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BenchLM

Claude Opus 5.5 vs Laguna S 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.

4 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Anthropic logo
Model A
Claude Opus 5.5

Anthropic

81.03/100

Estimated · Public rank #5

90% interval 56.4–92.5

Poolside logo
Model B
Laguna S 2.1

Poolside

—

Evidence status unavailable

90% interval unavailable

Updated September 22, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Laguna S 2.1

    Laguna S 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 S 2.1

    Laguna S 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 S 2.1

    Laguna S 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

    Claude Opus 5.5 and Laguna S 2.1 are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Laguna S 2.1 is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

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.

76.0Claude Opus 5.545.4Laguna S 2.1

Directional only · BenchAlign

Claude Opus 5.5 scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job

What is actually comparable

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

Shared results
4
Claude Opus 5.5 only
44
Laguna S 2.1 only
2
Like-for-like categories
0 / 8

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Agentic

Directional only
Claude Opus 5.5
82.7
Supported · #1/156
Laguna S 2.1
46.0
Estimated · #87/156
Basis
BenchAlign lane · 11 vs 2 public rows
Reading
Directional only

Coding

Directional only
Claude Opus 5.5
76.0
Estimated · #4/159
Laguna S 2.1
45.4
Estimated · #94/159
Basis
BenchAlign lane · 9 vs 4 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Opus 5.5
78.5
#4/19
Laguna S 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 S 2.1
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 5.5
81.5
Estimated · #3/187
Laguna S 2.1
Not ranked
Basis
BenchAlign lane · 17 vs 0 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 5.5
Not ranked
Laguna S 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 S 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 S 2.1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
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.

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 S 2.1
$0.0002
Fits in one request

Laguna S 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 S 2.1
$0.0056
Fits in one request

Laguna S 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 S 2.1
$0.006
Fits in one request

Laguna S 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.

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 documentation

Laguna S 2.1

$0.01 per 1M cached input tokens

Reasoning profile

Claude Opus 5.5

Reasoning

Laguna S 2.1

Reasoning

Weight access

Claude Opus 5.5

Proprietary

Laguna S 2.1

Open Weight

License

Claude Opus 5.5

Proprietary

Laguna S 2.1

Open Weight

Release date

Claude Opus 5.5

2026-09-22

Laguna S 2.1

2026-07-21

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 $0.006.
Context tradeoff
Both models list 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%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Opus 5.558.7%
    Source
    Laguna S 2.1—

    Not directly comparable

  • AutomationBench

    Claude Opus 5.540.0%
    Source
    Laguna S 2.1—

    Not directly comparable

  • HLE w/ tools

    Claude Opus 5.567.7%
    Source
    Laguna S 2.1—

    Not directly comparable

  • OSWorld 2.0

    Claude Opus 5.548.7%
    Source
    Laguna S 2.1—

    Not directly comparable

  • LAB all-pass (Harvey held-out)

    Claude Opus 5.58.3%
    Source
    Laguna S 2.1—

    Not directly comparable

  • LAB criterion-pass (Harvey held-out)

    Claude Opus 5.591.2%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Toolathlon-Verified

    Claude Opus 5.577.8%
    Source
    Laguna S 2.149.7%
    Source

    Claude Opus 5.5 leads this result

  • Toolathlon Verified Pass@3

    Claude Opus 5.582.4%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Opus 5.572.2%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Opus 5.526.9 turns
    Source
    Laguna S 2.1—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 5.5—
    Laguna S 2.170.2%
    Source

    Not directly comparable

Coding

  • FrontierCode 1.1 Main

    Claude Opus 5.554.4%
    Source
    Laguna S 2.1—

    Not directly comparable

  • cursorBench40

    Claude Opus 5.557.8%
    Source
    Laguna S 2.1—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 5.589.9%
    Source
    Laguna S 2.159.4%
    Source

    Claude Opus 5.5 leads this result

  • SWE Multilingual

    Claude Opus 5.593.9%
    Source
    Laguna S 2.178.5%
    Source

    Claude Opus 5.5 leads this result

  • SWE Multimodal

    Claude Opus 5.561.4%
    Source
    Laguna S 2.1—

    Not directly comparable

  • DeepSWE

    Claude Opus 5.574.2%
    Source
    Laguna S 2.140.4%
    Source

    Claude Opus 5.5 leads this result

  • FrontierCode 1.1 Extended

    Claude Opus 5.563.6%
    Source
    Laguna S 2.1—

    Not directly comparable

  • FrontierSWE v2

    Claude Opus 5.562.3%
    Source
    Laguna S 2.1—

    Not directly comparable

  • ProgramBench

    Claude Opus 5.591.2%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 5.5—
    Laguna S 2.170.2%
    Source

    Not directly comparable

Multimodal

  • Chartography (tools)

    Claude Opus 5.589.0%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Chartography (no tools)

    Claude Opus 5.564.4%
    Source
    Laguna S 2.1—

    Not directly comparable

  • BenchCAD Vision2Code (no tools)

    Claude Opus 5.50.730
    Source
    Laguna S 2.1—

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    Claude Opus 5.50.962
    Source
    Laguna S 2.1—

    Not directly comparable

  • Biomedical image analysis

    Claude Opus 5.571.4%
    Source
    Laguna S 2.1—

    Not directly comparable

  • OfficeQA

    Claude Opus 5.578.9%
    Source
    Laguna S 2.1—

    Not directly comparable

  • OfficeQA Pro

    Claude Opus 5.567.7%
    Source
    Laguna S 2.1—

    Not directly comparable

Knowledge

  • HLE

    Claude Opus 5.567.7%
    Source
    Laguna S 2.1—

    Not directly comparable

  • HLE w/o tools

    Claude Opus 5.564.4%
    Source
    Laguna S 2.1—

    Not directly comparable

  • HealthBench (raw)

    Claude Opus 5.568.1%
    Source
    Laguna S 2.1—

    Not directly comparable

  • HealthBench (length-adjusted)

    Claude Opus 5.560.6%
    Source
    Laguna S 2.1—

    Not directly comparable

  • HealthBench Professional

    Claude Opus 5.565.6%
    Source
    Laguna S 2.1—

    Not directly comparable

  • HealthBench Professional (raw)

    Claude Opus 5.577.1%
    Source
    Laguna S 2.1—

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Claude Opus 5.589.3%
    Source
    Laguna S 2.1—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Claude Opus 5.550.0%
    Source
    Laguna S 2.1—

    Not directly comparable

  • SpatialBench Verified

    Claude Opus 5.572.0%
    Source
    Laguna S 2.1—

    Not directly comparable

  • SingleCellBench

    Claude Opus 5.561.2%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Morphology-to-molecule matching

    Claude Opus 5.534.0%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Medicinal chemistry

    Claude Opus 5.563.5%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Protein Design

    Claude Opus 5.560.2%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Protein Design library ranking

    Claude Opus 5.556.0%
    Source
    Laguna S 2.1—

    Not directly comparable

  • De novo protein-binder design

    Claude Opus 5.582.6%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Protocols (troubleshooting)

    Claude Opus 5.573.7%
    Source
    Laguna S 2.1—

    Not directly comparable

  • Protocols (understanding)

    Claude Opus 5.569.0%
    Source
    Laguna S 2.1—

    Not directly comparable

Multilingual

  • GMMLU

    Claude Opus 5.594.3%
    Source
    Laguna S 2.1—

    Not directly comparable

  • MILU

    Claude Opus 5.593.1%
    Source
    Laguna S 2.1—

    Not directly comparable

Math

  • ArXivMath Aug. 2026 (no tools)

    Claude Opus 5.591.2%
    Source
    Laguna S 2.1—

    Not directly comparable

  • ArXivMath Aug. 2026 (tools)

    Claude Opus 5.596.9%
    Source
    Laguna S 2.1—

    Not directly comparable

Questions

Which is better, Claude Opus 5.5 or Laguna S 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 S 2.1?

Claude Opus 5.5 scores higher for coding on the public lane, 76 to 45.4. Claude Opus 5.5 and Laguna S 2.1 are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude Opus 5.5 or Laguna S 2.1?

Claude Opus 5.5 scores higher for agentic tasks on the public lane, 82.7 to 46. Laguna S 2.1 is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Opus 5.5 or Laguna S 2.1?

For the stated presets, chat costs $0.014 on Claude Opus 5.5 and $0.0002 on Laguna S 2.1; repository review costs $0.26 and $0.0056; the cache-heavy agent loop costs $0.32 and $0.006. Costs use the listed standard API rates.

Which has the larger context window, Claude Opus 5.5 or Laguna S 2.1?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 22, 2026

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