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Data as of October 6, 2026 · How the score is built

CurrentProprietaryReasoning

Released Sep 28, 20261M context

Claude Sonnet 5.5

Decision readingClaude Sonnet 5.5 scores 83.9 out of 100 and ranks #3 of 214. This profile shows 47 source-displayable benchmark rows; its strongest eligible category is Coding at #1. API pricing is $2 input and $10 output per million tokens, with cached input at $0.2.

Released Sep 28, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

83.9/100

field median 52#3 of 214 ranked models

Public

#3of 214

Verified #3 of 83

Price

$2input / $10 output

input median $0.95cached $0.20 · batch + cache $0.10 · blended $6

Speed

128tok/s

field median 98 tok/sFirst token 441.91 s

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Coding ranks #1. Particularly well-suited for software development and code generation tasks.

Validate before choosing

47 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #10.

Source-linked · 47 displayable benchmark rows

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Check the published record for the model and serving route you use.

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Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #10 of 120Percentile 92ndWeight 22%11 benchmarksVerified
68.1
CodingRank #1 of 144Percentile 100thWeight 20%9 benchmarksVerified
85.1
ReasoningWeight 17%0 benchmarksNot measured
Not measured
MultimodalRank Not rankedWeight 12%7 benchmarksVerified
83.3
KnowledgeRank #5 of 173Percentile 98thWeight 12%16 benchmarksVerified
81.5
MultilingualWeight 7%2 benchmarksVerified
Score pending
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathWeight 5%2 benchmarksVerified
Score pending

47 of 655 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic11/11 verified
  2. Coding9/9 verified
  3. ReasoningNot measured
  4. Multimodal7/7 verified
  5. Knowledge16/16 verified
  6. Multilingual2/2 verified
  7. Inst. FollowingNot measured
  8. Math2/2 verified
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Claude Sonnet 5.5 category percentile values

  • Agentic92nd percentile
  • Coding100th percentile
  • ReasoningNot eligible
  • MultimodalNot eligible
  • Knowledge98th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#10/120
  2. Coding#1/144
  3. ReasoningNot ranked
  4. MultimodalNot ranked
  5. Knowledge#5/173
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding9 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore81.3%Versus best verified row

Best verified: Claude Opus 5.5 · 89.9%

Gap8.6 behindWeight26% ref. weight
DeepSWEScore71.0%Versus best verified row

Best verified: Gemini 4 Argon · 77.9%

Gap6.9 behindWeight15% ref. weight
FrontierSWE v2Score61.9%Versus best verified row

Best verified: GPT-6 Astra · 65.5%

Gap3.6 behindWeight8% ref. weight
SWE MultilingualScore90.3%Versus best verified row

Best verified: Claude Opus 5.5 · 93.9%

Gap3.6 behindWeight5% ref. weight
FrontierCode 1.1 MainScore46.2%Versus best verified row

Best verified: Claude Opus 5.5 · 54.4%

Gap8.2 behindWeight4% ref. weight
CursorBench 4.0Score55.5%Versus best verified row

Best verified: Claude Opus 5.5 · 57.8%

Gap2.3 behindWeightDisplay only
SWE MultimodalSWE-bench MultimodalScore54.3%Versus best verified row

Best verified: Claude Opus 5.5 · 61.4%

Gap7.1 behindWeightDisplay only
FrontierCode 1.1 ExtendedScore59.1%Versus best verified row

Best verified: GPT-6 Astra · 64.5%

Gap5.4 behindWeightDisplay only
ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch?Score79.7%Versus best verified row

Best verified: Claude Opus 5 · 93.0%

Gap13.3 behindWeightDisplay only
Agentic11 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 4.0Score70.60%Versus best verified row

Best verified: Claude Sonnet 5.5 · 70.60%

GapBest verifiedWeight8% ref. weight
HLE w/ toolsHumanity's Last Exam with toolsScore64.5%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap3.2 behindWeight3% ref. weight
Toolathlon-VerifiedScore77.8%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap2.8 behindWeight3% ref. weight
DRACOData Research and Analysis with Complex OperationsScore87.0%Versus best verified row

Best verified: Claude Opus 5 · 88.6%

Gap1.6 behindWeightDisplay only
Terminal-Bench-Science 0.1Score59.9%Versus best verified row

Best verified: GPT-6 Astra · 64.6%

Gap4.7 behindWeightDisplay only
LAB all-pass (Harvey held-out)Legal Agent Benchmark all-pass rate — Harvey held-out setScore10.0%Versus best verified row

Best verified: Claude Opus 5 · 11.7%

Gap1.7 behindWeightDisplay only
LAB criterion-pass (Harvey held-out)Legal Agent Benchmark mean criterion-pass rate — Harvey held-out setScore93.1%Versus best verified row

Best verified: Claude Opus 5 · 94.1%

Gap1 behindWeightDisplay only
Toolathlon Verified Pass@3Score85.2%Versus best verified row

Best verified: Claude Opus 5 · 87.0%

Gap1.8 behindWeightDisplay only
Toolathlon Verified Pass³Toolathlon Verified Pass cubedScore68.5%Versus best verified row

Best verified: Claude Opus 5 · 73.1%

Gap4.6 behindWeightDisplay only
Toolathlon Verified avg. turnsToolathlon Verified average assistant turnsScore31.6 turnsVersus best verified row

Best verified: Claude Sonnet 5.5 · 31.6 turns

GapBest verifiedWeightDisplay only
AutomationBench (Zapier 1.0.6)AutomationBench, Zapier private evaluation set release 1.0.6Score44.70%Versus best verified row

Best verified: Claude Sonnet 5.5 · 44.70%

GapBest verifiedWeightDisplay only
Multimodal7 rows
Multimodal benchmark values, best verified comparison, weight, and source status
OfficeQA ProScore65.6%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap2.1 behindWeightWeighted 25%
Chartography (no tools)Chartography without toolsScore61.6%Versus best verified row

Best verified: Gemini 4 Argon · 71.6%

Gap10 behindWeightDisplay only
Chartography (tools)Chartography with image and code toolsScore90.2%Versus best verified row

Best verified: Claude Sonnet 5.5 · 90.2%

GapBest verifiedWeightDisplay only
BenchCAD Vision2Code (no tools)BenchCAD Vision2Code voxel IoU without toolsScore0.747Versus best verified row

Best verified: Claude Sonnet 5.5 · 0.747

GapBest verifiedWeightDisplay only
BenchCAD Vision2Code (tools)BenchCAD Vision2Code voxel IoU with toolsScore0.963Versus best verified row

Best verified: Claude Sonnet 5.5 · 0.963

GapBest verifiedWeightDisplay only
Biomedical image analysisAnthropic biomedical-image-analysis evaluationScore72.2%Versus best verified row

Best verified: Claude Sonnet 5.5 · 72.2%

GapBest verifiedWeightDisplay only
OfficeQAScore76.9%Versus best verified row

Best verified: Claude Opus 5.5 · 78.9%

Gap2 behindWeightDisplay only
Knowledge16 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLE w/o toolsHumanity's Last Exam without toolsScore56.9%Versus best verified row

Best verified: Claude Opus 5.5 · 64.4%

Gap7.5 behindWeight7% ref. weight
HealthBench (raw)HealthBench raw scoreScore69.4%Versus best verified row

Best verified: Claude Sonnet 5.5 · 69.4%

GapBest verifiedWeightDisplay only
HealthBench (length-adjusted)HealthBench length-adjusted scoreScore65.4%Versus best verified row

Best verified: Claude Sonnet 5.5 · 65.4%

GapBest verifiedWeightDisplay only
HealthBench Professional (raw)HealthBench Professional raw scoreScore77.1%Versus best verified row

Best verified: Claude Sonnet 5.5 · 77.1%

GapBest verifiedWeightDisplay only
HealthBench ProfessionalScore69.2%Versus best verified row

Best verified: Claude Sonnet 5.5 · 69.2%

GapBest verifiedWeightDisplay only
BioMysteryBench (human-solvable)BioMysteryBench Human SolvableScore89.2%Versus best verified row

Best verified: Claude Opus 5 · 90.1%

Gap0.9 behindWeightDisplay only
BioMysteryBench (human-difficult)BioMysteryBench Human DifficultScore44.7%Versus best verified row

Best verified: Gemini 3.8 Flash · 56.5%

Gap11.8 behindWeightDisplay only
SpatialBench VerifiedLatchBio SpatialBench VerifiedScore72.5%Versus best verified row

Best verified: Claude Opus 5 · 72.5%

GapBest verifiedWeightDisplay only
SingleCellBenchLatchBio SingleCellBenchScore59.1%Versus best verified row

Best verified: Claude Opus 5.5 · 61.2%

Gap2.1 behindWeightDisplay only
Protein DesignAnthropic Protein Design evaluationScore51.0%Versus best verified row

Best verified: Claude Opus 5.5 · 60.2%

Gap9.2 behindWeightDisplay only
Morphology-to-molecule matchingAxiom Bio morphology-to-molecule matchingScore25.0%Versus best verified row

Best verified: Claude Opus 5.5 · 34.0%

Gap9 behindWeightDisplay only
Medicinal chemistryAnthropic medicinal-chemistry evaluationScore65.3%Versus best verified row

Best verified: Claude Sonnet 5.5 · 65.3%

GapBest verifiedWeightDisplay only
Protein Design library rankingAnthropic protein-design library-ranking taskScore54.8%Versus best verified row

Best verified: Claude Opus 5.5 · 56.0%

Gap1.2 behindWeightDisplay only
De novo protein-binder designAnthropic de novo protein-binder design evaluationScore82.3%Versus best verified row

Best verified: Claude Opus 5.5 · 82.6%

Gap0.3 behindWeightDisplay only
Protocols (troubleshooting)Molecular Biology Protocols TroubleshootingScore67.3%Versus best verified row

Best verified: Claude Opus 5.5 · 73.7%

Gap6.4 behindWeightDisplay only
Protocols (understanding)Benchling Molecular Biology Protocols UnderstandingScore66.6%Versus best verified row

Best verified: Claude Opus 5 · 78.4%

Gap11.8 behindWeightDisplay only
Multilingual2 rows
Multilingual benchmark values, best verified comparison, weight, and source status
GMMLUGlobal MMLUScore92.1%Versus best verified row

Best verified: Claude Opus 5.5 · 94.3%

Gap2.2 behindWeightDisplay only
MILUMulti-task Indic Language Understanding BenchmarkScore91.6%Versus best verified row

Best verified: Claude Opus 5.5 · 93.1%

Gap1.5 behindWeightDisplay only
Math2 rows
Math benchmark values, best verified comparison, weight, and source status
ArXivMath Aug. 2026 (no tools)ArXivMath August 2026 without toolsScore86.8%Versus best verified row

Best verified: Claude Opus 5.5 · 91.2%

Gap4.4 behindWeightDisplay only
ArXivMath Aug. 2026 (tools)ArXivMath August 2026 with toolsScore95.2%Versus best verified row

Best verified: Claude Opus 5.5 · 96.9%

Gap1.7 behindWeightDisplay only

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Current modelExplore all models

Claude Sonnet 5.5 · 83.9 score · $6 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

30405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierClaude Sonnet 5.5

Horizontal: blended price per million tokens, log scale · Vertical: public score

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. February 2026

    Claude Sonnet 4.6

    Score 55.3 · $3 / $15

  2. Jun 30, 2026

    Claude Sonnet 5

    Score 66.0 · $2 / $10

  3. Sep 28, 2026 · you are here

    Claude Sonnet 5.5

    Score 83.9 · $2 / $10

Base entry

Radar

Claude Sonnet 5.5 release history

Full release history

Radar confirmed these at the source. Use Claude Sonnet 5.5 in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Parameters
Not disclosed by the provider
Availability
Claude API · Amazon Bedrock · Google Cloud · Microsoft Foundry · Claude Platform on AWSAnthropic Claude Sonnet 5.5 model documentation
Cloud regions
Not tracked yet
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.20 per million cached input tokensClaude API pricing
Self-host
Weights are not published
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Claude Sonnet 5.5 ranks #3 of 214 on the public leaderboard with a score of 83.9/100. Its source-verified position is #3 of 83.

Claude Sonnet 5.5 is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Available across Claude, the Claude Platform API, Amazon Web Services, Google Cloud, and Microsoft Azure. The API model ID is `claude-sonnet-5-5`; Anthropic lists a 1M-token context window and up to 128K output tokens.

Its explicit predecessor is Claude Sonnet 5. 47 of 655 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Coding at #1, while its lowest eligible position is Agentic at #10. particularly well-suited for software development and code generation tasks.

Last updated October 6, 2026. Runtime fields remain blank until a sourced snapshot exists.

Questions

How does Claude Sonnet 5.5 perform overall in AI benchmarks?

Claude Sonnet 5.5 ranks #3 out of 214 models on the public BenchAlign leaderboard, with a score of 83.9/100. Its evidence status is Supported, and this profile shows 47 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Claude Sonnet 5.5 good for knowledge and understanding?

Claude Sonnet 5.5 ranks #5 out of 173 eligible models for knowledge and understanding, with a public category score of 81.5/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Claude Sonnet 5.5 good for coding and programming?

Claude Sonnet 5.5 ranks #1 out of 144 eligible models for coding and programming, with a public category score of 85.1/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Claude Sonnet 5.5 good for mathematics?

Claude Sonnet 5.5 has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Claude Sonnet 5.5 good for agentic tool use and computer tasks?

Claude Sonnet 5.5 ranks #10 out of 120 eligible models for agentic tool use and computer tasks, with a public category score of 68.1/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Claude Sonnet 5.5 good for multimodal and grounded tasks?

Claude Sonnet 5.5 has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Claude Sonnet 5.5 good for multilingual tasks?

Claude Sonnet 5.5 has source-displayable benchmark coverage for multilingual tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Does Claude Sonnet 5.5 have full benchmark coverage on BenchLM?

No. Claude Sonnet 5.5 currently has 64 source-displayable rows across 655 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Claude Sonnet 5.5?

Claude Sonnet 5.5 has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

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Compare Claude Sonnet 5.5 with every tracked model881 comparisons