Data as of November 12, 2026 · How the score is built
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.
| Token type | Price 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.
Is Claude Sonnet 5.5 right for your job?
Its place on the LLM Selector’s job rankings, the same order the job pages publish. Describe your own job to see where it stands for that.
Where Claude Sonnet 5.5 ranks by benchmark score:
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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 | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #9 of 135Percentile 94thWeight 22%19 benchmarksVerified | 72.7 | 19 benchmarks | Verified | |||
| CodingRank #4 of 162Percentile 98thWeight 20%12 benchmarksVerified | 81.0 | 12 benchmarks | Verified | |||
| ReasoningRank #6 of 160Percentile 97thWeight 17%Not listedUnlisted sources | 77.0 | Not listed | Unlisted sources | |||
| MultimodalRank #7 of 67Percentile 91stWeight 12%10 benchmarksVerified | 78.9 | 10 benchmarks | Verified | |||
| KnowledgeRank #6 of 180Percentile 97thWeight 12%17 benchmarksVerified | 82.1 | 17 benchmarks | Verified | |||
| MultilingualWeight 7%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathRank Not rankedWeight 5%4 benchmarksVerified | 89.7 | 4 benchmarks | Verified |
78 of 906 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.
- Agentic19/19 verified
- Coding12/12 verified
- ReasoningNot measured
- Multimodal10/10 verified
- Knowledge17/17 verified
- Multilingual2/2 verified
- Inst. FollowingNot measured
- Math4/4 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
- 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
- Agentic#9/135
- Coding#4/162
- Reasoning#6/160
- Multimodal#7/67
- Knowledge#6/180
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
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.
Coding12 rows
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| SWE-bench Pro | 81.3% | Best verified: Claude Fable 5.2 · 93% | Gap11.7 behind | Reported by Anthropic | Counts26% ref. weight |
| DeepSWE | 71.0% | Best verified: Muse Wonder Full · 79.0% | Gap8 behind | Reported by Anthropic | Counts15% ref. weight |
| CursorBench 4.0 | 55.5% | Best verified: Gemini 4 Carbon · 60.4% | Gap4.9 behind | Run by CursorBench 4.0 | Counts10% ref. weight |
| FrontierSWE v2 | 61.9% | Best verified: Claude Fable 5.2 · 69.9% | Gap8 behind | Run by FrontierSWE v2 | Counts8% ref. weight |
| SWE Multilingual | 90.3% | Best verified: Claude Fable 5.2 · 96.6% | Gap6.3 behind | Reported by Anthropic | Counts5% ref. weight |
| FrontierCode 2.0 | 41.0% | Best verified: Claude Fable 5.2 · 49.1% | Gap8.1 behind | Run by FrontierCode 2.0 | Counts4% ref. weight |
| VulcanBench Frontier v4 | 92.0% | Best verified: Grok 4.7 · 93.2% | Gap1.1 behind | Run by VulcanBench Frontier v4 | Counts3% ref. weight |
| FrontierCode 1.1 Main | 46.2% | Best verified: Claude Opus 5.5 · 54.4% | Gap8.2 behind | Reported by Anthropic | Shown only |
| SWE MultimodalSWE-bench Multimodal | 54.3% | Best verified: Claude Fable 5.2 · 74.1% | Gap19.8 behind | Reported by Anthropic | Shown only |
| FrontierCode 1.1 Extended | 59.1% | Best verified: GPT-6 Astra · 64.5% | Gap5.4 behind | Reported by Anthropic | Shown only |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | 79.7% | Best verified: Claude Opus 5 · 93.0% | Gap13.3 behind | Reported by Anthropic | Shown only |
| Bug Hunt Bench | 51.3 fixes | Best verified: Claude Fable 5.2 · 58.0 fixes | Gap6.7 behind | Run by Bug Hunt Bench | Shown only |
Agentic19 rows
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| Terminal-Bench 4.1 | 63.90% | Best verified: Claude Opus 5.5 · 65.80% | Gap1.9 behind | Run by Terminal-Bench 4.1 | Counts9% ref. weight |
| Terminal-Bench 4.0 | 70.60% | Best verified: Claude Sonnet 5.5 · 70.60% | GapHighest listed | Reported by Anthropic | Counts9% ref. weight |
| Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI run | 83.1% | Best verified: Claude Opus 5.5 · 87.6% | Gap4.5 behind | Independent run: Vals AI | Counts4% ref. weight |
| HLE w/ toolsHumanity's Last Exam with tools | 64.5% | Best verified: Kimi K3.1 Pro · 70.0% | Gap5.5 behind | Reported by Anthropic | Counts3% ref. weight |
| Toolathlon-Verified | 77.8% | Best verified: Claude Opus 5 · 80.6% | Gap2.8 behind | Reported by Anthropic | Counts3% ref. weight |
| DRACOData Research and Analysis with Complex Operations | 87.0% | Best verified: Claude Opus 5 · 88.6% | Gap1.6 behind | Reported by Anthropic | Shown only |
| Terminal-Bench-Science 0.1 | 59.9% | Best verified: Claude Mythos 5.2 · 75.3% | Gap15.4 behind | Reported by Anthropic | Shown only |
| LAB all-pass (Harvey held-out)Legal Agent Benchmark all-pass rate — Harvey held-out set | 10.0% | Best verified: Claude Opus 5 · 11.7% | Gap1.7 behind | Reported by Anthropic | Shown only |
| LAB criterion-pass (Harvey held-out)Legal Agent Benchmark mean criterion-pass rate — Harvey held-out set | 93.1% | Best verified: Claude Opus 5 · 94.1% | Gap1 behind | Reported by Anthropic | Shown only |
| Toolathlon Verified Pass@3 | 85.2% | Best verified: Claude Opus 5 · 87.0% | Gap1.8 behind | Reported by Anthropic | Shown only |
| Toolathlon Verified Pass³Toolathlon Verified Pass cubed | 68.5% | Best verified: Claude Opus 5 · 73.1% | Gap4.6 behind | Reported by Anthropic | Shown only |
| Toolathlon Verified avg. turnsToolathlon Verified average assistant turns | 31.6 turns | Best verified: Claude Sonnet 5.5 · 31.6 turns | GapHighest listed | Reported by Anthropic | Shown only |
| AutomationBench (Zapier 1.0.6)AutomationBench, Zapier private evaluation set release 1.0.6 | 44.70% | Best verified: Claude Sonnet 5.5 · 44.70% | GapHighest listed | Reported by Anthropic | Shown only |
| Hermes IndexHermes Index: agentic capability and cost per task inside Hermes Agent | 53.1% | Best verified: Claude Opus 5.5 · 63.3% | Gap10.2 behind | Run by Hermes Index | Shown only |
| Hermes BenchHermes Bench: 150 agent tasks graded on the files and state the agent leaves behind | 73.5% | Best verified: Claude Opus 5.5 · 76.7% | Gap3.3 behind | Run by Hermes Bench | Shown only |
| MazeBenchMazeBench: visual spatial reasoning in a 3D open world | 8% | Best verified: GPT-6 Astra · 23% | Gap15 behind | Run by MazeBench | Shown only |
| OSWorld 2.1OSWorld 2.1 (all 108 tasks) | 80.1% | Best verified: Claude Opus 5.5 · 81.8% | Gap1.7 behind | Reported by Anthropic | Shown only |
| OSWorld 2.1 OfflineOSWorld 2.1 offline subset (82 tasks) | 83.9% | Best verified: Claude Fable 5.2 · 89.3% | Gap5.4 behind | Reported by Anthropic | Shown only |
| Binary Exploitation BenchmarkAnthropic Binary Exploitation Benchmark (formerly OSS-Fuzz), control-flow hijacks | 48 | Best verified: Claude Mythos 5.2 · 148 | Gap100 behind | Reported by Anthropic | Shown only |
Multimodal10 rows
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| OfficeQA Pro | 65.6% | Best verified: Claude Fable 5.2 · 72.9% | Gap7.3 behind | Reported by Anthropic | Counts20% ref. weight |
| ParseBenchParseBench: document parsing for AI agents (LlamaIndex leaderboard) | 69.21% | Best verified: Claude Opus 5.5 · 78.80% | Gap9.6 behind | Run by ParseBench | Counts7% ref. weight |
| ExtractBench ProExtractBench Pro: long-tail document extraction challenges (LlamaIndex) | 32% | Best verified: GPT-6 Astra · 58% | Gap26 behind | Run by ExtractBench Pro | Shown only |
| ExtractBench (LlamaIndex)ExtractBench: schema-guided enterprise document extraction (LlamaIndex leaderboard) | 94.68% | Best verified: GPT-6.1 Sol · 95.31% | Gap0.6 behind | Run by ExtractBench (LlamaIndex) | Shown only |
| Chartography (no tools)Chartography without tools | 61.6% | Best verified: Claude Fable 5.2 · 73.4% | Gap11.8 behind | Reported by Anthropic | Shown only |
| Chartography (tools)Chartography with image and code tools | 90.2% | Best verified: Claude Fable 5.2 · 91.6% | Gap1.4 behind | Reported by Anthropic | Shown only |
| BenchCAD Vision2Code (no tools)BenchCAD Vision2Code voxel IoU without tools | 0.747 | Best verified: Claude Sonnet 5.5 · 0.747 | GapHighest listed | Reported by Anthropic | Shown only |
| BenchCAD Vision2Code (tools)BenchCAD Vision2Code voxel IoU with tools | 0.963 | Best verified: Claude Sonnet 5.5 · 0.963 | GapHighest listed | Reported by Anthropic | Shown only |
| Biomedical image analysisAnthropic biomedical-image-analysis evaluation | 72.2% | Best verified: Claude Mythos 5.2 · 80.7% | Gap8.5 behind | Reported by Anthropic | Shown only |
| OfficeQA | 76.9% | Best verified: Claude Fable 5.2 · 83.4% | Gap6.5 behind | Reported by Anthropic | Shown only |
Knowledge17 rows
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| HLE w/o toolsHumanity's Last Exam without tools | 56.9% | Best verified: Claude Fable 5.2 · 73.2% | Gap16.3 behind | Reported by Anthropic | Counts7% ref. weight |
| HealthBench (raw)HealthBench raw score | 69.4% | Best verified: Claude Sonnet 5.5 · 69.4% | GapHighest listed | Reported by Anthropic | Shown only |
| HealthBench (length-adjusted)HealthBench length-adjusted score | 65.4% | Best verified: Claude Sonnet 5.5 · 65.4% | GapHighest listed | Reported by Anthropic | Shown only |
| HealthBench Professional (raw)HealthBench Professional raw score | 77.1% | Best verified: Claude Sonnet 5.5 · 77.1% | GapHighest listed | Reported by Anthropic | Shown only |
| HealthBench Professional | 69.2% | Best verified: Claude Sonnet 5.5 · 69.2% | GapHighest listed | Reported by Anthropic | Shown only |
| BioMysteryBench (human-solvable)BioMysteryBench Human Solvable | 89.2% | Best verified: Claude Opus 5 · 90.1% | Gap0.9 behind | Reported by Anthropic | Shown only |
| BioMysteryBench (human-difficult)BioMysteryBench Human Difficult | 44.7% | Best verified: Gemini 3.8 Flash · 56.5% | Gap11.8 behind | Reported by Anthropic | Shown only |
| SpatialBench VerifiedLatchBio SpatialBench Verified | 72.5% | Best verified: Claude Opus 5 · 72.5% | GapHighest listed | Reported by Anthropic | Shown only |
| SingleCellBenchLatchBio SingleCellBench | 59.1% | Best verified: Claude Mythos 5.2 · 65.6% | Gap6.5 behind | Reported by Anthropic | Shown only |
| Protein DesignAnthropic Protein Design evaluation | 51.0% | Best verified: Claude Mythos 5.2 · 64.6% | Gap13.6 behind | Reported by Anthropic | Shown only |
| Morphology-to-molecule matchingAxiom Bio morphology-to-molecule matching | 25.0% | Best verified: Claude Mythos 5.2 · 35.2% | Gap10.2 behind | Reported by Anthropic | Shown only |
| Medicinal chemistryAnthropic medicinal-chemistry evaluation | 65.3% | Best verified: Claude Mythos 5.2 · 69.0% | Gap3.7 behind | Reported by Anthropic | Shown only |
| Protein Design library rankingAnthropic protein-design library-ranking task | 54.8% | Best verified: Claude Opus 5.5 · 56.0% | Gap1.2 behind | Reported by Anthropic | Shown only |
| De novo protein-binder designAnthropic de novo protein-binder design evaluation | 82.3% | Best verified: Claude Mythos 5.2 · 85.1% | Gap2.8 behind | Reported by Anthropic | Shown only |
| Protocols (troubleshooting)Molecular Biology Protocols Troubleshooting | 67.3% | Best verified: Claude Mythos 5.2 · 77.1% | Gap9.8 behind | Reported by Anthropic | Shown only |
| Protocols (understanding)Benchling Molecular Biology Protocols Understanding | 66.6% | Best verified: Claude Opus 5 · 78.4% | Gap11.8 behind | Reported by Anthropic | Shown only |
| PhysicianBench | 63.2% | Best verified: Claude Opus 5.5 · 68.4% | Gap5.2 behind | Reported by Anthropic | Shown only |
Multilingual2 rows
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| GMMLUGlobal MMLU | 92.1% | Best verified: Claude Fable 5.2 · 96.0% | Gap3.9 behind | Reported by Anthropic | Shown only |
| MILUMulti-task Indic Language Understanding Benchmark | 91.6% | Best verified: Claude Fable 5.2 · 94.1% | Gap2.5 behind | Reported by Anthropic | Shown only |
Math4 rows
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | 88.772% | Best verified: Claude Fable 5.2 · 95.088% | Gap6.3 behind | Run by FrontierMath v2 (Tiers 1-3) | CountsWeighted 30% |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | 80.488% | Best verified: Claude Fable 5.2 · 100.000% | Gap19.5 behind | Run by FrontierMath v2 (Tier 4) | CountsWeighted 10% |
| ArXivMath Aug. 2026 (no tools)ArXivMath August 2026 without tools | 86.8% | Best verified: Claude Opus 5.5 · 91.2% | Gap4.4 behind | Reported by Anthropic | Shown only |
| ArXivMath Aug. 2026 (tools)ArXivMath August 2026 with tools | 95.2% | Best verified: Claude Opus 5.5 · 96.9% | Gap1.7 behind | Reported by Anthropic | Shown only |
External signals14 rows
| Benchmark | Score | Versus best verified row | Gap | Who ran it | Use in ranking |
|---|---|---|---|---|---|
| NYT ConnectionsNYT Connections LLM Benchmark (extended version) | 80.5% | Best verified: Gemini 4 Argon · 98.6% | Gap18.1 behind | Run by NYT Connections | Shown only |
| Joke Arena | 1549 | Best verified: GPT-6 Astra · 1564 | Gap15 behind | Run by Joke Arena | Shown only |
| Chart Arena | 1456 | Best verified: GPT-6.1 Sol · 1627 | Gap171 behind | Run by Chart Arena | Shown only |
| FailureSensorIQ | 67.4% | Best verified: GPT-6 Astra · 69.6% | Gap2.2 behind | Run by FailureSensorIQ | Shown only |
| DAYJOB Healthcare | 16.0% | Best verified: Claude Opus 5.5 · 25.2% | Gap9.2 behind | Run by DAYJOB Healthcare | Shown only |
| DAYJOB | 21.7% | Best verified: Claude Opus 5.5 · 24.5% | Gap2.8 behind | Run by DAYJOB | Shown only |
| FACTS Multimodal | 50.4% | Best verified: Gemini 4 Carbon · 60.2% | Gap9.8 behind | Run by FACTS Multimodal | Shown only |
| StealthMarkStealthMark Intelligence Benchmarks (overall score) | 70.2 | Best verified: GPT-6 Astra · 74.6 | Gap4.4 behind | Run by StealthMark | Shown only |
| MaxxBenchMaxxBench (mutated DeepSWE tasks) | 66.9% | Best verified: Claude Opus 5.5 · 76.4% | Gap9.5 behind | Run by MaxxBench | Shown only |
| SpireClimbSpireClimb (Slay the Spire 1 and 2) | 1.3% | Best verified: GPT-6 Astra · 34.0% | Gap32.7 behind | Run by SpireClimb | Shown only |
| Chess PuzzlesChess Puzzles (Epoch AI) | 59.0% | Best verified: Claude Fable 5.2 · 79.0% | Gap20 behind | Run by Chess Puzzles | Shown only |
| Mystery Game PuzzlesMystery Game Puzzles (Epoch AI) | 65.0% | Best verified: Claude Fable 5.2 · 90.0% | Gap25 behind | Run by Mystery Game Puzzles | Shown only |
| Furniture AssemblyFurniture Assembly Benchmark (Epoch AI) | 75.0% | Best verified: Claude Fable 5.2 · 90.0% | Gap15 behind | Run by Furniture Assembly | Shown only |
| MirrorCodeMirrorCode (Epoch AI and METR) | 97.8% | Best verified: Claude Sonnet 5.5 · 97.8% | GapBest verified | Run by MirrorCode | Shown 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.
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.
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.
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.
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.
- API model ID
- claude-sonnet-5-5Anthropic Claude Sonnet 5.5 model documentation
- Context window
- 1MAnthropic Claude Sonnet 5.5 model documentation
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, imageAnthropic Claude Sonnet 5.5 model documentation
- Output modalities
- textAnthropic Claude Sonnet 5.5 model documentation
- 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
- Lifecycle
- activeAnthropic Claude Sonnet 5.5 model documentation
- 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.
| Host | Input /1M | Output /1M | Cached /1M | Context |
|---|---|---|---|---|
| DeepInfra | $2.00 | $10.00 | — | 1M |
| OpenRouter | $2.00 | $10.00 | $0.10 | 1M |
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.