Claude Opus 5 vs Qwen3.8-27B

Updated September 28, 2026. Rank says Claude Opus 5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Claude Opus 5 has the higher public score, 79.64 versus 55.26, and the 90% score intervals do not overlap. 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 Opus 5

Anthropic

79.64/100

Supported · Public rank #6

90% interval 76.1–83.2

Model B

Qwen3.8-27B

Alibaba

55.26/100

Estimated · Public rank #54

90% interval 47.7–62.8

Shared results: 10
Claude Opus 5 only: 65
Qwen3.8-27B only: 23
Like-for-like categories: 3 / 8

Supported: Claude Opus 5 · Estimated: Qwen3.8-27BHow 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 Opus 5
Claude Opus 5 leads on the public coding lane, 72.1 to 48.7, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Agentic work
Tool use, computer use, and multi-step task completion
Claude Opus 5
Claude Opus 5 leads on the public agentic lane, 77.7 to 61.2, with Supported evidence for both models and non-overlapping 90% intervals.
Confidence: stronger
Long documents
Prompts that approach the documented context limit
Claude Opus 5
Claude Opus 5 has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

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.

72.1Claude Opus 548.7Qwen3.8-27B

Like-for-like · BenchAlign v5.7

Claude Opus 5 leads the like-for-like coding row.

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 33.9
Claude Opus 5:64.7%
Qwen3.8-27B:30.8%
Claude Opus 5 source Qwen3.8-27B source
HLE w/o toolsKnowledge
Normalized gap 25.5
Claude Opus 5:56.3%
Qwen3.8-27B:30.8%
Claude Opus 5 source Qwen3.8-27B source
SWE-bench ProCoding
Normalized gap 17.5
Claude Opus 5:79.2%
Qwen3.8-27B:61.7%
Claude Opus 5 source Qwen3.8-27B source
MMLU-Pro (Vals)Knowledge
Normalized gap 7.3
Claude Opus 5:91.6%
Qwen3.8-27B:84.3%
Claude Opus 5 source Qwen3.8-27B source
LiveCodeBench (Vals)Coding
Normalized gap 5.0
Claude Opus 5:89.0%
Qwen3.8-27B:84.0%
Claude Opus 5 source Qwen3.8-27B 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 Opus 5: 77.7; Supported · #3/111
Qwen3.8-27B: 61.2; Supported · #16/111
Basis: BenchAlign v5.7 lane · 20 vs 8 public rows
Reading: Claude Opus 5 leads

Coding

Like-for-like

Claude Opus 5: 72.1; Supported · #6/136
Qwen3.8-27B: 48.7; Supported · #41/136
Basis: BenchAlign v5.7 lane · 17 vs 8 public rows
Reading: Claude Opus 5 leads

Knowledge

Like-for-like

Claude Opus 5: 81.3; Supported · #5/160
Qwen3.8-27B: 49.2; Supported · #59/160
Basis: BenchAlign v5.7 lane · 19 vs 6 public rows
Reading: Claude Opus 5 leads

Reasoning

Directional only

Claude Opus 5: 77.3; #9/27
Qwen3.8-27B: 78.7; #8/27
Basis: Provisional lane · 2 vs 0 weighted rows
Reading: Directional only

Multimodal

Directional only

Claude Opus 5: 88.8; #2/50
Qwen3.8-27B: 80.9; #11/50
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Directional only

Multilingual

Not comparable

Claude Opus 5: Not ranked
Qwen3.8-27B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Claude Opus 5: Not ranked
Qwen3.8-27B: 83.2; #45/124
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Opus 5: Not ranked
Qwen3.8-27B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Opus 5 and Qwen3.8-27B
Category	Claude Opus 5	Qwen3.8-27B	Basis	Reading
Agentic	77.7Supported · #3/111	61.2Supported · #16/111	Like-for-likeBenchAlign v5.7 lane · 20 vs 8 public rows	Claude Opus 5 leads
Coding	72.1Supported · #6/136	48.7Supported · #41/136	Like-for-likeBenchAlign v5.7 lane · 17 vs 8 public rows	Claude Opus 5 leads
Knowledge	81.3Supported · #5/160	49.2Supported · #59/160	Like-for-likeBenchAlign v5.7 lane · 19 vs 6 public rows	Claude Opus 5 leads
Reasoning	77.3#9/27	78.7#8/27	Directional onlyProvisional lane · 2 vs 0 weighted rows	Directional only
Multimodal	88.8#2/50	80.9#11/50	Directional onlyProvisional lane · 1 vs 1 weighted rows	Directional only
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	83.2#45/124	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 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 Opus 5: $0.0175; Fits in one request
Qwen3.8-27B: Self-hosted; infrastructure cost varies; Fits in one request

Qwen3.8-27B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 5: $0.325; Fits in one request
Qwen3.8-27B: Self-hosted; infrastructure cost varies; Fits in one request

Qwen3.8-27B has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Opus 5: $0.45; Fits in one request
Qwen3.8-27B: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable

Qwen3.8-27B 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 Opus 5Qwen3.8-27B

Context window

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

Claude Opus 5

Anthropic model overview

Qwen3.8-27B

262K

Qwen3.8-27B model card

API model ID

Claude Opus 5

claude-opus-5

Anthropic model overview

Qwen3.8-27B

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Opus 5

$0.5 per 1M cached input tokens

Claude API pricing

Qwen3.8-27B

No comparable hosted API rate

Qwen3.8-27B model card

Documented inputs

Claude Opus 5

text, image

Anthropic model overview

Qwen3.8-27B

Not sourced

Documented outputs

Claude Opus 5

text

Anthropic model overview

Qwen3.8-27B

Not sourced

Provider availability

Claude Opus 5

Generally Available · Claude API

Anthropic model overview

Qwen3.8-27B

Not sourced

Reasoning profile

Claude Opus 5

Reasoning

Qwen3.8-27B

Reasoning

Weight access

Claude Opus 5

Proprietary

Qwen3.8-27B

Open Weight

License

Claude Opus 5

Proprietary

Qwen3.8-27B

Open Weight

Release date

Claude Opus 5

2026-07-24

Qwen3.8-27B

2026-08-05

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 Opus 5 has the higher public score, 79.64 versus 55.26, and the 90% score intervals do not overlap.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Claude Opus 5 has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Opus 5 or Qwen3.8-27B?

Claude Opus 5 has the higher public score, 79.64 versus 55.26, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Claude Opus 5 or Qwen3.8-27B?

Claude Opus 5 leads the public coding lane, 72.1 to 48.7, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Claude Opus 5 or Qwen3.8-27B?

Claude Opus 5 leads the public agentic tasks lane, 77.7 to 61.2, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Claude Opus 5 or Qwen3.8-27B?

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 Opus 5 or Qwen3.8-27B?

Claude Opus 5 has the larger documented context window: 1M, compared with 262K.

Benchmark evidence

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

Browse raw public benchmark evidence98 rows

Agentic

Terminal-Bench 3.0
Claude Opus 542.7%
Source
Qwen3.8-27B—
Not directly comparable
BrowseComp
Claude Opus 590.8%
Source
Qwen3.8-27B—
Not directly comparable
HLE w/ tools
Claude Opus 564.7%
Source
Qwen3.8-27B—
Not directly comparable
DeepSearchQA
Claude Opus 595.0%
Source
Qwen3.8-27B—
Not directly comparable
DRACO
Claude Opus 588.6%
Source
Qwen3.8-27B—
Not directly comparable
BrowseComp (10-agent, prerelease)
Claude Opus 593.6%
Source
Qwen3.8-27B—
Not directly comparable
OSWorld 2.0
Claude Opus 570.6%
Source
Qwen3.8-27B—
Not directly comparable
MCP Atlas
Claude Opus 585.8%
Source
Qwen3.8-27B—
Not directly comparable
MCP-Atlas claim coverage
Claude Opus 589.1%
Source
Qwen3.8-27B—
Not directly comparable
LAB all-pass (Anthropic harness)
Claude Opus 523.58%
Source
Qwen3.8-27B—
Not directly comparable
LAB criterion-pass (Anthropic harness)
Claude Opus 593.74%
Source
Qwen3.8-27B—
Not directly comparable
LAB all-pass (Harvey held-out)
Claude Opus 511.7%
Source
Qwen3.8-27B—
Not directly comparable
LAB criterion-pass (Harvey held-out)
Claude Opus 594.1%
Source
Qwen3.8-27B—
Not directly comparable
Toolathlon-Verified
Claude Opus 580.6%
Source
Qwen3.8-27B—
Not directly comparable
Toolathlon Verified Pass@3
Claude Opus 587.0%
Source
Qwen3.8-27B—
Not directly comparable
Toolathlon Verified Pass³
Claude Opus 573.1%
Source
Qwen3.8-27B—
Not directly comparable
Toolathlon Verified avg. turns
Claude Opus 523.5 turns
Source
Qwen3.8-27B—
Not directly comparable
AutomationBench
Claude Opus 526.0%
Source
Qwen3.8-27B—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Opus 584.6%
Source
Qwen3.8-27B58.4%
Source
Claude Opus 5 leads this result
ApprenticeBench
Claude Opus 536%
Source
Qwen3.8-27B—
Not directly comparable
Terminal-Bench 2.1
Claude Opus 5—
Qwen3.8-27B73.0%
Source
Not directly comparable
CoWorkBench
Claude Opus 5—
Qwen3.8-27B70.7%
Source
Not directly comparable
JobBench
Claude Opus 5—
Qwen3.8-27B33.4%
Source
Not directly comparable
Agents' Last Exam
Claude Opus 5—
Qwen3.8-27B42.9%
Source
Not directly comparable
OSWorld-Verified
Claude Opus 5—
Qwen3.8-27B84.3%
Source
Not directly comparable
WebArena-Verified
Claude Opus 5—
Qwen3.8-27B64.8%
Source
Not directly comparable
AndroidWorld
Claude Opus 5—
Qwen3.8-27B81.9%
Source
Not directly comparable

Coding

Bug Hunt Bench
Claude Opus 527 fixes
Source
Qwen3.8-27B—
Not directly comparable
SWE-bench Verified
Claude Opus 596%
Source
Qwen3.8-27B—
Not directly comparable
SWE-bench Pro
Claude Opus 579.2%
Source
Qwen3.8-27B61.7%
Source
Claude Opus 5 leads this result
SWE Multilingual
Claude Opus 589.5%
Source
Qwen3.8-27B—
Not directly comparable
SWE Multimodal
Claude Opus 559.4%
Source
Qwen3.8-27B—
Not directly comparable
DeepSWE
Claude Opus 568.8%
Source
Qwen3.8-27B42.2%
Source
Claude Opus 5 leads this result
FrontierCode 1.1 Main
Claude Opus 553.4%
Source
Qwen3.8-27B—
Not directly comparable
FrontierCode 1.1 Extended
Claude Opus 563.6%
Source
Qwen3.8-27B—
Not directly comparable
FrontierSWE v2
Claude Opus 552.0%
Source
Qwen3.8-27B—
Not directly comparable
ProgramBench (episode 1)
Claude Opus 583.0%
Source
Qwen3.8-27B—
Not directly comparable
ProgramBench
Claude Opus 593.0%
Source
Qwen3.8-27B—
Not directly comparable
cursorBench32
Claude Opus 570.0%
Source
Qwen3.8-27B—
Not directly comparable
VulcanBench v3
Claude Opus 587.0%
Source
Qwen3.8-27B82.6%
Source
Claude Opus 5 leads this result
VulcanBench CII v1
Claude Opus 596.4%
Source
Qwen3.8-27B—
Not directly comparable
LiveCodeBench (Vals)
Claude Opus 589.0%
Source
Qwen3.8-27B84.0%
Source
Claude Opus 5 leads this result
SWE-bench (Vals)
Claude Opus 597.0%
Source
Qwen3.8-27B86.0%
Source
Claude Opus 5 leads this result
cursorBench40
Claude Opus 546.6%
Source
Qwen3.8-27B—
Not directly comparable
Terminal-Bench 2.1
Claude Opus 5—
Qwen3.8-27B73.0%
Source
Not directly comparable
NL2Repo
Claude Opus 5—
Qwen3.8-27B42.3%
Source
Not directly comparable
LiveCodeBench v6
Claude Opus 5—
Qwen3.8-27B90.3%
Source
Not directly comparable

Reasoning

ARC-AGI-1
Claude Opus 597.50%
Source
Qwen3.8-27B—
Not directly comparable
ARC-AGI-2
Claude Opus 590.4%
Source
Qwen3.8-27B—
Not directly comparable
ARC-AGI-3
Claude Opus 530.2%
Source
Qwen3.8-27B—
Not directly comparable

Multimodal

Chartography (no tools)
Claude Opus 529.6%
Source
Qwen3.8-27B—
Not directly comparable
Chartography (tools)
Claude Opus 583.0%
Source
Qwen3.8-27B—
Not directly comparable
BenchCAD Vision2Code (no tools)
Claude Opus 50.366
Source
Qwen3.8-27B—
Not directly comparable
BenchCAD Vision2Code (tools)
Claude Opus 50.821
Source
Qwen3.8-27B—
Not directly comparable
GDP.pdf (no tools)
Claude Opus 583.4%
Source
Qwen3.8-27B—
Not directly comparable
GDP.pdf (tools)
Claude Opus 585.5%
Source
Qwen3.8-27B—
Not directly comparable
OfficeQA
Claude Opus 578.1%
Source
Qwen3.8-27B—
Not directly comparable
OfficeQA Pro
Claude Opus 566.9%
Source
Qwen3.8-27B—
Not directly comparable
MathVision
Claude Opus 5—
Qwen3.8-27B90.0%
Source
Not directly comparable
MathVision w/ Python
Claude Opus 5—
Qwen3.8-27B94.6%
Source
Not directly comparable
BabyVision
Claude Opus 5—
Qwen3.8-27B65.7%
Source
Not directly comparable
BabyVision w/ Python
Claude Opus 5—
Qwen3.8-27B85.6%
Source
Not directly comparable
Vision2Web
Claude Opus 5—
Qwen3.8-27B62.9%
Source
Not directly comparable
CharXiv w/o tools
Claude Opus 5—
Qwen3.8-27B83.7%
Source
Not directly comparable
CharXiv
Claude Opus 5—
Qwen3.8-27B90.2%
Source
Not directly comparable
OmniDocBench 1.5
Claude Opus 5—
Qwen3.8-27B91.1%
Source
Not directly comparable
RealWorldQA
Claude Opus 5—
Qwen3.8-27B85.9%
Source
Not directly comparable
ERQA
Claude Opus 5—
Qwen3.8-27B65.5%
Source
Not directly comparable

Knowledge

HLE
Claude Opus 564.7%
Source
Qwen3.8-27B30.8%
Source
Claude Opus 5 leads this result
HLE w/o tools
Claude Opus 556.3%
Source
Qwen3.8-27B30.8%
Source
Claude Opus 5 leads this result
HLE-Verified
Claude Opus 554.4%
Source
Qwen3.8-27B—
Not directly comparable
LABBench2
Claude Opus 584.2%
Source
Qwen3.8-27B—
Not directly comparable
HealthBench (raw)
Claude Opus 567.1%
Source
Qwen3.8-27B—
Not directly comparable
HealthBench (length-adjusted)
Claude Opus 557.8%
Source
Qwen3.8-27B—
Not directly comparable
HealthBench Professional
Claude Opus 559.8%
Source
Qwen3.8-27B—
Not directly comparable
HealthBench Professional (raw)
Claude Opus 573.4%
Source
Qwen3.8-27B—
Not directly comparable
BioMysteryBench (human-solvable)
Claude Opus 590.1%
Source
Qwen3.8-27B—
Not directly comparable
BioMysteryBench (human-difficult)
Claude Opus 549.4%
Source
Qwen3.8-27B—
Not directly comparable
SpatialBench Verified
Claude Opus 572.5%
Source
Qwen3.8-27B—
Not directly comparable
SingleCellBench
Claude Opus 560.6%
Source
Qwen3.8-27B—
Not directly comparable
ProteinGym Hard
Claude Opus 547.7%
Source
Qwen3.8-27B—
Not directly comparable
Protein Design
Claude Opus 542.5%
Source
Qwen3.8-27B—
Not directly comparable
Organic chemistry V2
Claude Opus 561.6%
Source
Qwen3.8-27B—
Not directly comparable
Protocols (troubleshooting)
Claude Opus 561.1%
Source
Qwen3.8-27B—
Not directly comparable
Protocols (understanding)
Claude Opus 578.4%
Source
Qwen3.8-27B—
Not directly comparable
GPQA Diamond (Vals)
Claude Opus 593.4%
Source
Qwen3.8-27B88.9%
Source
Claude Opus 5 leads this result
MMLU-Pro (Vals)
Claude Opus 591.6%
Source
Qwen3.8-27B84.3%
Source
Claude Opus 5 leads this result
GPQA
Claude Opus 5—
Qwen3.8-27B89.2%
Source
Not directly comparable
GPQA-D
Claude Opus 5—
Qwen3.8-27B89.2%
Source
Not directly comparable

Multilingual

GMMLU
Claude Opus 592.5%
Source
Qwen3.8-27B—
Not directly comparable
MILU
Claude Opus 592.1%
Source
Qwen3.8-27B—
Not directly comparable
INCLUDE
Claude Opus 589.8%
Source
Qwen3.8-27B—
Not directly comparable

Instruction following

IFBench
Claude Opus 5—
Qwen3.8-27B79.5%
Source
Not directly comparable

Math

IMO 2026
Claude Opus 542/42
Source
Qwen3.8-27B—
Not directly comparable
RiemannBench (no tools)
Claude Opus 560.0%
Source
Qwen3.8-27B—
Not directly comparable
RiemannBench (tools)
Claude Opus 579.0%
Source
Qwen3.8-27B—
Not directly comparable
ArXivMath Jun. 2026 (no tools)
Claude Opus 590.8%
Source
Qwen3.8-27B—
Not directly comparable
ArXivMath Jun. 2026 (tools)
Claude Opus 591.3%
Source
Qwen3.8-27B—
Not directly comparable

98 public results · 10 shared

Related comparisons

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Last updated September 28, 2026

Claude Opus 5 vs Qwen3.8-27B

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 Opus 5 or Qwen3.8-27B?

Which is better for coding, Claude Opus 5 or Qwen3.8-27B?

Which is better for agentic tasks, Claude Opus 5 or Qwen3.8-27B?

Which costs less, Claude Opus 5 or Qwen3.8-27B?

Which has the larger context window, Claude Opus 5 or Qwen3.8-27B?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Related comparisons

Watch Claude Opus 5 vs Qwen3.8-27B