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  1. Collection
  2. Large Language Models (LLMs)
  3. Claude Sonnet 4.6

Write, Code, and Plan with Claude Sonnet 4.6

Claude Sonnet 4.6 is a large language model that reads, writes, and reasons through text with a level of depth most tools cannot match. If you spend hours drafting documents, debugging functions, or summarizing lengthy reports, this model handles those tasks in seconds without requiring any technical setup on your end. It can hold up to 1 million tokens in a single conversation, so you can paste an entire codebase, a long legal contract, or a stack of research papers and get back an answer that accounts for all of it. It generates code that runs, spots logic errors in functions without being told where to look, and produces structured documents that stay on topic from start to finish. It also breaks complex multi-step goals into ordered tasks and works through each one in sequence. Freelance writers use it to draft and revise. Developers paste in error messages and get working fixes. Analysts hand it dense reports and receive clear, readable summaries. Claude Sonnet 4.6 fits into the workflow you already have, rather than asking you to change how you work.

Official

Anthropic

7.7k runs

Claude Sonnet 4.6

2026-05-26

Commercial Use

Write, Code, and Plan with Claude Sonnet 4.6

Table of contents

  • Overview
  • How It Works
  • Frequently Asked Questions
  • Credit Cost
  • Features
  • Use Cases
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Overview

Claude Sonnet 4.6 is a large language model built for text tasks that require real depth: writing structured documents, reasoning across long inputs, analyzing code, and planning multi-step work. It supports a 1 million token context window in beta, which means you can feed it an entire codebase, a long legal contract, or a novel-length report and ask questions without the model losing its place. On Picasso IA, you get access to this through a simple text box, with no API setup, no configuration files, and no technical knowledge required. You can also attach images alongside your text, making it useful for tasks like analyzing a screenshot, reading a diagram, or describing what you see in a photo.

How It Works

  • Write your prompt in the input box: a question, a task description, a document to summarize, or code you want reviewed
  • Optionally upload an image if your task includes a visual element, such as a screenshot, a chart, or a photo
  • Set a system prompt to give the model a specific role or set of rules, like "act as a legal document reviewer" or "always respond in bullet points"
  • Adjust the maximum token output to control how long the response can run; use a lower value for quick answers and a higher value for detailed writeups
  • Click generate and the model starts working immediately; longer responses stream in word by word so you see progress right away

Frequently Asked Questions

Do I need programming skills or technical knowledge to use this? No, just open Claude Sonnet 4.6 on Picasso IA, adjust the settings you want, and hit generate. The interface is plain text in, plain text out.

Is it free to try? You can run Claude Sonnet 4.6 on Picasso IA without a paid account to start. Free generations are available up to a daily limit; the pricing page has the current details on credits and plans.

How long does it take to get results? Short prompts come back in a few seconds. Longer outputs or prompts with attached images may take a bit more time, but the response streams in live so you don't have to wait for the full output before you start reading.

What kinds of tasks does this model handle well? It performs well across writing, coding, research summarization, document drafting, and multi-step reasoning tasks. The large context window makes it especially useful when the task involves long source material, like reviewing an entire document or comparing several files at once.

Can I attach images to my prompt? Yes. You can include an image alongside your text and ask the model to describe, interpret, or reason about it. The image is scaled automatically before processing to balance response time and cost.

What output formats does it support? The model outputs plain text by default. You can ask it to format the response as markdown, a table, a numbered list, or any structure you need; just include the formatting instruction in your prompt.

Where can I use the outputs? The text the model produces is yours to use however you want: paste it into a document, send it to a client, include it in a product, or use it as a starting point for further edits. There are no usage restrictions on the generated content.

Credit Cost

Each generation consumes 1 credit

1 credit

or 5 credits for 5 generations

Features

Everything this model can do for you

1M token context

Paste entire codebases, contracts, or books and receive answers that account for the full content.

Code generation

Write, debug, and refactor functions across dozens of languages with accurate, runnable output.

Image input

Submit screenshots, diagrams, or photos alongside text and receive a written response that addresses both.

Agent task planning

Describe a multi-step goal and receive a structured sequence of actions with reasoning at each step.

System prompt control

Define a custom role, tone, or behavior once and apply it consistently throughout the session.

Structured output

Request tables, lists, JSON, or formatted prose and get back exactly the format you specified.

Long-document Q&A

Ask specific questions about a pasted report or article without losing context across the full text.

Use Cases

Paste a block of buggy code and receive a corrected version with a plain-language explanation of what went wrong

Feed a full legal document or contract into the model and ask targeted questions to extract the clauses that matter to you

Describe a writing project and get a fully drafted first version you can revise and publish

Generate a structured project plan by listing your goal, timeline, and constraints in plain text

Summarize meeting transcripts or interview recordings into a concise list of decisions and action items

Draft a multi-turn customer support script by describing your product and common user complaints

Ask the model to review a long essay or article and get line-level feedback on clarity and structure

Input a dataset description and get back a working SQL query or Python script tailored to your question

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