Claude Opus 4.7, Sonnet 4.6, and Haiku 4.5: Differences and Model Selection Guide

What are the differences between Claude Opus 4.7, Claude Sonnet 4.6, and Claude Haiku 4.5? This guide compares positioning, capabilities, use cases, access options, and model selection advice for developers.

Anthropic’s core large language models mainly evolve through the Claude series. As of May 2026, Claude’s mainstream product line has entered the 4.x stage, while still following a three-tier structure: Opus is for maximum capability, Sonnet balances performance and cost, and Haiku focuses on speed and cost effectiveness.

If you only want a quick rule of thumb, remember this:

  • For the most complex and demanding reasoning and agentic coding: start with Claude Opus 4.7.
  • For most development, writing, analysis, and enterprise API scenarios: Claude Sonnet 4.6 is the safest starting point.
  • For high-concurrency, low-latency, cost-sensitive tasks: consider Claude Haiku 4.5.

Current Mainstream Models

According to Anthropic’s official model documentation, the current Claude mainstream models can be understood this way.

Model Positioning Suitable Scenarios
Claude Opus 4.7 The strongest generally available model, built for complex reasoning and agentic coding Large codebase refactoring, multi-step tasks, complex strategy analysis, work that requires stronger consistency
Claude Sonnet 4.6 The balance point between speed, capability, and cost, with a 1 million token context window Code generation, long-document analysis, enterprise knowledge work, Agent development, everyday high-quality production tasks
Claude Haiku 4.5 The fastest and lower-cost small-model tier, while still retaining capabilities close to frontier models Real-time chat, customer support, batch classification, simple code collaboration, high-concurrency API calls

There are two naming details worth noting.

First, the official name is Claude Haiku 4.5, not Claude 4.5 Haiku. Second, Claude Mythos Preview is not a mainstream available model for regular users or developers. It is a controlled research preview related to Project Glasswing, mainly aimed at defensive cybersecurity workflows, and should not be mixed into regular Claude model selection.

Opus: For the Hardest Problems

Opus is the tier Anthropic uses for its strongest models. The point of Claude Opus 4.7 is not being cheap or the fastest option, but being better suited to complex, multi-step tasks that require repeated verification.

It is better suited to these situations:

  • Large code changes across many files.
  • Complex system refactoring and architectural reasoning.
  • Long-chain Agent tasks.
  • Work requiring stronger visual understanding, document understanding, and multi-turn planning.
  • Enterprise analysis tasks where mistakes are costly.

If the cost of a single failed task is high, or you want the model to spend more time understanding context before acting, Opus is usually more worth trying.

Sonnet: The Default Starting Point for Most People

Claude Sonnet 4.6 is better suited as the default entry point. Its positioning is not “a lower-end Opus,” but rather a way to put sufficiently strong reasoning, coding, visual understanding, long context, and agent planning into a more controllable cost and speed profile.

For developers, the value of Sonnet 4.6 mainly comes from three points:

  1. It can handle very long context, making it suitable for codebases, contracts, reports, or multiple documents.
  2. It is easier to use as a regular model in Claude Code, API, and enterprise scenarios.
  3. It costs less than Opus, making it more suitable for high-frequency use.

If you do not know which Claude model to start with, Claude Sonnet 4.6 is usually the right beginning. Switch to Opus only when the task clearly needs stronger capability.

Haiku: When Fast and Affordable Matter More

Claude Haiku 4.5 is the small-model tier, but it should not simply be understood as a “weak model.” Anthropic positions it as fast and low cost while retaining capabilities close to frontier models.

It fits these scenarios:

  • Real-time chat and customer support bots.
  • Large-scale short-text classification.
  • Low-latency API calls.
  • Simple code edits and rapid prototypes.
  • Subtask execution in multi-Agent workflows.

If the task itself is clear, the context is not complex, and throughput matters, Haiku is often more reasonable than blindly using a larger model.

Claude’s Tool Capabilities

The Claude series is not just a set of chat models. Anthropic now places model capabilities inside multiple products and developer tools.

Claude Code is a command-line coding tool for developers. It can read codebases, edit files, run commands, and execute tests, making it suitable for sustained engineering work. Its experience depends heavily on the model’s code understanding, context management, and tool-calling stability.

Computer Use lets the model operate a desktop environment through screenshots, mouse actions, and keyboard input. It still needs to be used carefully, and the official documentation emphasizes running it in an isolated environment to avoid mistakes or security risks.

Artifacts is more of a Claude app-side experience. It can place code, page prototypes, charts, or document outputs into the interface for preview and iteration. It is not a standalone model, but part of the Claude product experience.

As for terms like “Managed Agents” or “self-evolving Agents,” be careful when writing about them. Anthropic is indeed strengthening Agent SDK, Claude Code, long context, tool use, and enterprise workflows, but it should not be described as already having uncontrolled self-evolution capability.

Access Options

Regular users can use Claude through the Claude.ai web app or mobile apps. Different plans affect available models, usage limits, and features.

Developers usually have several access options:

  • Anthropic Console and Claude API.
  • Amazon Bedrock.
  • Google Cloud Vertex AI.
  • Microsoft Foundry.

Specific available models, context windows, pricing, and regional support can change. Before development, it is best to rely on Anthropic’s official model documentation and the relevant cloud platform pages.

How to Choose

In actual use, you do not need to chase the strongest model from the beginning. A better approach is to tier model choice by task cost.

For everyday writing, code generation, long-document analysis, knowledge organization, and most Agent prototypes, start with Claude Sonnet 4.6. It is usually the best starting point for cost effectiveness and general capability.

If the task requires stronger complex reasoning, cross-file engineering changes, long-chain planning, or higher reliability, switch to Claude Opus 4.7.

If the task is simple, high-volume, and latency-sensitive, such as classification, summarization, customer support, or batch processing, put Claude Haiku 4.5 on the shortlist.

Claude’s model line is not simply “new versions replacing old versions.” It is a toolbox layered by task difficulty, speed, and cost. Choosing the right model matters more than blindly using the most expensive one.

References

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