Claude 5.5 Sonnet
Anthropic next-generation frontier model featuring autonomous SWE capabilities, high-reliability tool loops, and industry-leading coding benchmarks.
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.
Strengths & Trade-offs
Where it wins
- Best-in-class agentic coding — top of the SWE-bench Verified tier
- Preferred for long Claude Code sessions; consolidates shared logic instead of duplicating
- 1M context + 65K max output window
- Strong price-to-capability versus Opus-class models
Trade-offs to watch
- Proprietary — no self-hosting or fine-tuning
- High-effort runs get expensive on long sessions
- Vision understanding trails Gemini's native multimodality
Killer Use Cases
Developer Quickstart & API
ANTHROPIC_API_KEY first — get an API keycurl https://api.anthropic.com/v1/messages \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2023-06-01" \
-H "content-type: application/json" \
-d '{
"model": "claude-sonnet-5-5",
"max_tokens": 1024,
"messages": [{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}]
}'import anthropic
client = anthropic.Anthropic() # reads ANTHROPIC_API_KEY
msg = client.messages.create(
model="claude-sonnet-5-5",
max_tokens=1024,
messages=[{"role": "user", "content": "Refactor this function for O(n) time and explain the change."}],
)
print(msg.content[0].text)const res = await fetch("https://api.anthropic.com/v1/messages", {
method: "POST",
headers: {
"x-api-key": process.env.ANTHROPIC_API_KEY,
"anthropic-version": "2023-06-01",
"content-type": "application/json",
},
body: JSON.stringify({
model: "claude-sonnet-5-5",
max_tokens: 1024,
messages: [{ role: "user", content: "Refactor this function for O(n) time and explain the change." }],
}),
});
console.log((await res.json()).content[0].text);Official Resources & Links
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
Scores by Source
Category Scores
Benchmark Results
Head-to-head Live Matchups
Live Specs & Architecture
- Extended thinking with adjustable effort levels (low → xhigh)
- Context compaction keeps long agent sessions coherent without dropping state
- 1M-token context with prompt caching for repo-scale prompts
Estimated monthly bill
Cite & embed
Loading badge markdown...@misc{llmpodium2026claudesonnet55,
title = {Benchmark Analysis and Intelligence Evaluation of Claude 5.5 Sonnet},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/claude-sonnet-5-5}
}Embed Score Badge
Add a live Podium Score badge to your GitHub or Hugging Face README — it links back to the live ranking.
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