Anthropic · Frontier
Claude Sonnet 5.5 Thinking
Claude Sonnet 5.5 with adaptive thinking for complex coding, multi-step tool use, visual analysis, and detailed planning. Supports a 1M-token context window and five reasoning effort levels, with stronger thinking available when a task needs it.
- Reasoning
- Tools
- Vision
- Structured output
- PDF input
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- low · medium · high · xhigh · max
- Discovery tier
- Frontier
Pricing
USD per 1M tokens- Input
- $2.00
- Output
- $10.00
- Cache read
- $0.10
- Cache write
- $2.50
- $4.00 for a 1-hour cache
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 128K
- Average output (7 days)
- 3K tokens
- Longer than 96% of 473 models
Side by side
Compare models
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Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
Intelligence Index
46.8
Tested at high reasoning effort
Better than 93% of 326 scored models
Agentic work
AutomationBench-AA
59.4%Workflow automation, penalized for guardrail violations
Better than 79% of 173 scored models
AutomationBench-AA tasks completed
29.4%Workflows finished end to end without a guardrail violation
Better than 80% of 173 scored models
AA-Briefcasev1.1
1,635 EloAgentic knowledge work, rated head to head
Better than 93% of 166 scored models
GDPval-AAv2.1
1,548 EloEconomically valuable occupational tasks, rated head to head
Better than 81% of 187 scored models
Document reasoning
GDP.pdf
25.2%Professional reasoning over PDF documents, all-pass rate
Better than 88% of 171 scored models
AA-LCRv1.1
78.0%Reasoning across long documents
Better than 65% of 309 scored models
MLCR-AA
18.9%Long-context reasoning over medical records
Better than 76% of 121 scored models
Reasoning and knowledge
Humanity’s Last Exam
45.8%Expert-level questions across academic fields
Better than 88% of 323 scored models
Coding
Terminal-Benchv4.0
43.9%Practical software engineering in a terminal
Better than 90% of 171 scored models
SciCode
53.7%Scientific computing in Python
Better than 66% of 174 scored models
Legacy evaluations
AA-LCR (unversioned)
78.0%Long-context reasoning, earlier grading
Better than 65% of 309 scored models
Scores from Artificial Analysis, updated Oct 26, 2026. Claude Sonnet 5.5 Thinking was tested at high reasoning effort; compare scores measured at the same effort.Artificial Analysis
- #14Math7.2%
Ranks among Noumen catalog models on Use cases leaderboards. Only top-20 placements are listed.
- #14Math1501.1
- #13Longer Query1499.5
- #16Creative Writing1466.3
- #14Instruction Following1485.1
- #19Hard Prompts1504.5
- #9Chinese1541.9
- #14English1491.9
- #6Expert1534.7
- #14Hard Prompts English1513.2
- #12Industry Entertainment And Sports And Media1464.2
- #19Industry Life And Physical And Social Science1498.2
- #11Industry Mathematical1513.3
- #19Industry Software And It Services1515.7
- #18Industry Writing And Literature And Language1473.6
- #10Vision Style Control · Diagram1321.3
- #11Vision Style Control · Homework1325.5
- #3WebDev Overall1768.9
- #2WebDev · Image To Webdev1737.1
- #3WebDev · Webdev1768.9
- #4WebDev · Webdev-html1739.4
- #2WebDev · Webdev-react1816.1
Ranks among Noumen catalog models on LMArena leaderboards. Only top-20 placements are listed.LMArena
- #14ARC-AGI-283.9%
- #5ARC-AGI-3 (Default harness)24.3%
Ranks among Noumen catalog models on ARC Prize leaderboards. Only top-20 placements are listed.ARC Prize
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 250.1 tok/s
- Faster than 90% of 259 models
- Time to first token
- 5.7 s
- Quicker than 25% of 259 models
- Prompt cache hits
- 43.6%
- About $1.17 per 1M input tokens with caching
- Request success (24h)
- 99.3%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "anthropic/claude-sonnet-5.5:thinking",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="anthropic/claude-sonnet-5.5:thinking",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Anthropic
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