Model comparison
Claude Haiku 4.5 vs Claude Sonnet 4.6
Claude Sonnet 4.6 supports a dramatically larger token context window of 1,000,000 tokens compared to Claude Haiku 4.5's 200,000 tokens, enabling significant differences in application potential.
Anthropic
Claude Haiku 4.5
Fast, cheap, surprisingly capable for high-volume jobs.
Anthropic
Claude Sonnet 4.6
The pragmatic default — Claude quality without Opus pricing.
Specs
| Metric | Claude Haiku 4.5 | Claude Sonnet 4.6 |
|---|---|---|
| Context window | 200K tokens | 1M tokens↑ |
| Input $/1M tokens | $1.00↑ | $3.00 |
| Output $/1M tokens | $5.00↑ | $15.00 |
| Modalities | Image · Text | Text · Image |
| Open weights | No | No |
| Released | Oct 2025 | — |
How they differ
Context handling
Claude Haiku 4.5
Claude Haiku 4.5 is limited to processing contexts of up to 200,000 tokens, making it suitable for moderately long documents or applications.
Claude Sonnet 4.6
Claude Sonnet 4.6 can handle up to 1,000,000 tokens, accommodating expansive multi-document workflows or complex context requirements.
Cost profile
Claude Haiku 4.5
Claude Haiku 4.5 costs $1.0/1M input tokens and $5.0/1M output tokens, offering a more economical option for smaller tasks.
Claude Sonnet 4.6
Claude Sonnet 4.6 costs $3.0/1M input tokens and $15.0/1M output tokens, reflecting its capability to manage extensive inputs and outputs.
Vision
Claude Haiku 4.5
Claude Haiku 4.5 supports both image and text inputs, providing multimodal interaction within its token constraints.
Claude Sonnet 4.6
Claude Sonnet 4.6 also supports image and text inputs, leveraging its higher token limit for larger or more complex multimodal setups.
Claude Haiku 4.5 — what sets it apart
- +Claude Haiku 4.5 is designed for shorter interaction sequences with faster response times and lower costs.
- +Its lower token context may restrict its usability for tasks requiring extensive input analysis.
Claude Sonnet 4.6 — what sets it apart
- +Claude Sonnet 4.6 enables in-depth contextual analysis across 1,000,000 tokens, suitable for handling large datasets or multi-document scenarios.
- +Its higher costs align with its scalability for complex problem-solving tasks.
Claude Sonnet 4.6's support for a significantly larger token context window is the most consequential difference, impacting its suitability for handling extensive workflows.
Analysis synthesized from gpt-4o, llama-4-maverick, phi-4, etc.