Agentic
Not comparable- Claude Opus 5.5
- 82.9
- Supported · #1/157
- Laguna XS 2.1
- Not ranked
- Basis
- BenchAlign lane · 11 vs 1 public rows
- Reading
- Not comparable
Claude Opus 5.5 vs Laguna XS 2.1
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Updated September 22, 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
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.
Long documents
Prompts that approach the documented context limit
Claude Opus 5.5
Claude Opus 5.5 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Laguna XS 2.1
Laguna XS 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Laguna XS 2.1
Laguna XS 2.1 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
Laguna XS 2.1
Laguna XS 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Laguna XS 2.1 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Laguna XS 2.1 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
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.
80.1Claude Opus 5.5—Laguna XS 2.1
Not comparable · BenchAlign
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.
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
45 Claude Opus 5.5 only
2 Shared
3 Laguna XS 2.1 only
- Shared results
- 2
- Claude Opus 5.5 only
- 45
- Laguna XS 2.1 only
- 3
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign 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
Not comparable- Claude Opus 5.5
- 80.1
- Supported · #2/159
- Laguna XS 2.1
- Not ranked
- Basis
- BenchAlign lane · 9 vs 4 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Opus 5.5
- 78.5
- #4/17
- Laguna XS 2.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Opus 5.5
- 88.8
- #3/50
- Laguna XS 2.1
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Opus 5.5
- 81.8
- Estimated · #4/189
- Laguna XS 2.1
- Not ranked
- Basis
- BenchAlign lane · 16 vs 0 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 5.5
- Not ranked
- Laguna XS 2.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 5.5
- Not ranked
- Laguna XS 2.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 5.5
- Not ranked
- Laguna XS 2.1
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 5.5 | Laguna XS 2.1 | Basis | Reading |
|---|---|---|---|---|
| Agentic | 82.9Supported · #1/157 | Not ranked | Not comparableBenchAlign lane · 11 vs 1 public rows | Not comparable |
| Coding | 80.1Supported · #2/159 | Not ranked | Not comparableBenchAlign lane · 9 vs 4 public rows | Not comparable |
| Reasoning | 78.5#4/17 | 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 | 81.8Estimated · #4/189 | Not ranked | Not comparableBenchAlign 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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
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.
SWE-bench Pro
Coding
Claude Opus 5.5: 89.9%Laguna XS 2.1: 47.6%Normalized gap 42.3Claude Opus 5.5 source Laguna XS 2.1 sourceSWE Multilingual
Coding
Claude Opus 5.5: 93.9%Laguna XS 2.1: 63.1%Normalized gap 30.8Claude Opus 5.5 source Laguna XS 2.1 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 Opus 5.5
- $0.014
- Fits in one request
- Laguna XS 2.1
- $0.0002
- Fits in one request
Laguna XS 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Opus 5.5
- $0.26
- Fits in one request
- Laguna XS 2.1
- $0.0056
- Fits in one request
Laguna XS 2.1 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 Opus 5.5
- $0.32
- Fits in one request
- Laguna XS 2.1
- $0.014
- Fits in one request
Laguna XS 2.1 has the lower modeled cost
Costs use the listed standard API rates.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 5.5Laguna XS 2.1
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 5.5
Laguna XS 2.1
API model ID
Claude Opus 5.5
claude-opus-5-5
Anthropic Claude Opus 5.5 model documentationLaguna XS 2.1
poolside/Laguna-XS-2.1
Poolside Laguna XS 2.1 launch postCached-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 documentationLaguna XS 2.1
$0.05 per 1M cached input tokens
Poolside Laguna XS 2.1 launch postDocumented inputs
Claude Opus 5.5
Laguna XS 2.1
Not sourced
Documented outputs
Claude Opus 5.5
Laguna XS 2.1
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 documentationLaguna XS 2.1
Not sourced
Reasoning profile
Claude Opus 5.5
Reasoning
Laguna XS 2.1
Reasoning
Weight access
Claude Opus 5.5
Proprietary
Laguna XS 2.1
Open Weight
License
Claude Opus 5.5
Proprietary
Laguna XS 2.1
Open Weight
Release date
Claude Opus 5.5
2026-09-22
Laguna XS 2.1
2026-07-02
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
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- Repository review: $0.26 vs $0.0056. Cache-heavy agent loop: $0.32 vs $0.014.
- Context tradeoff
- Claude Opus 5.5 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 evidence50 rows
Agentic
Terminal-Bench 4.0
Claude Opus 5.566.40%SourceLaguna XS 2.1—Not directly comparable
Terminal-Bench-Science 0.1
Claude Opus 5.558.7%SourceLaguna XS 2.1—Not directly comparable
AutomationBench
Claude Opus 5.540.0%SourceLaguna XS 2.1—Not directly comparable
HLE w/ tools
Claude Opus 5.567.7%SourceLaguna XS 2.1—Not directly comparable
OSWorld 2.0
Claude Opus 5.548.7%SourceLaguna XS 2.1—Not directly comparable
LAB all-pass (Harvey held-out)
Claude Opus 5.58.3%SourceLaguna XS 2.1—Not directly comparable
LAB criterion-pass (Harvey held-out)
Claude Opus 5.591.2%SourceLaguna XS 2.1—Not directly comparable
Toolathlon-Verified
Claude Opus 5.577.8%SourceLaguna XS 2.1—Not directly comparable
Toolathlon Verified Pass@3
Claude Opus 5.582.4%SourceLaguna XS 2.1—Not directly comparable
Toolathlon Verified Pass³
Claude Opus 5.572.2%SourceLaguna XS 2.1—Not directly comparable
Toolathlon Verified avg. turns
Claude Opus 5.526.9 turnsSourceLaguna XS 2.1—Not directly comparable
Terminal-Bench 2.0
Claude Opus 5.5—Laguna XS 2.137.5%SourceNot directly comparable
Coding
FrontierCode 1.1 Main
Claude Opus 5.554.4%SourceLaguna XS 2.1—Not directly comparable
cursorBench40
Claude Opus 5.557.8%SourceLaguna XS 2.1—Not directly comparable
SWE-bench Pro
Claude Opus 5.589.9%SourceLaguna XS 2.147.6%SourceClaude Opus 5.5 leads this result
SWE Multilingual
Claude Opus 5.593.9%SourceLaguna XS 2.163.1%SourceClaude Opus 5.5 leads this result
SWE Multimodal
Claude Opus 5.561.4%SourceLaguna XS 2.1—Not directly comparable
DeepSWE
Claude Opus 5.574.2%SourceLaguna XS 2.1—Not directly comparable
FrontierCode 1.1 Extended
Claude Opus 5.563.6%SourceLaguna XS 2.1—Not directly comparable
FrontierSWE v2
Claude Opus 5.562.3%SourceLaguna XS 2.1—Not directly comparable
ProgramBench
Claude Opus 5.591.2%SourceLaguna XS 2.1—Not directly comparable
SWE-bench Verified
Claude Opus 5.5—Laguna XS 2.170.9%SourceNot directly comparable
Terminal-Bench 2.0
Claude Opus 5.5—Laguna XS 2.137.5%SourceNot directly comparable
Multimodal
Chartography (tools)
Claude Opus 5.589.0%SourceLaguna XS 2.1—Not directly comparable
Chartography (no tools)
Claude Opus 5.564.4%SourceLaguna XS 2.1—Not directly comparable
BenchCAD Vision2Code (no tools)
Claude Opus 5.50.730SourceLaguna XS 2.1—Not directly comparable
BenchCAD Vision2Code (tools)
Claude Opus 5.50.962SourceLaguna XS 2.1—Not directly comparable
Biomedical image analysis
Claude Opus 5.571.4%SourceLaguna XS 2.1—Not directly comparable
OfficeQA
Claude Opus 5.578.9%SourceLaguna XS 2.1—Not directly comparable
OfficeQA Pro
Claude Opus 5.567.7%SourceLaguna XS 2.1—Not directly comparable
Knowledge
HLE w/o tools
Claude Opus 5.564.4%SourceLaguna XS 2.1—Not directly comparable
HealthBench (raw)
Claude Opus 5.568.1%SourceLaguna XS 2.1—Not directly comparable
HealthBench (length-adjusted)
Claude Opus 5.560.6%SourceLaguna XS 2.1—Not directly comparable
HealthBench Professional
Claude Opus 5.565.6%SourceLaguna XS 2.1—Not directly comparable
HealthBench Professional (raw)
Claude Opus 5.577.1%SourceLaguna XS 2.1—Not directly comparable
BioMysteryBench (human-solvable)
Claude Opus 5.589.3%SourceLaguna XS 2.1—Not directly comparable
BioMysteryBench (human-difficult)
Claude Opus 5.550.0%SourceLaguna XS 2.1—Not directly comparable
SpatialBench Verified
Claude Opus 5.572.0%SourceLaguna XS 2.1—Not directly comparable
SingleCellBench
Claude Opus 5.561.2%SourceLaguna XS 2.1—Not directly comparable
Morphology-to-molecule matching
Claude Opus 5.534.0%SourceLaguna XS 2.1—Not directly comparable
Medicinal chemistry
Claude Opus 5.563.5%SourceLaguna XS 2.1—Not directly comparable
Protein Design
Claude Opus 5.560.2%SourceLaguna XS 2.1—Not directly comparable
Protein Design library ranking
Claude Opus 5.556.0%SourceLaguna XS 2.1—Not directly comparable
De novo protein-binder design
Claude Opus 5.582.6%SourceLaguna XS 2.1—Not directly comparable
Protocols (troubleshooting)
Claude Opus 5.573.7%SourceLaguna XS 2.1—Not directly comparable
Protocols (understanding)
Claude Opus 5.569.0%SourceLaguna XS 2.1—Not directly comparable
Multilingual
Math
Questions
Which is better, Claude Opus 5.5 or Laguna XS 2.1?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Opus 5.5 or Laguna XS 2.1?
Laguna XS 2.1 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 Laguna XS 2.1?
Laguna XS 2.1 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 Laguna XS 2.1?
For the stated presets, chat costs $0.014 on Claude Opus 5.5 and $0.0002 on Laguna XS 2.1; repository review costs $0.26 and $0.0056; the cache-heavy agent loop costs $0.32 and $0.014. Costs use the listed standard API rates.
Which has the larger context window, Claude Opus 5.5 or Laguna XS 2.1?
Claude Opus 5.5 has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 22, 2026
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