Anthropic · Model release
Data as of September 28, 2026 · How the score is built
Claude Sonnet 5.5
Decision readingClaude Sonnet 5.5 scores 80.5 out of 100 and ranks #5 of 201. This profile shows 47 source-displayable benchmark rows; its strongest eligible category is Coding at #3. 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
Claude Sonnet 5.5 will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Share or export
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
80.5/100
field median 50.3#5 of 201 ranked models
Public
#5of 201
Verified —
Price
$2input / $10 output
input median $1cached $0.20 · batch + cache $0.10 · blended $6
Speed
Not measured
field median 95 tok/sTime to first token not measured
Context
1Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Coding ranks #3. Particularly well-suited for software development and code generation tasks.
Validate before choosing
47 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
Source-linked · 47 displayable benchmark rows
Follow model changesCategory 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 | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #10 of 111Percentile 92ndWeight 22%11 benchmarksVerified | 66.1 | 11 benchmarks | Verified | |||
| CodingRank #3 of 136Percentile 99thWeight 20%9 benchmarksVerified | 79.6 | 9 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalRank Not rankedWeight 12%7 benchmarksVerified | 83.3 | 7 benchmarks | Verified | |||
| KnowledgeRank #6 of 160Percentile 97thWeight 12%16 benchmarksVerified | 80.9 | 16 benchmarks | Verified | |||
| MultilingualWeight 7%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%2 benchmarksVerified | Score pending | 2 benchmarks | Verified |
47 of 486 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow 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.
- Agentic11/11 verified
- Coding9/9 verified
- ReasoningNot measured
- Multimodal7/7 verified
- Knowledge16/16 verified
- Multilingual2/2 verified
- Inst. FollowingNot measured
- Math2/2 verified
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
- Coding99th percentile
- ReasoningNot eligible
- MultimodalNot eligible
- Knowledge97th percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#10/111
- Coding#3/136
- ReasoningNot ranked
- MultimodalNot ranked
- Knowledge#6/160
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
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
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score81.3% | Versus best verified row Best verified: Claude Opus 5.5 · 89.9% | Gap8.6 behind | Weight26% ref. weight | Provider exact |
| DeepSWE | Score71.0% | Versus best verified row Best verified: Muse Spark 1.3 · 75.4% | Gap4.4 behind | Weight15% ref. weight | Provider exact |
| FrontierSWE v2 | Score61.9% | Versus best verified row Best verified: GPT-6 Astra · 65.5% | Gap3.6 behind | Weight8% ref. weight | Provider exact |
| SWE Multilingual | Score90.3% | Versus best verified row Best verified: Claude Opus 5.5 · 93.9% | Gap3.6 behind | Weight5% ref. weight | Provider exact |
| FrontierCode 1.1 Main | Score46.2% | Versus best verified row Best verified: Claude Opus 5.5 · 54.4% | Gap8.2 behind | Weight4% ref. weight | Provider exact |
| CursorBench 4.0 | Score55.5% | Versus best verified row Best verified: Claude Opus 5.5 · 57.8% | Gap2.3 behind | WeightDisplay only | Benchmark exact |
| SWE MultimodalSWE-bench Multimodal | Score54.3% | Versus best verified row Best verified: Claude Opus 5.5 · 61.4% | Gap7.1 behind | WeightDisplay only | Provider exact |
| FrontierCode 1.1 Extended | Score59.1% | Versus best verified row Best verified: GPT-6 Astra · 64.5% | Gap5.4 behind | WeightDisplay only | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score79.7% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap13.3 behind | WeightDisplay only | Provider exact |
Agentic11 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 4.0 | Score70.60% | Versus best verified row Best verified: Claude Sonnet 5.5 · 70.60% | GapBest verified | Weight8% ref. weight | Provider exact |
| HLE w/ toolsHumanity's Last Exam with tools | Score64.5% | Versus best verified row Best verified: Claude Opus 5.5 · 67.7% | Gap3.2 behind | Weight3% ref. weight | Provider exact |
| Toolathlon-Verified | Score77.8% | Versus best verified row Best verified: Claude Opus 5 · 80.6% | Gap2.8 behind | Weight3% ref. weight | Provider exact |
| DRACOData Research and Analysis with Complex Operations | Score87.0% | Versus best verified row Best verified: Claude Opus 5 · 88.6% | Gap1.6 behind | WeightDisplay only | Provider exact |
| Terminal-Bench-Science 0.1 | Score59.9% | Versus best verified row Best verified: GPT-6 Astra · 64.6% | Gap4.7 behind | WeightDisplay only | Provider exact |
| LAB all-pass (Harvey held-out)Legal Agent Benchmark all-pass rate — Harvey held-out set | Score10.0% | Versus best verified row Best verified: Claude Opus 5 · 11.7% | Gap1.7 behind | WeightDisplay only | Provider exact |
| LAB criterion-pass (Harvey held-out)Legal Agent Benchmark mean criterion-pass rate — Harvey held-out set | Score93.1% | Versus best verified row Best verified: Claude Opus 5 · 94.1% | Gap1 behind | WeightDisplay only | Provider exact |
| Toolathlon Verified Pass@3 | Score85.2% | Versus best verified row Best verified: Claude Opus 5 · 87.0% | Gap1.8 behind | WeightDisplay only | Provider exact |
| Toolathlon Verified Pass³Toolathlon Verified Pass cubed | Score68.5% | Versus best verified row Best verified: Claude Opus 5 · 73.1% | Gap4.6 behind | WeightDisplay only | Provider exact |
| Toolathlon Verified avg. turnsToolathlon Verified average assistant turns | Score31.6 turns | Versus best verified row Best verified: Claude Sonnet 5.5 · 31.6 turns | GapBest verified | WeightDisplay only | Provider exact |
| AutomationBench (Zapier 1.0.6)AutomationBench, Zapier private evaluation set release 1.0.6 | Score44.7% | Versus best verified row Best verified: Claude Sonnet 5.5 · 44.7% | GapBest verified | WeightDisplay only | Provider exact |
Multimodal7 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| OfficeQA Pro | Score65.6% | Versus best verified row Best verified: Claude Opus 5.5 · 67.7% | Gap2.1 behind | WeightWeighted 25% | Provider exact |
| Chartography (no tools)Chartography without tools | Score61.6% | Versus best verified row Best verified: Claude Opus 5.5 · 64.4% | Gap2.8 behind | WeightDisplay only | Provider exact |
| Chartography (tools)Chartography with image and code tools | Score90.2% | Versus best verified row Best verified: Claude Sonnet 5.5 · 90.2% | GapBest verified | WeightDisplay only | Provider exact |
| BenchCAD Vision2Code (no tools)BenchCAD Vision2Code voxel IoU without tools | Score0.747 | Versus best verified row Best verified: Claude Sonnet 5.5 · 0.747 | GapBest verified | WeightDisplay only | Provider exact |
| BenchCAD Vision2Code (tools)BenchCAD Vision2Code voxel IoU with tools | Score0.963 | Versus best verified row Best verified: Claude Sonnet 5.5 · 0.963 | GapBest verified | WeightDisplay only | Provider exact |
| Biomedical image analysisAnthropic biomedical-image-analysis evaluation | Score72.2% | Versus best verified row Best verified: Claude Sonnet 5.5 · 72.2% | GapBest verified | WeightDisplay only | Provider exact |
| OfficeQA | Score76.9% | Versus best verified row Best verified: Claude Opus 5.5 · 78.9% | Gap2 behind | WeightDisplay only | Provider exact |
Knowledge16 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLE w/o toolsHumanity's Last Exam without tools | Score56.9% | Versus best verified row Best verified: Claude Opus 5.5 · 64.4% | Gap7.5 behind | Weight7% ref. weight | Provider exact |
| HealthBench (raw)HealthBench raw score | Score69.4% | Versus best verified row Best verified: Claude Sonnet 5.5 · 69.4% | GapBest verified | WeightDisplay only | Provider exact |
| HealthBench (length-adjusted)HealthBench length-adjusted score | Score65.4% | Versus best verified row Best verified: Claude Sonnet 5.5 · 65.4% | GapBest verified | WeightDisplay only | Provider exact |
| HealthBench Professional (raw)HealthBench Professional raw score | Score77.1% | Versus best verified row Best verified: Claude Sonnet 5.5 · 77.1% | GapBest verified | WeightDisplay only | Provider exact |
| HealthBench Professional | Score69.2% | Versus best verified row Best verified: Claude Sonnet 5.5 · 69.2% | GapBest verified | WeightDisplay only | Provider exact |
| BioMysteryBench (human-solvable)BioMysteryBench Human Solvable | Score89.2% | Versus best verified row Best verified: Claude Opus 5 · 90.1% | Gap0.9 behind | WeightDisplay only | Provider exact |
| BioMysteryBench (human-difficult)BioMysteryBench Human Difficult | Score44.7% | Versus best verified row Best verified: Gemini 3.8 Flash · 56.5% | Gap11.8 behind | WeightDisplay only | Provider exact |
| SpatialBench VerifiedLatchBio SpatialBench Verified | Score72.5% | Versus best verified row Best verified: Claude Opus 5 · 72.5% | GapBest verified | WeightDisplay only | Provider exact |
| SingleCellBenchLatchBio SingleCellBench | Score59.1% | Versus best verified row Best verified: Claude Opus 5.5 · 61.2% | Gap2.1 behind | WeightDisplay only | Provider exact |
| Protein DesignAnthropic Protein Design evaluation | Score51.0% | Versus best verified row Best verified: Claude Opus 5.5 · 60.2% | Gap9.2 behind | WeightDisplay only | Provider exact |
| Morphology-to-molecule matchingAxiom Bio morphology-to-molecule matching | Score25.0% | Versus best verified row Best verified: Claude Opus 5.5 · 34.0% | Gap9 behind | WeightDisplay only | Provider exact |
| Medicinal chemistryAnthropic medicinal-chemistry evaluation | Score65.3% | Versus best verified row Best verified: Claude Sonnet 5.5 · 65.3% | GapBest verified | WeightDisplay only | Provider exact |
| Protein Design library rankingAnthropic protein-design library-ranking task | Score54.8% | Versus best verified row Best verified: Claude Opus 5.5 · 56.0% | Gap1.2 behind | WeightDisplay only | Provider exact |
| De novo protein-binder designAnthropic de novo protein-binder design evaluation | Score82.3% | Versus best verified row Best verified: Claude Opus 5.5 · 82.6% | Gap0.3 behind | WeightDisplay only | Provider exact |
| Protocols (troubleshooting)Molecular Biology Protocols Troubleshooting | Score67.3% | Versus best verified row Best verified: Claude Opus 5.5 · 73.7% | Gap6.4 behind | WeightDisplay only | Provider exact |
| Protocols (understanding)Benchling Molecular Biology Protocols Understanding | Score66.6% | Versus best verified row Best verified: Claude Opus 5 · 78.4% | Gap11.8 behind | WeightDisplay only | Provider exact |
Multilingual2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| GMMLUGlobal MMLU | Score92.1% | Versus best verified row Best verified: Claude Opus 5.5 · 94.3% | Gap2.2 behind | WeightDisplay only | Provider exact |
| MILUMulti-task Indic Language Understanding Benchmark | Score91.6% | Versus best verified row Best verified: Claude Opus 5.5 · 93.1% | Gap1.5 behind | WeightDisplay only | Provider exact |
Math2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| ArXivMath Aug. 2026 (no tools)ArXivMath August 2026 without tools | Score86.8% | Versus best verified row Best verified: Claude Opus 5.5 · 91.2% | Gap4.4 behind | WeightDisplay only | Provider exact |
| ArXivMath Aug. 2026 (tools)ArXivMath August 2026 with tools | Score95.2% | Versus best verified row Best verified: Claude Opus 5.5 · 96.9% | Gap1.7 behind | WeightDisplay only | Provider exact |
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.
Claude Sonnet 5.5 · 80.5 score · $6 blended per million tokens
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
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.
Base entry
Claude Sonnet 5.5 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.
- API model ID
- claude-sonnet-5-5Claude API pricing
- Context window
- 1MClaude API pricing
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not disclosed by the provider
- Availability
- 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.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- 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 #5 of 201 on the public leaderboard with a score of 80.49/100. It does not yet have enough sourced coverage for a verified position.
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 486 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #3, while its lowest eligible position is Agentic at #10. particularly well-suited for software development and code generation tasks.
Last updated September 28, 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 #5 out of 201 models on the public BenchAlign leaderboard, with a score of 80.49/100. Its evidence status is Estimated, 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 #6 out of 160 eligible models for knowledge and understanding, with a public category score of 80.9/100. 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 #3 out of 136 eligible models for coding and programming, with a public category score of 79.6/100. 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 111 eligible models for agentic tool use and computer tasks, with a public category score of 66.1/100. 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 61 source-displayable rows across 486 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.