Claude 3.5 Haiku
Faster than Claude 3 Haiku with improved performance across multiple intelligence benchmarks.
Anthropic 
Amazon Bedrock Fast, capable text generation with large context
Claude 3.5 Haiku is a text generation model developed by Anthropic, positioned as the next generation of their fastest model in the Claude family. It supports a 200,000-token context window and has a training data cutoff of July 2024. The model is designed to deliver response speeds comparable to its predecessor, Claude 3 Haiku, while offering improved performance across a broader range of tasks and intelligence benchmarks.
Claude 3.5 Haiku is well-suited for applications that require low latency and high throughput, such as real-time chat interfaces, content classification, data extraction, and lightweight coding assistance. Its large context window makes it practical for tasks involving long documents or extended conversation histories. Developers looking for a balance between speed and capability within the Claude 3.5 generation will find it a practical option for production workloads.
What Claude 3.5 Haiku supports
Long Context Processing
Handles up to 200,000 tokens in a single context window, enabling analysis of long documents, codebases, or extended conversation histories in one pass.
Text Generation
Generates coherent, contextually relevant text for tasks including summarization, drafting, Q&A, and content classification.
Code Assistance
Supports code generation, explanation, and debugging across common programming languages, suitable for lightweight developer tooling and IDE integrations.
Low-Latency Responses
Optimized for speed, making it suitable for real-time applications such as chatbots, autocomplete, and interactive user-facing products.
Data Extraction
Can parse and extract structured information from unstructured text, supporting use cases like form processing and document parsing.
Instruction Following
Follows multi-step instructions and system prompts reliably, enabling consistent behavior in agent workflows and automated pipelines.
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Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 63.4% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 40.8% |
| MATH-500 | Undergraduate and competition-level math problems | 72.1% |
| AIME 2024 | American math olympiad problems | 3.3% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 31.4% |
| HLE | Questions that challenge frontier models across many domains | 3.5% |
| SciCode | Scientific research coding and numerical methods | 27.4% |
Common questions about Claude 3.5 Haiku
What is the context window size for Claude 3.5 Haiku?
Claude 3.5 Haiku supports a context window of 200,000 tokens, allowing it to process long documents or extended conversations in a single request.
What is the knowledge cutoff date for Claude 3.5 Haiku?
The model's training data has a cutoff of July 2024, meaning it does not have knowledge of events or information published after that date.
How is Claude 3.5 Haiku accessed on MindStudio?
Claude 3.5 Haiku is available on MindStudio under the model ID 'claude-3-5-haiku-bedrock', accessed via Amazon Bedrock. No separate API key setup is required when using it through MindStudio.
What types of tasks is Claude 3.5 Haiku best suited for?
It is designed for latency-sensitive applications such as real-time chat, content classification, data extraction, and coding assistance, where response speed is a priority alongside reasonable task complexity.
What input types does Claude 3.5 Haiku support?
Claude 3.5 Haiku is a text-based model. It accepts text inputs and produces text outputs, making it suitable for language tasks, instruction following, and code-related workflows.
What people think about Claude 3.5 Haiku
Community discussions referencing Claude models generally reflect interest in benchmark performance and cost-efficiency comparisons across the Claude model family. Users in the ClaudeAI subreddit have shared practical usage resources, suggesting an active base of developers and everyday users working with Claude models.
The Reddit threads found do not focus specifically on Claude 3.5 Haiku, so direct community sentiment about this model is limited in the available data. Discussions tend to center on newer or larger Claude releases, with Haiku-tier models implicitly valued for speed and affordability in production contexts.
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Documentation & links
Parameters & options
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