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const Anthropic = require('@anthropic-ai/sdk');
const api = new Anthropic({
baseURL: 'https://api.ai.cc/',
authToken: '',
});
const main = async () => {
const message = await api.messages.create({
model: 'anthropic/claude-haiku-4.5',
max_tokens: 2048,
system: 'You are an AI assistant who knows everything.',
messages: [
{
role: 'user',
content: 'Tell me, why is the sky blue?',
},
],
});
console.log('Message:', message);
};
main();
import asyncio
from anthropic import Anthropic
client = Anthropic(
base_url="https://api.ai.cc/",
auth_token="",
)
def main():
message = client.messages.create(
model="anthropic/claude-haiku-4.5",
max_tokens=2048,
system="You are an AI assistant who knows everything.",
messages=[
{
"role": "user",
"content": "Hello, Claude",
}
],
)
print("Message:", message.content)
if __name__ == "__main__":
main()
-
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Product Detail
✨ Overview: Claude 4.5 Haiku
Claude 4.5 Haiku is Anthropic's cutting-edge lightweight AI model, delivering near-frontier-level capabilities with exceptional speed and cost efficiency. It is engineered to power real-time, interactive applications like advanced chat assistants, intelligent coding tools, and complex multi-agent workflows. Haiku 4.5 significantly enhances AI accessibility by providing state-of-the-art performance at a fraction of the cost and with much lower latency, making advanced AI more attainable for diverse applications.
🚀 Technical Specifications
- Model Class: Lightweight variant of Claude 4 series
- Coding Performance: Matches Claude Sonnet 4 with 90% effectiveness in agentic coding tasks.
- Speed: Up to 2x faster than Sonnet 4.
- Context Window: Supports very long contexts (e.g., up to 200,000 tokens reported).
- Output Token Limit: Large max output tokens for extended generation capabilities.
📊 Performance Benchmarks
- SWE-bench Verified: Achieved a 73.3% score, closely trailing Sonnet 4.5's 77.2%, positioning it as one of the best coding AI models globally.
- Agentic Coding: Provides robust support for multi-agent orchestration with high responsiveness.
- Instruction Following: Demonstrates 65% accuracy on slide text generation, outperforming several premium-tier models.
- Speed & Responsiveness: Operates 4-5x faster than Sonnet 4.5, enabling seamless real-time AI-assisted development.
- Safety & Alignment: Classified as AI Safety Level 2 with statistically significantly lower misalignment rates compared to Sonnet 4.5 and Opus 4.1.
Visual representation of Claude 4.5 Haiku's performance.
💡 Key Features
- High-speed, cost-efficient coding support: Perfect for rapid prototyping, multi-agent coding environments, and collaborative pair programming.
- Parallel task management: Seamlessly works alongside larger Claude models (e.g., Sonnet 4.5) to efficiently delegate subtasks in complex multi-step workflows.
- Enhanced real-time interactivity: An ideal choice for dynamic chatbots, responsive customer service AI, and agentic systems demanding instant responses.
- Advanced reasoning support: Capable of deep problem-solving combined with rapid output generation for intricate challenges.
💲 API Pricing
- Base Input Tokens: $1.05 (per million tokens)
- Output Tokens: $5.25 (per million tokens)
🎯 Use Cases
- Real-time chat assistants and conversational AI services.
- Customer support automation with low latency responses.
- AI pair programming and accelerated code generation.
- Agent orchestration for complex workflows involving multiple AI instances.
- Rapid prototyping of software with interactive AI support.
💻 Code Sample
While a specific code snippet isn't provided here, developers can integrate Claude 4.5 Haiku via Anthropic's API for various applications. The interaction typically involves sending prompts and receiving AI-generated responses, similar to other large language models.
↔️ Comparison with Other Models
vs Claude 4.5 Sonnet: Haiku 4.5 offers nearly identical coding performance at roughly one-third of the cost and twice the speed. Sonnet 4.5 remains a frontier model with slightly higher accuracy but comes with higher costs and latency.
vs Claude 3.5 Haiku: Haiku 4.5 introduces substantial speed and cost improvements while matching or surpassing the performance benchmarks of its predecessor. It also boasts an AI Safety Level 2 classification with improved alignment and reduced risks.
vs Opus 4.1: Haiku 4.5 is faster, more cost-effective, and safer, demonstrating statistically lower misalignment behaviors. It also outperforms Opus 4.1 in coding tasks and agentic workflow support.
vs GPT-5: Haiku 4.5 is an excellent choice for developers prioritizing speed, cost, and reliability in coding and interactive AI applications. In contrast, GPT-5 is generally suited for scenarios demanding advanced reasoning and multimodal capabilities with flexible configurations.
Comparative performance overview of Claude models.
❓ Frequently Asked Questions (FAQ)
Q: What is Claude 4.5 Haiku AI model?
A: Claude 4.5 Haiku is Anthropic's fastest and most cost-efficient model in the Claude 4.5 series, engineered for quick responses, strong reasoning, and excellent performance across various tasks while maintaining high quality and reliability.
Q: What are the key advantages of Claude 4.5 Haiku?
A: It offers exceptional speed, cost-effectiveness, strong reasoning abilities, reliable performance, quick response times, and efficient resource usage, all while adhering to Anthropic's ethical AI principles.
Q: How fast is Claude 4.5 Haiku compared to other Claude models?
A: As the 'Haiku' variant, it is specifically optimized for speed, typically responding 2-3 times faster than larger Claude models while maintaining excellent quality for most practical applications.
Q: What types of tasks is Claude 4.5 Haiku particularly good at?
A: Claude 4.5 Haiku excels at quick analysis, real-time conversations, content moderation, data processing, customer support, text summarization, and any application requiring fast, reliable responses with strong reasoning capabilities.
Q: Does Claude 4.5 Haiku support multi-turn conversations?
A: Yes, Claude 4.5 Haiku effectively handles multi-turn conversations with strong context retention, making it ideal for chat applications, customer service, and interactive AI experiences.
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