Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Qwen4 27B is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Claude Opus 5.5 vs Qwen4 27B
Updated September 23, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 0
- Claude Opus 5.5 only
- 47
- Qwen4 27B only
- 0
- Like-for-like categories
- 0 / 8
Estimated: Claude Opus 5.5How 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.
No workload recommendation clears the current evidence threshold.
Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Qwen4 27B is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedLong documents
Prompts that approach the documented context limit
Not enough matched evidence
A complete context comparison is not sourced.
Confidence: limitedChat 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-ratesCache-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-ratesRepository 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.
87.1Claude Opus 5.5—Qwen4 27B
Not comparable · BenchAlign v5.6
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
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.
47 Claude Opus 5.5 only
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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.6 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
Not comparable- Claude Opus 5.5
- 88.8
- Supported · #1/105
- Qwen4 27B
- Not ranked
- Basis
- BenchAlign v5.6 lane · 11 vs 0 public rows
- Reading
- Not comparable
Coding
Not comparable- Claude Opus 5.5
- 87.1
- Supported · #1/135
- Qwen4 27B
- Not ranked
- Basis
- BenchAlign v5.6 lane · 9 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 5.5
- 78.5
- #4/18
- Qwen4 27B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 5.5
- 88.8
- #3/50
- Qwen4 27B
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Opus 5.5
- 90.0
- Supported · #1/160
- Qwen4 27B
- Not ranked
- Basis
- BenchAlign v5.6 lane · 16 vs 0 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 5.5
- Not ranked
- Qwen4 27B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 5.5
- Not ranked
- Qwen4 27B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 5.5
- Not ranked
- Qwen4 27B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 5.5 | Qwen4 27B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 88.8Supported · #1/105 | Not ranked | Not comparableBenchAlign v5.6 lane · 11 vs 0 public rows | Not comparable |
| Coding | 87.1Supported · #1/135 | Not ranked | Not comparableBenchAlign v5.6 lane · 9 vs 0 public rows | Not comparable |
| Reasoning | 78.5#4/18 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 88.8#3/50 | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Knowledge | 90.0Supported · #1/160 | Not ranked | Not comparableBenchAlign v5.6 lane · 16 vs 0 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 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 v5.6) 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 5.5
- $0.014
- Fits in one request
- Qwen4 27B
- API rate not published
- Fit state unavailable
Qwen4 27B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 5.5
- $0.26
- Fits in one request
- Qwen4 27B
- API rate not published
- Fit state unavailable
Qwen4 27B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Opus 5.5
- $0.32
- Fits in one request
- Qwen4 27B
- API rate not published
- Fit state unavailable
- Cached-input rate unavailable
Qwen4 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 5.5Qwen4 27B
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 5.5
Qwen4 27B
Not sourced
API model ID
Claude Opus 5.5
claude-opus-5-5
Anthropic Claude Opus 5.5 model documentationQwen4 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 5.5
$0.2 per 1M cached input tokens
Claude Opus 5.5 model documentationQwen4 27B
No comparable hosted API rate
Alibaba Cloud Apsara ConferenceDocumented inputs
Claude Opus 5.5
Qwen4 27B
Not sourced
Documented outputs
Claude Opus 5.5
Qwen4 27B
Not sourced
Provider availability
Claude Opus 5.5
Generally Available · Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Claude Platform on AWS
Anthropic Claude Opus 5.5 model documentationQwen4 27B
Not sourced
Reasoning profile
Claude Opus 5.5
Reasoning
Qwen4 27B
Pending
Weight access
Claude Opus 5.5
Proprietary
Qwen4 27B
Pending
License
Claude Opus 5.5
Proprietary
Qwen4 27B
Pending
Release date
Claude Opus 5.5
2026-09-22
Qwen4 27B
Not sourced
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
- The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- A complete documented context comparison is not available.
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Opus 5.5 or Qwen4 27B?
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Opus 5.5 or Qwen4 27B?
Qwen4 27B is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Opus 5.5 or Qwen4 27B?
Qwen4 27B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Opus 5.5 or Qwen4 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 5.5 or Qwen4 27B?
A complete documented context-window comparison is not available.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence47 rows
Agentic
Terminal-Bench 4.0
Claude Opus 5.566.40%SourceQwen4 27B—Not directly comparable
Terminal-Bench-Science 0.1
Claude Opus 5.558.7%SourceQwen4 27B—Not directly comparable
AutomationBench
Claude Opus 5.540.0%SourceQwen4 27B—Not directly comparable
HLE w/ tools
Claude Opus 5.567.7%SourceQwen4 27B—Not directly comparable
OSWorld 2.0
Claude Opus 5.548.7%SourceQwen4 27B—Not directly comparable
LAB all-pass (Harvey held-out)
Claude Opus 5.58.3%SourceQwen4 27B—Not directly comparable
LAB criterion-pass (Harvey held-out)
Claude Opus 5.591.2%SourceQwen4 27B—Not directly comparable
Toolathlon-Verified
Claude Opus 5.577.8%SourceQwen4 27B—Not directly comparable
Toolathlon Verified Pass@3
Claude Opus 5.582.4%SourceQwen4 27B—Not directly comparable
Toolathlon Verified Pass³
Claude Opus 5.572.2%SourceQwen4 27B—Not directly comparable
Toolathlon Verified avg. turns
Claude Opus 5.526.9 turnsSourceQwen4 27B—Not directly comparable
Coding
FrontierCode 1.1 Main
Claude Opus 5.554.4%SourceQwen4 27B—Not directly comparable
cursorBench40
Claude Opus 5.557.8%SourceQwen4 27B—Not directly comparable
SWE-bench Pro
Claude Opus 5.589.9%SourceQwen4 27B—Not directly comparable
SWE Multilingual
Claude Opus 5.593.9%SourceQwen4 27B—Not directly comparable
SWE Multimodal
Claude Opus 5.561.4%SourceQwen4 27B—Not directly comparable
DeepSWE
Claude Opus 5.574.2%SourceQwen4 27B—Not directly comparable
FrontierCode 1.1 Extended
Claude Opus 5.563.6%SourceQwen4 27B—Not directly comparable
FrontierSWE v2
Claude Opus 5.562.3%SourceQwen4 27B—Not directly comparable
ProgramBench
Claude Opus 5.591.2%SourceQwen4 27B—Not directly comparable
Multimodal
Chartography (tools)
Claude Opus 5.589.0%SourceQwen4 27B—Not directly comparable
Chartography (no tools)
Claude Opus 5.564.4%SourceQwen4 27B—Not directly comparable
BenchCAD Vision2Code (no tools)
Claude Opus 5.50.730SourceQwen4 27B—Not directly comparable
BenchCAD Vision2Code (tools)
Claude Opus 5.50.962SourceQwen4 27B—Not directly comparable
Biomedical image analysis
Claude Opus 5.571.4%SourceQwen4 27B—Not directly comparable
OfficeQA
Claude Opus 5.578.9%SourceQwen4 27B—Not directly comparable
OfficeQA Pro
Claude Opus 5.567.7%SourceQwen4 27B—Not directly comparable
Knowledge
HLE w/o tools
Claude Opus 5.564.4%SourceQwen4 27B—Not directly comparable
HealthBench (raw)
Claude Opus 5.568.1%SourceQwen4 27B—Not directly comparable
HealthBench (length-adjusted)
Claude Opus 5.560.6%SourceQwen4 27B—Not directly comparable
HealthBench Professional
Claude Opus 5.565.6%SourceQwen4 27B—Not directly comparable
HealthBench Professional (raw)
Claude Opus 5.577.1%SourceQwen4 27B—Not directly comparable
BioMysteryBench (human-solvable)
Claude Opus 5.589.3%SourceQwen4 27B—Not directly comparable
BioMysteryBench (human-difficult)
Claude Opus 5.550.0%SourceQwen4 27B—Not directly comparable
SpatialBench Verified
Claude Opus 5.572.0%SourceQwen4 27B—Not directly comparable
SingleCellBench
Claude Opus 5.561.2%SourceQwen4 27B—Not directly comparable
Morphology-to-molecule matching
Claude Opus 5.534.0%SourceQwen4 27B—Not directly comparable
Medicinal chemistry
Claude Opus 5.563.5%SourceQwen4 27B—Not directly comparable
Protein Design
Claude Opus 5.560.2%SourceQwen4 27B—Not directly comparable
Protein Design library ranking
Claude Opus 5.556.0%SourceQwen4 27B—Not directly comparable
De novo protein-binder design
Claude Opus 5.582.6%SourceQwen4 27B—Not directly comparable
Protocols (troubleshooting)
Claude Opus 5.573.7%SourceQwen4 27B—Not directly comparable
Protocols (understanding)
Claude Opus 5.569.0%SourceQwen4 27B—Not directly comparable
Multilingual
Math
47 public results · 0 shared
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Last updated September 23, 2026