57.46, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

6 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.

Coding work
Code generation, repair, and software-engineering tasks
Claude Sonnet 5
Claude Sonnet 5 leads on the same 2 weighted benchmark rows.
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
Chat turn cost
1K fresh input + 500 output tokens
Qwen3.5 397B
Qwen3.5 397B has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates

Show secondary and unsupported calls

Repository review cost
50K fresh input + 3K output tokens
Qwen3.5 397B
Qwen3.5 397B has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
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
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. Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback

What is actually comparable

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

13 Claude Sonnet 5 only

6 Shared

32 Qwen3.5 397B only

Shared results: 6
Claude Sonnet 5 only: 13
Qwen3.5 397B only: 32
Like-for-like categories: 1 / 8

3 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.

Coding

Like-for-like

Claude Sonnet 5: 76.7
Qwen3.5 397B: 66.5
Weighted basis: 2 vs 2 rows
Reading: Claude Sonnet 5 leads

Agentic

Directional only

Claude Sonnet 5: 81.9
Qwen3.5 397B: 56.5
Weighted basis: 3 vs 2 rows
Reading: Directional only

Knowledge

Directional only

Claude Sonnet 5: 57.4
Qwen3.5 397B: 56.6
Weighted basis: 1 vs 4 rows
Reading: Directional only

Multimodal

Directional only

Claude Sonnet 5: 88.3
Qwen3.5 397B: 79.6
Weighted basis: 1 vs 2 rows
Reading: Directional only

Reasoning

Not comparable

Claude Sonnet 5: Not measured
Qwen3.5 397B: 63.2
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Math

Not comparable

Claude Sonnet 5: Not measured
Qwen3.5 397B: 90.6
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Multilingual

Not comparable

Claude Sonnet 5: Not measured
Qwen3.5 397B: 84.7
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Instruction following

Not comparable

Claude Sonnet 5: Not measured
Qwen3.5 397B: 92.6
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Claude Sonnet 5 and Qwen3.5 397B
Category	Claude Sonnet 5	Qwen3.5 397B	Weighted basis	Reading
Coding	76.7	66.5	Like-for-like2 vs 2 rows	Claude Sonnet 5 leads
Agentic	81.9	56.5	Directional only3 vs 2 rows	Directional only
Knowledge	57.4	56.6	Directional only1 vs 4 rows	Directional only
Multimodal	88.3	79.6	Directional only1 vs 2 rows	Directional only
Reasoning	Not measured	63.2	Not comparable0 vs 1 rows	Not comparable
Math	Not measured	90.6	Not comparable0 vs 2 rows	Not comparable
Multilingual	Not measured	84.7	Not comparable0 vs 1 rows	Not comparable
Instruction following	Not measured	92.6	Not comparable0 vs 1 rows	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.

HLE
Knowledge
Claude Sonnet 5: 57.4%Qwen3.5 397B: 28.7%Normalized gap 28.7Claude Sonnet 5 source Qwen3.5 397B source
Terminal-Bench 2.0
Agentic
Claude Sonnet 5: 80.4%Qwen3.5 397B: 52.5%Normalized gap 27.9Claude Sonnet 5 source Qwen3.5 397B source
BrowseComp
Agentic
Claude Sonnet 5: 84.7%Qwen3.5 397B: 62%Normalized gap 22.7Claude Sonnet 5 source Qwen3.5 397B source
SWE-bench Pro
Coding
Claude Sonnet 5: 63.2%Qwen3.5 397B: 50.9%Normalized gap 12.3Claude Sonnet 5 source Qwen3.5 397B source
SWE-bench Verified
Coding
Claude Sonnet 5: 85.2%Qwen3.5 397B: 76.2%Normalized gap 9.0Claude Sonnet 5 source Qwen3.5 397B source

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
Qwen3.5 397B: $0.0024; Fits in one request

Qwen3.5 397B has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 5: $0.13; Fits in one request
Qwen3.5 397B: $0.0408; Fits in one request

Qwen3.5 397B has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Claude Sonnet 5: $0.18; Fits in one request
Qwen3.5 397B: $0.168; Does not fit in one request; Cached input priced at the published list-input rate

Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationClaude Sonnet 5Qwen3.5 397B

Context window

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

Claude Sonnet 5

Anthropic model overview

Qwen3.5 397B

128K

API model ID

Claude Sonnet 5

claude-sonnet-5

Anthropic model overview

Qwen3.5 397B

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

Qwen3.5 397B

Not published

Documented inputs

Claude Sonnet 5

text, image

Anthropic model overview

Qwen3.5 397B

Not sourced

Documented outputs

Claude Sonnet 5

text

Anthropic model overview

Qwen3.5 397B

Not sourced

Provider availability

Claude Sonnet 5

Generally Available · Claude API

Anthropic model overview

Qwen3.5 397B

Not sourced

Reasoning profile

Claude Sonnet 5

Reasoning

Qwen3.5 397B

Non-Reasoning

Weight access

Claude Sonnet 5

Proprietary

Qwen3.5 397B

Open Weight

License

Claude Sonnet 5

Proprietary

Qwen3.5 397B

Open Weight

Release date

Claude Sonnet 5

2026-06-30

Qwen3.5 397B

2026-02-16

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, 64.78 versus 57.46, but the 90% score intervals overlap.
Workload cost: Repository review: $0.13 vs $0.0408. Cache-heavy agent loop: $0.18 vs $0.168.
Context tradeoff: Claude Sonnet 5 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 evidence51 rows

Agentic

Terminal-Bench 3.0
Claude Sonnet 514.6%
Source
Qwen3.5 397B—
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%
Source
Qwen3.5 397B52.5%
Source
Claude Sonnet 5 leads this result
BrowseComp
Claude Sonnet 584.7%
Source
Qwen3.5 397B62%
Source
Claude Sonnet 5 leads this result
HLE w/ tools
Claude Sonnet 557.4%
Source
Qwen3.5 397B—
Not directly comparable
OSWorld-Verified
Claude Sonnet 581.2%
Source
Qwen3.5 397B—
Not directly comparable
Claw-Eval
Claude Sonnet 5—
Qwen3.5 397B56.8%
Source
Not directly comparable
QwenClawBench
Claude Sonnet 5—
Qwen3.5 397B51.8%
Source
Not directly comparable
τ³-bench results
Claude Sonnet 5—
Qwen3.5 397B68.4%
Source
Not directly comparable
VITA-Bench
Claude Sonnet 5—
Qwen3.5 397B43.7%
Source
Not directly comparable
DeepPlanning
Claude Sonnet 5—
Qwen3.5 397B37.6%
Source
Not directly comparable
Toolathlon
Claude Sonnet 5—
Qwen3.5 397B36.3%
Source
Not directly comparable
MCP Atlas
Claude Sonnet 5—
Qwen3.5 397B46.1%
Source
Not directly comparable
MCP-Tasks
Claude Sonnet 5—
Qwen3.5 397B74.2%
Source
Not directly comparable
WideResearch
Claude Sonnet 5—
Qwen3.5 397B74.0%
Source
Not directly comparable
Gert Labs
Claude Sonnet 5—
Qwen3.5 397B46.76%
Source
Not directly comparable
ResearchClawBench
Claude Sonnet 5—
Qwen3.5 397B14.2%
Source
Not directly comparable

Coding

SWE-bench Verified
Claude Sonnet 585.2%
Source
Qwen3.5 397B76.2%
Source
Claude Sonnet 5 leads this result
SWE-bench Pro
Claude Sonnet 563.2%
Source
Qwen3.5 397B50.9%
Source
Claude Sonnet 5 leads this result
SWE Multilingual
Claude Sonnet 578.3%
Source
Qwen3.5 397B—
Not directly comparable
SWE Multimodal
Claude Sonnet 528.1%
Source
Qwen3.5 397B—
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%
Source
Qwen3.5 397B—
Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 542.7%
Source
Qwen3.5 397B—
Not directly comparable
cursorBench32
Claude Sonnet 561.5%
Source
Qwen3.5 397B—
Not directly comparable
APEX-SWE
Claude Sonnet 546.4%
Source
Qwen3.5 397B—
Not directly comparable
EEBench
Claude Sonnet 540.3%
Source
Qwen3.5 397B—
Not directly comparable
3DCodeBench
Claude Sonnet 539.2%
Source
Qwen3.5 397B—
Not directly comparable
LiveCodeBench v6
Claude Sonnet 5—
Qwen3.5 397B83.6%
Source
Not directly comparable

Reasoning

LongBench v2
Claude Sonnet 5—
Qwen3.5 397B63.2%
Source
Not directly comparable
AI-Needle
Claude Sonnet 5—
Qwen3.5 397B68.7%
Source
Not directly comparable

Knowledge

HLE
Claude Sonnet 557.4%
Source
Qwen3.5 397B28.7%
Source
Claude Sonnet 5 leads this result
HLE w/o tools
Claude Sonnet 543.2%
Source
Qwen3.5 397B—
Not directly comparable
GPQA
Claude Sonnet 5—
Qwen3.5 397B88.4%
Source
Not directly comparable
SuperGPQA
Claude Sonnet 5—
Qwen3.5 397B70.4%
Source
Not directly comparable
MMLU-Pro
Claude Sonnet 5—
Qwen3.5 397B87.8%
Source
Not directly comparable
MMLU-Redux
Claude Sonnet 5—
Qwen3.5 397B94.9%
Source
Not directly comparable
C-Eval
Claude Sonnet 5—
Qwen3.5 397B93%
Source
Not directly comparable

Math

AIME26
Claude Sonnet 5—
Qwen3.5 397B93.3%
Source
Not directly comparable
HMMT Feb 2025
Claude Sonnet 5—
Qwen3.5 397B94.8%
Source
Not directly comparable
HMMT Nov 2025
Claude Sonnet 5—
Qwen3.5 397B92.7%
Source
Not directly comparable
HMMT Feb 2026
Claude Sonnet 5—
Qwen3.5 397B87.9%
Source
Not directly comparable
MMAnswerBench
Claude Sonnet 5—
Qwen3.5 397B80.9%
Source
Not directly comparable

Multilingual

MMLU-ProX
Claude Sonnet 5—
Qwen3.5 397B84.7%
Source
Not directly comparable
NOVA-63
Claude Sonnet 5—
Qwen3.5 397B59.1%
Source
Not directly comparable

Multimodal

CharXiv
Claude Sonnet 588.3%
Source
Qwen3.5 397B80.8%
Source
Claude Sonnet 5 leads this result
CharXiv w/o tools
Claude Sonnet 577%
Source
Qwen3.5 397B—
Not directly comparable
MMMU-Pro
Claude Sonnet 5—
Qwen3.5 397B79%
Source
Not directly comparable
MathVision
Claude Sonnet 5—
Qwen3.5 397B88.6%
Source
Not directly comparable
VideoMMMU
Claude Sonnet 5—
Qwen3.5 397B84.7%
Source
Not directly comparable
ScreenSpot Pro
Claude Sonnet 5—
Qwen3.5 397B65.6%
Source
Not directly comparable
V*
Claude Sonnet 5—
Qwen3.5 397B95.8%
Source
Not directly comparable

Instruction following

IFEval
Claude Sonnet 5—
Qwen3.5 397B92.6%
Source
Not directly comparable

Frequently asked questions

Which is better, Claude Sonnet 5 or Qwen3.5 397B?

Claude Sonnet 5 has the higher public score estimate, 64.78 versus 57.46, 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 Qwen3.5 397B?

Claude Sonnet 5 leads the like-for-like coding comparison across 2 shared weighted benchmark rows.

Which is better for agentic tasks, Claude Sonnet 5 or Qwen3.5 397B?

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, Claude Sonnet 5 or Qwen3.5 397B?

For the stated presets, chat costs $0.007 on Claude Sonnet 5 and $0.0024 on Qwen3.5 397B; repository review costs $0.13 and $0.0408; the cache-heavy agent loop costs $0.18 and $0.168. Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Sonnet 5 or Qwen3.5 397B?

Claude Sonnet 5 has the larger documented context window: 1M, compared with 128K.

Related comparisons

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Last updated August 14, 2026

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Claude Sonnet 5 vs Qwen3.5 397B

Which one for your work

Coding work

Long documents

Chat turn cost

Repository review cost

Agentic work

Cache-heavy agent loop cost

What is actually comparable

Category results, on a stated basis

Coding

Agentic

Knowledge

Multimodal

Reasoning

Math

Multilingual

Instruction following

Shape of the matched evidence

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

Benchmark evidence

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, Claude Sonnet 5 or Qwen3.5 397B?

Which is better for coding, Claude Sonnet 5 or Qwen3.5 397B?

Which is better for agentic tasks, Claude Sonnet 5 or Qwen3.5 397B?

Which costs less, Claude Sonnet 5 or Qwen3.5 397B?

Which has the larger context window, Claude Sonnet 5 or Qwen3.5 397B?

Related comparisons

Watch Claude Sonnet 5 vs Qwen3.5 397B