Long documents
Prompts that approach the documented context limit
GPT-5.5 Pro
GPT-5.5 Pro has the larger documented context window.
Confidence: documented
Claude Sonnet 5.5 vs GPT-5.5 Pro
Updated November 12, 2026. Rank says Claude Sonnet 5.5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
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Decision reading
Claude Sonnet 5.5 has the higher public point estimate, 83.07 versus 70.96. Their conditional score ranges overlap. These ranges do not establish rank confidence. 3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- API price per 1M tokens
Claude Sonnet 5.5: $2 input / $10 output
GPT-5.5 Pro: $30 input / $180 output
- Context window
Claude Sonnet 5.5: 1M
GPT-5.5 Pro: 1.05M
- Released
Claude Sonnet 5.5: September 28, 2026
GPT-5.5 Pro: April 23, 2026
- Shared results
- 3
- Claude Sonnet 5.5 only
- 61
- GPT-5.5 Pro only
- 5
- Like-for-like categories
- 1 / 8
Supported: Claude Sonnet 5.5 · Estimated: GPT-5.5 Pro. Conditional ranges do not establish rank confidence.How the comparison works
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Chat turn cost
1K fresh input + 500 output tokens
Claude Sonnet 5.5
Claude Sonnet 5.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Claude Sonnet 5.5
Claude Sonnet 5.5 has the lower estimated token cost for this stated workload. GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Claude Sonnet 5.5
Claude Sonnet 5.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-ratesCoding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
GPT-5.5 Pro is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GPT-5.5 Pro is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
81.0Claude Sonnet 5.5—GPT-5.5 Pro
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
Or describe your own job
The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.
Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.
We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
61 Claude Sonnet 5.5 only
3 Shared
5 GPT-5.5 Pro only
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
HLE w/o toolsKnowledge
Normalized gap 13.8Claude Sonnet 5.5:56.9%GPT-5.5 Pro:43.1%FrontierMath v2 (Tier 4)Math
Normalized gap 2.4Claude Sonnet 5.5:80.488%GPT-5.5 Pro:78.049%FrontierMath v2 (Tiers 1-3)Math
Normalized gap 1.1Claude Sonnet 5.5:88.772%GPT-5.5 Pro:87.719%
Bars run 0–100 on each benchmark’s normalized display scale
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, reasoning, multimodal, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Reasoning
Like-for-like- Claude Sonnet 5.5
- 77.0
- Supported · #6/160
- GPT-5.5 Pro
- 74.8
- Supported · #11/160
- Basis
- BenchAlign v5.8 lane · 0 vs 2 public rows
- Reading
- Claude Sonnet 5.5 leads · intervals overlap
Agentic
Not comparable- Claude Sonnet 5.5
- 72.7
- Supported · #9/135
- GPT-5.5 Pro
- Not ranked
- Basis
- BenchAlign v5.8 lane · 19 vs 1 public rows
- Reading
- Not comparable
Coding
Not comparable- Claude Sonnet 5.5
- 81.0
- Supported · #4/162
- GPT-5.5 Pro
- Not ranked
- Basis
- BenchAlign v5.8 lane · 12 vs 0 public rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Sonnet 5.5
- 78.9
- Estimated · #7/67
- GPT-5.5 Pro
- Not ranked
- Basis
- BenchAlign v5.8 lane · 10 vs 0 public rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Sonnet 5.5
- 82.1
- Supported · #6/180
- GPT-5.5 Pro
- Not ranked
- Basis
- BenchAlign v5.8 lane · 17 vs 2 public rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 5.5
- Not ranked
- GPT-5.5 Pro
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 5.5
- Not ranked
- GPT-5.5 Pro
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 5.5
- 89.7
- Unranked · 4 rankable rows
- GPT-5.5 Pro
- 88.5
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Not comparable
| Category | Claude Sonnet 5.5 | GPT-5.5 Pro | Basis | Reading |
|---|---|---|---|---|
| Reasoning | 77.0Supported · #6/160 | 74.8Supported · #11/160 | Like-for-likeBenchAlign v5.8 lane · 0 vs 2 public rows | Claude Sonnet 5.5 leads · intervals overlap |
| Agentic | 72.7Supported · #9/135 | Not ranked | Not comparableBenchAlign v5.8 lane · 19 vs 1 public rows | Not comparable |
| Coding | 81.0Supported · #4/162 | Not ranked | Not comparableBenchAlign v5.8 lane · 12 vs 0 public rows | Not comparable |
| Multimodal | 78.9Estimated · #7/67 | Not ranked | Not comparableBenchAlign v5.8 lane · 10 vs 0 public rows | Not comparable |
| Knowledge | 82.1Supported · #6/180 | Not ranked | Not comparableBenchAlign v5.8 lane · 17 vs 2 public rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 89.7Unranked · 4 rankable rows | 88.5Unranked · 3 rankable rows | Not comparableProvisional lane · 2 vs 2 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Supported evidence per lane · bars run 0–100Methodology
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Claude Sonnet 5.5
- $0.007
- Fits in one request
- GPT-5.5 Pro
- $0.12
- Fits in one request
Claude Sonnet 5.5 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 5.5
- $0.13
- Fits in one request
- GPT-5.5 Pro
- $2.04
- Fits in one request
Claude Sonnet 5.5 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Sonnet 5.5
- $0.16
- Fits in one request
- GPT-5.5 Pro
- $8.40
- Fits in one request
- Cached input priced at the published list-input rate
Claude Sonnet 5.5 has the lower modeled cost
GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate.
Your workload
Enter a month of tokens to price it at both models’ listed API rates.
- Claude Sonnet 5.5
- $40.00
- per month
- GPT-5.5 Pro
- $660.00
- per month
Standard listed rates, no batch or volume discounts.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Sonnet 5.5GPT-5.5 Pro
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 5.5
GPT-5.5 Pro
API model ID
Claude Sonnet 5.5
claude-sonnet-5-5
Anthropic Claude Sonnet 5.5 model documentationGPT-5.5 Pro
gpt-5.5-pro
OpenAI GPT-5.5 Pro model documentationCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5.5
$0.1 per 1M cached input tokens
Claude API pricingGPT-5.5 Pro
Not published
OpenAI pricingDocumented inputs
Claude Sonnet 5.5
GPT-5.5 Pro
text, image
OpenAI model catalogDocumented outputs
Claude Sonnet 5.5
GPT-5.5 Pro
Provider availability
Claude Sonnet 5.5
Generally Available · Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Claude Platform on AWS
Anthropic Claude Sonnet 5.5 model documentationGPT-5.5 Pro
Generally Available · OpenAI Responses API
OpenAI model catalogReasoning profile
Claude Sonnet 5.5
Reasoning
GPT-5.5 Pro
Reasoning
Weight access
Claude Sonnet 5.5
Proprietary
GPT-5.5 Pro
Proprietary
License
Claude Sonnet 5.5
Proprietary
GPT-5.5 Pro
Proprietary
Release date
Claude Sonnet 5.5
2026-09-28
GPT-5.5 Pro
2026-04-23
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Claude Sonnet 5.5 has the higher public point estimate, 83.07 versus 70.96. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- Repository review: $0.13 vs $2.04. Cache-heavy agent loop: $0.16 vs $8.40.
- Context tradeoff
- GPT-5.5 Pro has the larger documented window (1.05M).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, Claude Sonnet 5.5 or GPT-5.5 Pro?
Claude Sonnet 5.5 has the higher public point estimate, 83.07 versus 70.96. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Sonnet 5.5 or GPT-5.5 Pro?
GPT-5.5 Pro is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Claude Sonnet 5.5 or GPT-5.5 Pro?
GPT-5.5 Pro is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Claude Sonnet 5.5 or GPT-5.5 Pro?
For the stated presets, chat costs $0.007 on Claude Sonnet 5.5 and $0.12 on GPT-5.5 Pro; repository review costs $0.13 and $2.04; the cache-heavy agent loop costs $0.16 and $8.40. GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Sonnet 5.5 or GPT-5.5 Pro?
GPT-5.5 Pro has the larger documented context window: 1.05M, compared with 1M.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence69 rows
Agentic
Terminal-Bench 4.1
Claude Sonnet 5.563.90%SourceGPT-5.5 Pro—Not directly comparable
Terminal-Bench 4.0
Claude Sonnet 5.570.60%SourceGPT-5.5 Pro—Not directly comparable
HLE w/ tools
Claude Sonnet 5.564.5%SourceGPT-5.5 Pro—Not directly comparable
DRACO
Claude Sonnet 5.587.0%SourceGPT-5.5 Pro—Not directly comparable
Terminal-Bench-Science 0.1
Claude Sonnet 5.559.9%SourceGPT-5.5 Pro—Not directly comparable
LAB all-pass (Harvey held-out)
Claude Sonnet 5.510.0%SourceGPT-5.5 Pro—Not directly comparable
LAB criterion-pass (Harvey held-out)
Claude Sonnet 5.593.1%SourceGPT-5.5 Pro—Not directly comparable
Toolathlon Verified Pass@3
Claude Sonnet 5.585.2%SourceGPT-5.5 Pro—Not directly comparable
Toolathlon Verified Pass³
Claude Sonnet 5.568.5%SourceGPT-5.5 Pro—Not directly comparable
Toolathlon Verified avg. turns
Claude Sonnet 5.531.6 turnsSourceGPT-5.5 Pro—Not directly comparable
AutomationBench (Zapier 1.0.6)
Claude Sonnet 5.544.70%SourceGPT-5.5 Pro—Not directly comparable
Toolathlon-Verified
Claude Sonnet 5.577.8%SourceGPT-5.5 Pro—Not directly comparable
Hermes Index
Claude Sonnet 5.553.1%SourceGPT-5.5 Pro—Not directly comparable
Hermes Bench
Claude Sonnet 5.573.5%SourceGPT-5.5 Pro—Not directly comparable
MazeBench
Claude Sonnet 5.58%SourceGPT-5.5 Pro—Not directly comparable
OSWorld 2.1
Claude Sonnet 5.580.1%SourceGPT-5.5 Pro—Not directly comparable
OSWorld 2.1 Offline
Claude Sonnet 5.583.9%SourceGPT-5.5 Pro—Not directly comparable
Binary Exploitation Benchmark
Claude Sonnet 5.548SourceGPT-5.5 Pro—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Sonnet 5.583.1%SourceGPT-5.5 Pro—Not directly comparable
BrowseComp
Claude Sonnet 5.5—GPT-5.5 Pro90.1%SourceNot directly comparable
Coding
FrontierCode 1.1 Main
Claude Sonnet 5.546.2%SourceGPT-5.5 Pro—Not directly comparable
CursorBench 4.0
Claude Sonnet 5.555.5%SourceGPT-5.5 Pro—Not directly comparable
SWE-bench Pro
Claude Sonnet 5.581.3%SourceGPT-5.5 Pro—Not directly comparable
SWE Multilingual
Claude Sonnet 5.590.3%SourceGPT-5.5 Pro—Not directly comparable
SWE Multimodal
Claude Sonnet 5.554.3%SourceGPT-5.5 Pro—Not directly comparable
DeepSWE
Claude Sonnet 5.571.0%SourceGPT-5.5 Pro—Not directly comparable
FrontierCode 1.1 Extended
Claude Sonnet 5.559.1%SourceGPT-5.5 Pro—Not directly comparable
ProgramBench
Claude Sonnet 5.579.7%SourceGPT-5.5 Pro—Not directly comparable
FrontierSWE v2
Claude Sonnet 5.561.9%SourceGPT-5.5 Pro—Not directly comparable
Bug Hunt Bench
Claude Sonnet 5.551.3 fixesSourceGPT-5.5 Pro—Not directly comparable
FrontierCode 2.0
Claude Sonnet 5.541.0%SourceGPT-5.5 Pro—Not directly comparable
VulcanBench Frontier v4
Claude Sonnet 5.592.0%SourceGPT-5.5 Pro—Not directly comparable
Reasoning
Multimodal
ExtractBench Pro
Claude Sonnet 5.532%SourceGPT-5.5 Pro—Not directly comparable
ExtractBench (LlamaIndex)
Claude Sonnet 5.594.68%SourceGPT-5.5 Pro—Not directly comparable
ParseBench
Claude Sonnet 5.569.21%SourceGPT-5.5 Pro—Not directly comparable
Chartography (no tools)
Claude Sonnet 5.561.6%SourceGPT-5.5 Pro—Not directly comparable
Chartography (tools)
Claude Sonnet 5.590.2%SourceGPT-5.5 Pro—Not directly comparable
BenchCAD Vision2Code (no tools)
Claude Sonnet 5.50.747SourceGPT-5.5 Pro—Not directly comparable
BenchCAD Vision2Code (tools)
Claude Sonnet 5.50.963SourceGPT-5.5 Pro—Not directly comparable
Biomedical image analysis
Claude Sonnet 5.572.2%SourceGPT-5.5 Pro—Not directly comparable
OfficeQA
Claude Sonnet 5.576.9%SourceGPT-5.5 Pro—Not directly comparable
OfficeQA Pro
Claude Sonnet 5.565.6%SourceGPT-5.5 Pro—Not directly comparable
Knowledge
HealthBench (raw)
Claude Sonnet 5.569.4%SourceGPT-5.5 Pro—Not directly comparable
HealthBench (length-adjusted)
Claude Sonnet 5.565.4%SourceGPT-5.5 Pro—Not directly comparable
HealthBench Professional (raw)
Claude Sonnet 5.577.1%SourceGPT-5.5 Pro—Not directly comparable
HealthBench Professional
Claude Sonnet 5.569.2%SourceGPT-5.5 Pro—Not directly comparable
BioMysteryBench (human-solvable)
Claude Sonnet 5.589.2%SourceGPT-5.5 Pro—Not directly comparable
BioMysteryBench (human-difficult)
Claude Sonnet 5.544.7%SourceGPT-5.5 Pro—Not directly comparable
SpatialBench Verified
Claude Sonnet 5.572.5%SourceGPT-5.5 Pro—Not directly comparable
SingleCellBench
Claude Sonnet 5.559.1%SourceGPT-5.5 Pro—Not directly comparable
Protein Design
Claude Sonnet 5.551.0%SourceGPT-5.5 Pro—Not directly comparable
Morphology-to-molecule matching
Claude Sonnet 5.525.0%SourceGPT-5.5 Pro—Not directly comparable
Medicinal chemistry
Claude Sonnet 5.565.3%SourceGPT-5.5 Pro—Not directly comparable
Protein Design library ranking
Claude Sonnet 5.554.8%SourceGPT-5.5 Pro—Not directly comparable
De novo protein-binder design
Claude Sonnet 5.582.3%SourceGPT-5.5 Pro—Not directly comparable
Protocols (troubleshooting)
Claude Sonnet 5.567.3%SourceGPT-5.5 Pro—Not directly comparable
Protocols (understanding)
Claude Sonnet 5.566.6%SourceGPT-5.5 Pro—Not directly comparable
HLE w/o tools
Claude Sonnet 5.556.9%SourceGPT-5.5 Pro43.1%SourceClaude Sonnet 5.5 leads this result
PhysicianBench
Claude Sonnet 5.563.2%SourceGPT-5.5 Pro—Not directly comparable
HLE
Claude Sonnet 5.5—GPT-5.5 Pro57.2%SourceNot directly comparable
Multilingual
Math
ArXivMath Aug. 2026 (no tools)
Claude Sonnet 5.586.8%SourceGPT-5.5 Pro—Not directly comparable
ArXivMath Aug. 2026 (tools)
Claude Sonnet 5.595.2%SourceGPT-5.5 Pro—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude Sonnet 5.588.772%GPT-5.5 Pro87.719%Claude Sonnet 5.5 leads this result
FrontierMath v2 (Tier 4)
Shared sourceClaude Sonnet 5.580.488%GPT-5.5 Pro78.049%Claude Sonnet 5.5 leads this result
FrontierMath (legacy)
Claude Sonnet 5.5—GPT-5.5 Pro52.4%SourceNot directly comparable
69 public results · 3 shared
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Last updated November 12, 2026