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Data

Data as of November 12, 2026 · How the score is built

Claude Sonnet 5.5

CurrentProprietaryReasoning

Decision readingClaude Sonnet 5.5 scores 83.1 out of 100 and ranks #6 of 215. This profile shows 78 source-displayable benchmark rows; its strongest eligible category is Coding at #4. API pricing is $2 input and $10 output per million tokens, with cached input at $0.1.

Email me when its price, rank or availability changes.

Capability

83.1/100

field median 49.4#6 of 215 ranked models

Public

#6of 215

Verified #5 of 81

Price

$2input / $10 output

input median $0.60cached $0.10 · batch + cache $0.050 · blended $6

Speed

138tok/s

field median 92 tok/sFirst token 448.12 s

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Holds badges in the November 2026 rankings release: #7 Overall, #3 Coding, #8 Reasoning, #8 Knowledge (rank badges)

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.

Strongest published evidence

Coding ranks #4. Particularly well-suited for software development and code generation tasks.

Validate before choosing

78 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #9.

Source-linked · 78 displayable benchmark rows

Claude Sonnet 5.5 API pricing

Claude Sonnet 5.5 costs $2.00 per million input tokens and $10.00 per million output tokens on the Claude API. Cached input is $0.10 per million.

Claude Sonnet 5.5 API pricing, per million tokens
Token typePrice per 1M tokens
Input$2.00
Cached input$0.10
Output$10.00

At these rates, a request with 10,000 input tokens and 1,000 output tokens costs $0.03 without caching.

On blended price (the average of the input and output rates), 2 of the 118 other ranked models with a published API price cost the same or less and score higher. See where it sits on the chart

Pricing notes: Anthropic’s current pricing docs list $2 per million input tokens, $10 per million output tokens, $0.10 cache reads, $2.50 five-minute cache writes, and $4 one-hour cache writes. The October 7, 2026 Haiku 5.5 announcement cut Sonnet 5.5 cache reads by 50% from $0.20. Batch API rates are $1 input and $5 output per million tokens; the cached-input batch estimate is half the current cache-read rate. Anthropic states that the 1M context window is included at standard pricing.

Rates from Claude API pricing, effective October 7, 2026. API model ID: claude-sonnet-5-5. Price registry updated November 12, 2026.

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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 #9 of 135Percentile 94thWeight 22%19 benchmarksVerified
72.7
CodingRank #4 of 162Percentile 98thWeight 20%12 benchmarksVerified
81.0
ReasoningRank #6 of 160Percentile 97thWeight 17%Not listedUnlisted sources
77.0
MultimodalRank #7 of 67Percentile 91stWeight 12%10 benchmarksVerified
78.9
KnowledgeRank #6 of 180Percentile 97thWeight 12%17 benchmarksVerified
82.1
MultilingualWeight 7%2 benchmarksVerified
Score pending
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathRank Not rankedWeight 5%4 benchmarksVerified
89.7

78 of 906 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. Agentic19/19 verified
  2. Coding12/12 verified
  3. ReasoningNot measured
  4. Multimodal10/10 verified
  5. Knowledge17/17 verified
  6. Multilingual2/2 verified
  7. Inst. FollowingNot measured
  8. Math4/4 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

  • Agentic94th percentile
  • Coding98th percentile
  • Reasoning97th percentile
  • Multimodal91st percentile
  • Knowledge97th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#9/135
  2. Coding#4/162
  3. Reasoning#6/160
  4. Multimodal#7/67
  5. Knowledge#6/180
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Every result says who ran the test. For this model, Anthropic ran 49 of 78. Coding opens by default. The tick marks the best source-verified result in the catalog; provisional leaders do not set the reference.

Overall rank
#6
of 215 on the leaderboard
Reported by Anthropic
49
Shown with that label
Run by a benchmark
28
The benchmark’s own run
Independent runs
1
An outside evaluator’s run
Coding12 rows
Coding benchmark results, best verified comparison, who ran each test, and whether it counts toward a rank
SWE-bench Pro81.3%

Best verified: Claude Fable 5.2 · 93%

Gap11.7 behindReported by AnthropicCounts26% ref. weight
DeepSWE71.0%

Best verified: Muse Wonder Full · 79.0%

Gap8 behindReported by AnthropicCounts15% ref. weight
CursorBench 4.055.5%

Best verified: Gemini 4 Carbon · 60.4%

Gap4.9 behindRun by CursorBench 4.0Counts10% ref. weight
FrontierSWE v261.9%

Best verified: Claude Fable 5.2 · 69.9%

Gap8 behindRun by FrontierSWE v2Counts8% ref. weight
SWE Multilingual90.3%

Best verified: Claude Fable 5.2 · 96.6%

Gap6.3 behindReported by AnthropicCounts5% ref. weight
FrontierCode 2.041.0%

Best verified: Claude Fable 5.2 · 49.1%

Gap8.1 behindRun by FrontierCode 2.0Counts4% ref. weight
VulcanBench Frontier v492.0%

Best verified: Grok 4.7 · 93.2%

Gap1.1 behindRun by VulcanBench Frontier v4Counts3% ref. weight
FrontierCode 1.1 Main46.2%

Best verified: Claude Opus 5.5 · 54.4%

Gap8.2 behindReported by AnthropicShown only
SWE MultimodalSWE-bench Multimodal54.3%

Best verified: Claude Fable 5.2 · 74.1%

Gap19.8 behindReported by AnthropicShown only
FrontierCode 1.1 Extended59.1%

Best verified: GPT-6 Astra · 64.5%

Gap5.4 behindReported by AnthropicShown only
ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch?79.7%

Best verified: Claude Opus 5 · 93.0%

Gap13.3 behindReported by AnthropicShown only
Bug Hunt Bench51.3 fixes

Best verified: Claude Fable 5.2 · 58.0 fixes

Gap6.7 behindRun by Bug Hunt BenchShown only
Agentic19 rows
Agentic benchmark results, best verified comparison, who ran each test, and whether it counts toward a rank
Terminal-Bench 4.163.90%

Best verified: Claude Opus 5.5 · 65.80%

Gap1.9 behindRun by Terminal-Bench 4.1Counts9% ref. weight
Terminal-Bench 4.070.60%

Best verified: Claude Sonnet 5.5 · 70.60%

GapHighest listedReported by AnthropicCounts9% ref. weight
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI run83.1%

Best verified: Claude Opus 5.5 · 87.6%

Gap4.5 behindIndependent run: Vals AICounts4% ref. weight
HLE w/ toolsHumanity's Last Exam with tools64.5%

Best verified: Kimi K3.1 Pro · 70.0%

Gap5.5 behindReported by AnthropicCounts3% ref. weight
Toolathlon-Verified77.8%

Best verified: Claude Opus 5 · 80.6%

Gap2.8 behindReported by AnthropicCounts3% ref. weight
DRACOData Research and Analysis with Complex Operations87.0%

Best verified: Claude Opus 5 · 88.6%

Gap1.6 behindReported by AnthropicShown only
Terminal-Bench-Science 0.159.9%

Best verified: Claude Mythos 5.2 · 75.3%

Gap15.4 behindReported by AnthropicShown only
LAB all-pass (Harvey held-out)Legal Agent Benchmark all-pass rate — Harvey held-out set10.0%

Best verified: Claude Opus 5 · 11.7%

Gap1.7 behindReported by AnthropicShown only
LAB criterion-pass (Harvey held-out)Legal Agent Benchmark mean criterion-pass rate — Harvey held-out set93.1%

Best verified: Claude Opus 5 · 94.1%

Gap1 behindReported by AnthropicShown only
Toolathlon Verified Pass@385.2%

Best verified: Claude Opus 5 · 87.0%

Gap1.8 behindReported by AnthropicShown only
Toolathlon Verified Pass³Toolathlon Verified Pass cubed68.5%

Best verified: Claude Opus 5 · 73.1%

Gap4.6 behindReported by AnthropicShown only
Toolathlon Verified avg. turnsToolathlon Verified average assistant turns31.6 turns

Best verified: Claude Sonnet 5.5 · 31.6 turns

GapHighest listedReported by AnthropicShown only
AutomationBench (Zapier 1.0.6)AutomationBench, Zapier private evaluation set release 1.0.644.70%

Best verified: Claude Sonnet 5.5 · 44.70%

GapHighest listedReported by AnthropicShown only
Hermes IndexHermes Index: agentic capability and cost per task inside Hermes Agent53.1%

Best verified: Claude Opus 5.5 · 63.3%

Gap10.2 behindRun by Hermes IndexShown only
Hermes BenchHermes Bench: 150 agent tasks graded on the files and state the agent leaves behind73.5%

Best verified: Claude Opus 5.5 · 76.7%

Gap3.3 behindRun by Hermes BenchShown only
MazeBenchMazeBench: visual spatial reasoning in a 3D open world8%

Best verified: GPT-6 Astra · 23%

Gap15 behindRun by MazeBenchShown only
OSWorld 2.1OSWorld 2.1 (all 108 tasks)80.1%

Best verified: Claude Opus 5.5 · 81.8%

Gap1.7 behindReported by AnthropicShown only
OSWorld 2.1 OfflineOSWorld 2.1 offline subset (82 tasks)83.9%

Best verified: Claude Fable 5.2 · 89.3%

Gap5.4 behindReported by AnthropicShown only
Binary Exploitation BenchmarkAnthropic Binary Exploitation Benchmark (formerly OSS-Fuzz), control-flow hijacks48

Best verified: Claude Mythos 5.2 · 148

Gap100 behindReported by AnthropicShown only
Multimodal10 rows
Multimodal benchmark results, best verified comparison, who ran each test, and whether it counts toward a rank
OfficeQA Pro65.6%

Best verified: Claude Fable 5.2 · 72.9%

Gap7.3 behindReported by AnthropicCounts20% ref. weight
ParseBenchParseBench: document parsing for AI agents (LlamaIndex leaderboard)69.21%

Best verified: Claude Opus 5.5 · 78.80%

Gap9.6 behindRun by ParseBenchCounts7% ref. weight
ExtractBench ProExtractBench Pro: long-tail document extraction challenges (LlamaIndex)32%

Best verified: GPT-6 Astra · 58%

Gap26 behindRun by ExtractBench ProShown only
ExtractBench (LlamaIndex)ExtractBench: schema-guided enterprise document extraction (LlamaIndex leaderboard)94.68%

Best verified: GPT-6.1 Sol · 95.31%

Gap0.6 behindRun by ExtractBench (LlamaIndex)Shown only
Chartography (no tools)Chartography without tools61.6%

Best verified: Claude Fable 5.2 · 73.4%

Gap11.8 behindReported by AnthropicShown only
Chartography (tools)Chartography with image and code tools90.2%

Best verified: Claude Fable 5.2 · 91.6%

Gap1.4 behindReported by AnthropicShown only
BenchCAD Vision2Code (no tools)BenchCAD Vision2Code voxel IoU without tools0.747

Best verified: Claude Sonnet 5.5 · 0.747

GapHighest listedReported by AnthropicShown only
BenchCAD Vision2Code (tools)BenchCAD Vision2Code voxel IoU with tools0.963

Best verified: Claude Sonnet 5.5 · 0.963

GapHighest listedReported by AnthropicShown only
Biomedical image analysisAnthropic biomedical-image-analysis evaluation72.2%

Best verified: Claude Mythos 5.2 · 80.7%

Gap8.5 behindReported by AnthropicShown only
OfficeQA76.9%

Best verified: Claude Fable 5.2 · 83.4%

Gap6.5 behindReported by AnthropicShown only
Knowledge17 rows
Knowledge benchmark results, best verified comparison, who ran each test, and whether it counts toward a rank
HLE w/o toolsHumanity's Last Exam without tools56.9%

Best verified: Claude Fable 5.2 · 73.2%

Gap16.3 behindReported by AnthropicCounts7% ref. weight
HealthBench (raw)HealthBench raw score69.4%

Best verified: Claude Sonnet 5.5 · 69.4%

GapHighest listedReported by AnthropicShown only
HealthBench (length-adjusted)HealthBench length-adjusted score65.4%

Best verified: Claude Sonnet 5.5 · 65.4%

GapHighest listedReported by AnthropicShown only
HealthBench Professional (raw)HealthBench Professional raw score77.1%

Best verified: Claude Sonnet 5.5 · 77.1%

GapHighest listedReported by AnthropicShown only
HealthBench Professional69.2%

Best verified: Claude Sonnet 5.5 · 69.2%

GapHighest listedReported by AnthropicShown only
BioMysteryBench (human-solvable)BioMysteryBench Human Solvable89.2%

Best verified: Claude Opus 5 · 90.1%

Gap0.9 behindReported by AnthropicShown only
BioMysteryBench (human-difficult)BioMysteryBench Human Difficult44.7%

Best verified: Gemini 3.8 Flash · 56.5%

Gap11.8 behindReported by AnthropicShown only
SpatialBench VerifiedLatchBio SpatialBench Verified72.5%

Best verified: Claude Opus 5 · 72.5%

GapHighest listedReported by AnthropicShown only
SingleCellBenchLatchBio SingleCellBench59.1%

Best verified: Claude Mythos 5.2 · 65.6%

Gap6.5 behindReported by AnthropicShown only
Protein DesignAnthropic Protein Design evaluation51.0%

Best verified: Claude Mythos 5.2 · 64.6%

Gap13.6 behindReported by AnthropicShown only
Morphology-to-molecule matchingAxiom Bio morphology-to-molecule matching25.0%

Best verified: Claude Mythos 5.2 · 35.2%

Gap10.2 behindReported by AnthropicShown only
Medicinal chemistryAnthropic medicinal-chemistry evaluation65.3%

Best verified: Claude Mythos 5.2 · 69.0%

Gap3.7 behindReported by AnthropicShown only
Protein Design library rankingAnthropic protein-design library-ranking task54.8%

Best verified: Claude Opus 5.5 · 56.0%

Gap1.2 behindReported by AnthropicShown only
De novo protein-binder designAnthropic de novo protein-binder design evaluation82.3%

Best verified: Claude Mythos 5.2 · 85.1%

Gap2.8 behindReported by AnthropicShown only
Protocols (troubleshooting)Molecular Biology Protocols Troubleshooting67.3%

Best verified: Claude Mythos 5.2 · 77.1%

Gap9.8 behindReported by AnthropicShown only
Protocols (understanding)Benchling Molecular Biology Protocols Understanding66.6%

Best verified: Claude Opus 5 · 78.4%

Gap11.8 behindReported by AnthropicShown only
PhysicianBench63.2%

Best verified: Claude Opus 5.5 · 68.4%

Gap5.2 behindReported by AnthropicShown only
Multilingual2 rows
Multilingual benchmark results, best verified comparison, who ran each test, and whether it counts toward a rank
GMMLUGlobal MMLU92.1%

Best verified: Claude Fable 5.2 · 96.0%

Gap3.9 behindReported by AnthropicShown only
MILUMulti-task Indic Language Understanding Benchmark91.6%

Best verified: Claude Fable 5.2 · 94.1%

Gap2.5 behindReported by AnthropicShown only
Math4 rows
Math benchmark results, best verified comparison, who ran each test, and whether it counts toward a rank
FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-388.772%

Best verified: Claude Fable 5.2 · 95.088%

Gap6.3 behindRun by FrontierMath v2 (Tiers 1-3)CountsWeighted 30%
FrontierMath v2 (Tier 4)FrontierMath v2 Tier 480.488%

Best verified: Claude Fable 5.2 · 100.000%

Gap19.5 behindRun by FrontierMath v2 (Tier 4)CountsWeighted 10%
ArXivMath Aug. 2026 (no tools)ArXivMath August 2026 without tools86.8%

Best verified: Claude Opus 5.5 · 91.2%

Gap4.4 behindReported by AnthropicShown only
ArXivMath Aug. 2026 (tools)ArXivMath August 2026 with tools95.2%

Best verified: Claude Opus 5.5 · 96.9%

Gap1.7 behindReported by AnthropicShown only
External signals14 rows
External signals benchmark results, best verified comparison, who ran each test, and whether it counts toward a rank
NYT ConnectionsNYT Connections LLM Benchmark (extended version)80.5%

Best verified: Gemini 4 Argon · 98.6%

Gap18.1 behindRun by NYT ConnectionsShown only
Joke Arena1549

Best verified: GPT-6 Astra · 1564

Gap15 behindRun by Joke ArenaShown only
Chart Arena1456

Best verified: GPT-6.1 Sol · 1627

Gap171 behindRun by Chart ArenaShown only
FailureSensorIQ67.4%

Best verified: GPT-6 Astra · 69.6%

Gap2.2 behindRun by FailureSensorIQShown only
DAYJOB Healthcare16.0%

Best verified: Claude Opus 5.5 · 25.2%

Gap9.2 behindRun by DAYJOB HealthcareShown only
DAYJOB21.7%

Best verified: Claude Opus 5.5 · 24.5%

Gap2.8 behindRun by DAYJOBShown only
FACTS Multimodal50.4%

Best verified: Gemini 4 Carbon · 60.2%

Gap9.8 behindRun by FACTS MultimodalShown only
StealthMarkStealthMark Intelligence Benchmarks (overall score)70.2

Best verified: GPT-6 Astra · 74.6

Gap4.4 behindRun by StealthMarkShown only
MaxxBenchMaxxBench (mutated DeepSWE tasks)66.9%

Best verified: Claude Opus 5.5 · 76.4%

Gap9.5 behindRun by MaxxBenchShown only
SpireClimbSpireClimb (Slay the Spire 1 and 2)1.3%

Best verified: GPT-6 Astra · 34.0%

Gap32.7 behindRun by SpireClimbShown only
Chess PuzzlesChess Puzzles (Epoch AI)59.0%

Best verified: Claude Fable 5.2 · 79.0%

Gap20 behindRun by Chess PuzzlesShown only
Mystery Game PuzzlesMystery Game Puzzles (Epoch AI)65.0%

Best verified: Claude Fable 5.2 · 90.0%

Gap25 behindRun by Mystery Game PuzzlesShown only
Furniture AssemblyFurniture Assembly Benchmark (Epoch AI)75.0%

Best verified: Claude Fable 5.2 · 90.0%

Gap15 behindRun by Furniture AssemblyShown only
MirrorCodeMirrorCode (Epoch AI and METR)97.8%

Best verified: Claude Sonnet 5.5 · 97.8%

GapBest verifiedRun by MirrorCodeShown only

Outlined bars are lab-reported. Filled bars are benchmark-run or independent.

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 · 83.1 score · $6 blended per million tokens

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

405060708090100$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

Published price history

This chart appears only when at least two dated first-party price records exist for the exact model. It shows rate changes, not an inferred cost trend.

06122026-092026-10Output priceInput price

2 dated first-party price records. The newest record lists $10 per million tokens.

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 55.8 · $3 / $15

  2. Jun 30, 2026

    Claude Sonnet 5

    Score 63.8 · $2 / $10

  3. Sep 28, 2026 · you are here

    Claude Sonnet 5.5

    Score 83.1 · $2 / $10

Base entry

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 $0.10 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 #6 of 215 on the public leaderboard with a score of 83.07/100. Its source-verified position is #5 of 81.

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. 78 of 906 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Coding at #4, while its lowest eligible position is Agentic at #9. particularly well-suited for software development and code generation tasks.

Last updated November 12, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Where to run Claude Sonnet 5.5 by API

2 hosts publish a per-token price for it. DeepInfra has the lowest output rate, $10.00 per million tokens. Prices read from each host’s own pages on November 11, 2026.

Inference hosts for Claude Sonnet 5.5 with input, output and cached-input prices per million tokens.
HostInput /1MOutput /1MCached /1MContext
DeepInfra$2.00$10.00—1M
OpenRouter$2.00$10.00$0.101M
Compare inference hosts

Questions

How does Claude Sonnet 5.5 perform overall in AI benchmarks?

Claude Sonnet 5.5 ranks #6 out of 215 models on the public BenchAlign leaderboard, with a score of 83.07/100. Its evidence status is Supported, and this profile shows 78 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 180 eligible models for knowledge and understanding, with a public category score of 82.1/100. 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 coding and programming?

Claude Sonnet 5.5 ranks #4 out of 162 eligible models for coding and programming, with a public category score of 81/100. 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 #9 out of 135 eligible models for agentic tool use and computer tasks, with a public category score of 72.7/100. 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 ranks #7 out of 67 eligible models for multimodal and grounded tasks, with a public category score of 78.9/100. 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 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 101 source-displayable rows. 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.

Compare Claude Sonnet 5.5 with every tracked model1030 comparisons