Anthropic
Claude Sonnet 5.5
anthropic/claude-sonnet-5.5
Anthropic's Sonnet-class model for well-scoped everyday work: building features, fixing bugs, shipping tickets. A sensible default for a coding assistant or PR bot.
RoleThe everyday builder
$2
In / M
$10
Out / M
1.0M
Context
- AA intelligence index
- 54.5
- Inputs
- text, image, file
- Outputs
- text
- Tools
- Listed
- Structured output
- Listed
- Reasoning
- Listed
- Weights
- Not verified
- Listed
- Sep 28, 2026
01 · What it's good at
Use it for this.
Three jobs this model is built for, and the ones to give to something else.
01
Building a feature from a clear ticket
02
Fixing bugs when you have a repro
03
Day-to-day coding help in the editor or in CI
Skip it for
- Open-ended runs that go on for hours. Escalate those to Opus
- Cheap high-volume text jobs
02 · Example tasks
What you'd actually send it.
Real inputs, not a benchmark. Paste one into the snippet below to try it.
You send
Add CSV export to the /reports page. Reuse the existing table data, stream the file, and add one Playwright test.
Why this model
Well-scoped feature work is exactly the Sonnet brief on the listing.
03 · Your stack
Where it sits: Plan & reason.
Make it the default model behind your coding assistant, PR bot, or ticket agent. Run it on every ticket; escalate to Opus only when it gets stuck or the change spans the whole codebase.
Layer 01
Retrieve
Layer 02 · this model
Plan & reason
Layer 03
Do the volume
Layer 04
Gate & route
Layer 05
Draw, speak, listen
04 · Wire it up
One request. Paste and run.
Uses OpenRouter, so one key works for every model on this site. Set OPENROUTER_API_KEY and swap the prompt for one of the tasks above.
// OpenRouter speaks the OpenAI Chat Completions format.
const res = await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "anthropic/claude-sonnet-5.5",
"messages": [
{
"role": "system",
"content": "You are a senior engineer. Reply with a short plan, then the full diff."
},
{
"role": "user",
"content": "Add CSV export to the /reports page. Reuse the existing table data and add one Playwright test."
}
],
"reasoning": {
"effort": "medium"
}
}),
});
const data = await res.json();
console.log(data.choices[0].message.content);
05 · Watch out for
Gotchas.
Reasoning is mandatory on the listing (default effort: high). Medium is often enough for ticket-sized work.
Compare it with GPT-6.1 Sol on your own repo. Both target agentic coding at a similar tier.
Sources
Lessons are written from each model's listing and the linked docs. We don't publish our own benchmark numbers; the index above is Artificial Analysis, as shown on OpenRouter.
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