Data as of November 6, 2026 · How the score is built
Claude Opus 5.5
Decision readingClaude Opus 5.5 scores 86.3 out of 100 and ranks #2 of 212. This profile shows 68 source-displayable benchmark rows; its strongest eligible category is Agentic at #1. API pricing is $4 input and $20 output per million tokens, with cached input at $0.2.
Released Sep 22, 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
86.3/100
field median 50.1#2 of 212 ranked models
Public
#2of 212
Verified #1 of 77
Price
$4input / $20 output
input median $0.60cached $0.20 · batch + cache $0.10 · blended $12
Speed
98tok/s
field median 92 tok/sFirst token 663.66 s
Context
1Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Agentic ranks #1. Particularly useful for coding agents, browser research, and computer-use workflows.
Validate before choosing
68 published rows leave some tracked benchmark slots empty. Reasoning is its lowest eligible category at #4.
Source-linked · 68 displayable benchmark rows
Claude Opus 5.5 API pricing
Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 per million output tokens on the Claude API. Cached input is $0.20 per million.
| Token type | Price per 1M tokens |
|---|---|
| Input | $4.00 |
| Cached input | $0.20 |
| Output | $20.00 |
At these rates, a request with 10,000 input tokens and 1,000 output tokens costs $0.06 without caching.
On blended price (the average of the input and output rates), 1 of the 112 other ranked models with a published API price costs the same or less and scores higher. See where it sits on the chart
Pricing notes: Anthropic's September 22, 2026 Claude Opus 5.5 model documentation lists the claude-opus-5-5 API model at $4 input / $20 output per million tokens, with $0.20 cache reads. Five-minute and one-hour cache writes are $5 and $8 per million tokens; Batch API input and output receive a 50% discount.
Rates from Claude Opus 5.5 model documentation, effective September 22, 2026. API model ID: claude-opus-5-5. Price registry updated November 6, 2026.
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 #1 of 131Percentile 100thWeight 22%17 benchmarksVerified | 89.3 | 17 benchmarks | Verified | |||
| CodingRank #1 of 157Percentile 100thWeight 20%13 benchmarksVerified | 82.8 | 13 benchmarks | Verified | |||
| ReasoningRank #4 of 25Percentile 88thWeight 17%4 benchmarksVerified | 84.4 | 4 benchmarks | Verified | |||
| MultimodalRank #3 of 59Percentile 97thWeight 12%10 benchmarksVerified | 91.6 | 10 benchmarks | Verified | |||
| KnowledgeRank #1 of 178Percentile 100thWeight 12%16 benchmarksVerified | 89.4 | 16 benchmarks | Verified | |||
| MultilingualWeight 7%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| Inst. FollowingWeight 5%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| MathRank Not rankedWeight 5%4 benchmarksVerified | 93.8 | 4 benchmarks | Verified |
68 of 816 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.
- Agentic17/17 verified
- Coding13/13 verified
- Reasoning4/4 verified
- Multimodal10/10 verified
- Knowledge16/16 verified
- Multilingual2/2 verified
- Inst. Following1/1 verified
- 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 Opus 5.5 category percentile values
- Agentic100th percentile
- Coding100th percentile
- Reasoning88th percentile
- Multimodal97th percentile
- Knowledge100th percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#1/131
- Coding#1/157
- Reasoning#4/25
- Multimodal#3/59
- Knowledge#1/178
- 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.
Coding13 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score89.9% | Versus best verified row Best verified: Claude Opus 5.5 · 89.9% | GapBest verified | Weight26% ref. weight | Provider exact |
| DeepSWE | Score74.2% | Versus best verified row Best verified: Muse Wonder Full · 79.0% | Gap4.8 behind | Weight15% ref. weight | Provider exact |
| FrontierSWE v2 | Score62.3% | Versus best verified row Best verified: GPT-6 Astra · 65.5% | Gap3.2 behind | Weight8% ref. weight | Benchmark exact |
| SWE Multilingual | Score93.9% | Versus best verified row Best verified: Claude Opus 5.5 · 93.9% | GapBest verified | Weight5% ref. weight | Provider exact |
| FrontierCode 1.1 Main | Score54.4% | Versus best verified row Best verified: Claude Opus 5.5 · 54.4% | GapBest verified | Weight4% ref. weight | Provider exact |
| ScarfBenchScarfBench: Cross-Framework Application Migration in Enterprise Java | Score70.5% | Versus best verified row Best verified: Gemini 4 Argon · 75.2% | Gap4.7 behind | WeightDisplay only | Benchmark exact |
| CursorBench 4.0 | Score57.8% | Versus best verified row Best verified: Claude Opus 5.5 · 57.8% | GapBest verified | WeightDisplay only | Benchmark exact |
| SWE MultimodalSWE-bench Multimodal | Score61.4% | Versus best verified row Best verified: Claude Opus 5.5 · 61.4% | GapBest verified | WeightDisplay only | Provider exact |
| FrontierCode 1.1 Extended | Score63.6% | Versus best verified row Best verified: GPT-6 Astra · 64.5% | Gap0.9 behind | WeightDisplay only | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score91.2% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap1.8 behind | WeightDisplay only | Provider exact |
| PostTrainBench v1.1 | Score49.3% | Versus best verified row Best verified: Claude Opus 5.5 · 49.3% | GapBest verified | WeightDisplay only | Provider exact |
| Bug Hunt Bench | Score41.7 fixes | Versus best verified row Best verified: Claude Sonnet 5.5 · 51.3 fixes | Gap9.6 behind | WeightDisplay only | Benchmark exact |
| FrontierCode 2.0 | Score45.5% | Versus best verified row Best verified: Claude Opus 5.5 · 45.5% | GapBest verified | WeightDisplay only | Benchmark exact |
Agentic17 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 4.0 | Score66.40% | Versus best verified row Best verified: Claude Sonnet 5.5 · 70.60% | Gap4.2 behind | Weight8% ref. weight | Provider exact |
| AutomationBench | Score40.0% | Versus best verified row Best verified: MiniMax M3.1 Flash · 62.2% | Gap22.2 behind | Weight6% ref. weight | Provider exact |
| HLE w/ toolsHumanity's Last Exam with tools | Score67.7% | Versus best verified row Best verified: Kimi K3.1 Pro · 70.0% | Gap2.3 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 |
| Terminal-Bench-Science 0.1 | Score58.7% | Versus best verified row Best verified: GPT-6 Astra · 64.6% | Gap5.9 behind | WeightDisplay only | Provider exact |
| OSWorld 2.0 | Score48.7% | Versus best verified row Best verified: Kimi K3.1 Pro · 79.6% | Gap30.9 behind | WeightDisplay only | Provider exact |
| LAB all-pass (Harvey held-out)Legal Agent Benchmark all-pass rate — Harvey held-out set | Score8.3% | Versus best verified row Best verified: Claude Opus 5 · 11.7% | Gap3.4 behind | WeightDisplay only | Provider exact |
| LAB criterion-pass (Harvey held-out)Legal Agent Benchmark mean criterion-pass rate — Harvey held-out set | Score91.2% | Versus best verified row Best verified: Claude Opus 5 · 94.1% | Gap2.9 behind | WeightDisplay only | Provider exact |
| Toolathlon Verified Pass@3 | Score82.4% | Versus best verified row Best verified: Claude Opus 5 · 87.0% | Gap4.6 behind | WeightDisplay only | Provider exact |
| Toolathlon Verified Pass³Toolathlon Verified Pass cubed | Score72.2% | Versus best verified row Best verified: Claude Opus 5 · 73.1% | Gap0.9 behind | WeightDisplay only | Provider exact |
| Toolathlon Verified avg. turnsToolathlon Verified average assistant turns | Score26.9 turns | Versus best verified row Best verified: Claude Sonnet 5.5 · 31.6 turns | Gap4.7 behind | WeightDisplay only | Provider exact |
| CWE-bench v1 | Score67.0% | Versus best verified row Best verified: Gemini 4 Carbon · 71.0% | Gap4 behind | WeightDisplay only | Benchmark exact |
| Hermes IndexHermes Index: agentic capability and cost per task inside Hermes Agent | Score63.3% | Versus best verified row Best verified: Claude Opus 5.5 · 63.3% | GapBest verified | WeightDisplay only | Benchmark exact |
| Hermes BenchHermes Bench: 150 agent tasks graded on the files and state the agent leaves behind | Score76.7% | Versus best verified row Best verified: Claude Opus 5.5 · 76.7% | GapBest verified | WeightDisplay only | Benchmark exact |
| MazeBenchMazeBench: visual spatial reasoning in a 3D open world | Score13% | Versus best verified row Best verified: GPT-6 Astra · 23% | Gap10 behind | WeightDisplay only | Benchmark exact |
| OSWorld 2.1OSWorld 2.1 (all 108 tasks) | Score81.8% | Versus best verified row Best verified: Claude Opus 5.5 · 81.8% | GapBest verified | WeightDisplay only | Provider exact |
| OSWorld 2.1 OfflineOSWorld 2.1 offline subset (82 tasks) | Score87.2% | Versus best verified row Best verified: Claude Opus 5.5 · 87.2% | GapBest verified | WeightDisplay only | Provider exact |
Reasoning4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2 | Score91.7% | Versus best verified row Best verified: GPT-6 Astra · 95% | Gap3.3 behind | WeightWeighted 25% | Benchmark exact |
| STEMBenchSTEMBench120: six-domain scientific research progress | Score2.62 | Versus best verified row Best verified: GPT-6 Astra · 2.81 | Gap0.2 behind | WeightDisplay only | Benchmark exact |
| ARC-AGI-1ARC-AGI-1 Semi-Private Evaluation | Score97.50% | Versus best verified row Best verified: Claude Fable 5 · 98.50% | Gap1 behind | WeightDisplay only | Benchmark exact |
| GraphWalks BFS 256K–1M | Score66.8% | Versus best verified row Best verified: Gemini 4 Carbon · 96.2% | Gap29.4 behind | WeightDisplay only | Provider exact |
Multimodal10 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| OfficeQA Pro | Score67.7% | Versus best verified row Best verified: Claude Opus 5.5 · 67.7% | GapBest verified | WeightWeighted 25% | Provider exact |
| ExtractBench ProExtractBench Pro: long-tail document extraction challenges (LlamaIndex) | Score51% | Versus best verified row Best verified: GPT-6 Astra · 58% | Gap7 behind | WeightDisplay only | |
| ExtractBench (LlamaIndex)ExtractBench: schema-guided enterprise document extraction (LlamaIndex leaderboard) | Score86.06% | Versus best verified row Best verified: GPT-6.1 Sol · 95.31% | Gap9.3 behind | WeightDisplay only | |
| ParseBenchParseBench: document parsing for AI agents (LlamaIndex leaderboard) | Score78.80% | Versus best verified row Best verified: Claude Opus 5.5 · 78.80% | GapBest verified | WeightDisplay only | |
| Chartography (tools)Chartography with image and code tools | Score89.0% | Versus best verified row Best verified: Claude Sonnet 5.5 · 90.2% | Gap1.2 behind | WeightDisplay only | Provider exact |
| Chartography (no tools)Chartography without tools | Score64.4% | Versus best verified row Best verified: Gemini 4 Carbon · 72.5% | Gap8.1 behind | WeightDisplay only | Provider exact |
| BenchCAD Vision2Code (no tools)BenchCAD Vision2Code voxel IoU without tools | Score0.730 | Versus best verified row Best verified: Claude Sonnet 5.5 · 0.747 | Gap0 behind | WeightDisplay only | Provider exact |
| BenchCAD Vision2Code (tools)BenchCAD Vision2Code voxel IoU with tools | Score0.962 | Versus best verified row Best verified: Claude Sonnet 5.5 · 0.963 | Gap0 behind | WeightDisplay only | Provider exact |
| Biomedical image analysisAnthropic biomedical-image-analysis evaluation | Score71.4% | Versus best verified row Best verified: Claude Sonnet 5.5 · 72.2% | Gap0.8 behind | WeightDisplay only | Provider exact |
| OfficeQA | Score78.9% | Versus best verified row Best verified: Claude Opus 5.5 · 78.9% | GapBest verified | WeightDisplay only | Provider exact |
Knowledge16 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLE w/o toolsHumanity's Last Exam without tools | Score64.4% | Versus best verified row Best verified: Claude Opus 5.5 · 64.4% | GapBest verified | Weight7% ref. weight | Provider exact |
| HealthBench (raw)HealthBench raw score | Score68.1% | Versus best verified row Best verified: Claude Sonnet 5.5 · 69.4% | Gap1.3 behind | WeightDisplay only | Provider exact |
| HealthBench (length-adjusted)HealthBench length-adjusted score | Score60.6% | Versus best verified row Best verified: Claude Sonnet 5.5 · 65.4% | Gap4.8 behind | WeightDisplay only | Provider exact |
| HealthBench Professional | Score65.6% | Versus best verified row Best verified: Claude Sonnet 5.5 · 69.2% | Gap3.6 behind | 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 |
| BioMysteryBench (human-solvable)BioMysteryBench Human Solvable | Score89.3% | Versus best verified row Best verified: Claude Opus 5 · 90.1% | Gap0.8 behind | WeightDisplay only | Provider exact |
| BioMysteryBench (human-difficult)BioMysteryBench Human Difficult | Score50.0% | Versus best verified row Best verified: Gemini 3.8 Flash · 56.5% | Gap6.5 behind | WeightDisplay only | Provider exact |
| SpatialBench VerifiedLatchBio SpatialBench Verified | Score72.0% | Versus best verified row Best verified: Claude Opus 5 · 72.5% | Gap0.5 behind | WeightDisplay only | Provider exact |
| SingleCellBenchLatchBio SingleCellBench | Score61.2% | Versus best verified row Best verified: Claude Opus 5.5 · 61.2% | GapBest verified | WeightDisplay only | Provider exact |
| Morphology-to-molecule matchingAxiom Bio morphology-to-molecule matching | Score34.0% | Versus best verified row Best verified: Claude Opus 5.5 · 34.0% | GapBest verified | WeightDisplay only | Provider exact |
| Medicinal chemistryAnthropic medicinal-chemistry evaluation | Score63.5% | Versus best verified row Best verified: Claude Sonnet 5.5 · 65.3% | Gap1.8 behind | WeightDisplay only | Provider exact |
| Protein DesignAnthropic Protein Design evaluation | Score60.2% | Versus best verified row Best verified: Claude Opus 5.5 · 60.2% | GapBest verified | WeightDisplay only | Provider exact |
| Protein Design library rankingAnthropic protein-design library-ranking task | Score56.0% | Versus best verified row Best verified: Claude Opus 5.5 · 56.0% | GapBest verified | WeightDisplay only | Provider exact |
| De novo protein-binder designAnthropic de novo protein-binder design evaluation | Score82.6% | Versus best verified row Best verified: Claude Opus 5.5 · 82.6% | GapBest verified | WeightDisplay only | Provider exact |
| Protocols (troubleshooting)Molecular Biology Protocols Troubleshooting | Score73.7% | Versus best verified row Best verified: Claude Opus 5.5 · 73.7% | GapBest verified | WeightDisplay only | Provider exact |
| Protocols (understanding)Benchling Molecular Biology Protocols Understanding | Score69.0% | Versus best verified row Best verified: Claude Opus 5 · 78.4% | Gap9.4 behind | WeightDisplay only | Provider exact |
Multilingual2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| GMMLUGlobal MMLU | Score94.3% | Versus best verified row Best verified: Claude Opus 5.5 · 94.3% | GapBest verified | WeightDisplay only | Provider exact |
| MILUMulti-task Indic Language Understanding Benchmark | Score93.1% | Versus best verified row Best verified: Claude Opus 5.5 · 93.1% | GapBest verified | WeightDisplay only | Provider exact |
Inst. Following1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Gray Swan IPI (15 attempts)Gray Swan Indirect Prompt Injection, attack success at 15 attempts | Score1.0% | Versus best verified row Best verified: Gemini 4 Carbon · 0.0% | Gap1 behind | WeightDisplay only | Provider exact |
Math4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | Score91.228% | Versus best verified row Best verified: GPT-6 Astra · 93.684% | Gap2.5 behind | WeightWeighted 30% | Benchmark exact |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | Score95.000% | Versus best verified row Best verified: GPT-6.1 Sol · 100.000% | Gap5 behind | WeightWeighted 10% | Benchmark exact |
| ArXivMath Aug. 2026 (no tools)ArXivMath August 2026 without tools | Score91.2% | Versus best verified row Best verified: Claude Opus 5.5 · 91.2% | GapBest verified | WeightDisplay only | Provider exact |
| ArXivMath Aug. 2026 (tools)ArXivMath August 2026 with tools | Score96.9% | Versus best verified row Best verified: Claude Opus 5.5 · 96.9% | GapBest verified | WeightDisplay only | Provider exact |
External signals1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Clocktower BenchClocktower Bench (Blood on the Clocktower) | Score1549 | Versus best verified row Best verified: GPT-6 Astra · 1859 | Gap310 behind | WeightDisplay only | Benchmark 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 Opus 5.5 · 86.3 score · $12 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
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-opus-5-5Anthropic Claude Opus 5.5 model documentation
- Context window
- 1MAnthropic Claude Opus 5.5 model documentation
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, imageAnthropic Claude Opus 5.5 model documentation
- Output modalities
- textAnthropic Claude Opus 5.5 model documentation
- Parameters
- Not disclosed by the provider
- Availability
- Claude API · Amazon Bedrock · Google Cloud · Microsoft Foundry · Claude Platform on AWSAnthropic Claude Opus 5.5 model documentation
- Cloud regions
- Not tracked yet
- Lifecycle
- activeAnthropic Claude Opus 5.5 model documentation
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.20 per million cached input tokensClaude Opus 5.5 model documentation
- 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 Opus 5.5 ranks #2 of 212 on the public leaderboard with a score of 86.32/100. Its source-verified position is #1 of 77.
Claude Opus 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 through the Claude API as `claude-opus-5-5`, plus Amazon Bedrock, Google Cloud, Microsoft Foundry, and Claude Platform on AWS. Anthropic lists a 1M-token context window and 128K standard output limit.
Official exact-value snapshot from Anthropic's September 22, 2026 Claude Opus 5.5 launch page and system card. The system-card results use adaptive thinking at maximum effort unless noted; Terminal-Bench 4.0 uses xhigh effort. Cursor's live leaderboard supplies the independent CursorBench 4.0 Max row, which remains display-only because it uses Cursor's agent harness. OSWorld 2.0 stores only the reported strict pass rate, not its paired partial-credit rate. The August 2026 ArXivMath release is kept on distinct display-only lanes rather than collapsed into the earlier June release.
Its explicit predecessor is Claude Opus 5. 68 of 816 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Agentic at #1, while its lowest eligible position is Reasoning at #4. particularly useful for coding agents, browser research, and computer-use workflows.
Last updated November 6, 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 Opus 5.5 by API
2 hosts publish a per-token price for it. DeepInfra has the lowest output rate, $20.00 per million tokens. Prices read from each host’s own pages on October 20, 2026.
| Host | Input /1M | Output /1M | Cached /1M | Context |
|---|---|---|---|---|
| DeepInfra | $4.00 | $20.00 | $0.20 | 1M |
| OpenRouter | $4.00 | $20.00 | $0.20 | 1M |
Questions
How does Claude Opus 5.5 perform overall in AI benchmarks?
Claude Opus 5.5 ranks #2 out of 212 models on the public BenchAlign leaderboard, with a score of 86.32/100. Its evidence status is Supported, and this profile shows 68 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Claude Opus 5.5 good for knowledge and understanding?
Claude Opus 5.5 ranks #1 out of 178 eligible models for knowledge and understanding, with a public category score of 89.4/100. 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 Opus 5.5 good for coding and programming?
Claude Opus 5.5 ranks #1 out of 157 eligible models for coding and programming, with a public category score of 82.8/100. 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 Opus 5.5 good for mathematics?
Claude Opus 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 Opus 5.5 good for reasoning and logic?
Claude Opus 5.5 ranks #4 out of 25 eligible models for reasoning and logic, with a public category score of 84.4/100. 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 Opus 5.5 good for agentic tool use and computer tasks?
Claude Opus 5.5 ranks #1 out of 131 eligible models for agentic tool use and computer tasks, with a public category score of 89.3/100. 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 Opus 5.5 good for multimodal and grounded tasks?
Claude Opus 5.5 ranks #3 out of 59 eligible models for multimodal and grounded tasks, with a public category score of 91.6/100. 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 Opus 5.5 good for instruction following?
Claude Opus 5.5 has source-displayable benchmark coverage for instruction following, 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 Opus 5.5 good for multilingual tasks?
Claude Opus 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 Opus 5.5 have full benchmark coverage on BenchLM?
No. Claude Opus 5.5 currently has 92 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 Opus 5.5?
Claude Opus 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.