Why it matters
- 200K token context window handles entire codebases, legal documents, and research papers that exceed GPT-4's limits.
- Computer Use is a unique capability for building agents that interact with real software — no other major API provider offers equivalent functionality.
- Constitutional AI training reduces harmful outputs and hallucinations — Claude tends to be more honest about uncertainty and less likely to confabulate.
- Best-in-class instruction following for complex prompts — Claude reliably follows detailed formatting, tone, and structural requirements.
Key capabilities
- Text generation: Single-turn and multi-turn conversation via Messages API.
- 200K context: Process entire codebases, legal documents, or research papers in one call.
- Vision: Analyze images, screenshots, charts, PDFs, and documents.
- Tool use: Function calling with parallel tool calls and agentic workflows.
- Computer Use: Control browsers and desktop applications via actions on screenshots.
- Streaming: Real-time token streaming via SSE.
- Batch API: Async batch processing at 50% cost discount for high-volume offline tasks.
- Prompt caching: Cache long system prompts for up to 90% cost reduction on repeated context.
- Extended thinking: Reveal Claude's reasoning process for complex problems.
Technical notes
- Models: claude-opus-4-6, claude-sonnet-4-6, claude-haiku-4-5
- Context: 200K tokens input; 8K tokens output (Sonnet/Opus)
- API format: REST; Messages API
- Python:
pip install anthropic
- TypeScript:
npm install @anthropic-ai/sdk
- Pricing: Haiku $0.25/M; Sonnet $3/M; Opus $15/M input tokens
- Free credits: $5 on sign-up
Usage example
import anthropic
client = anthropic.Anthropic(api_key="YOUR_ANTHROPIC_API_KEY")
message = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=1024,
messages=[
{"role": "user", "content": "Explain the difference between TCP and UDP in 3 sentences."}
]
)
print(message.content[0].text)
Ideal for
- Applications requiring 200K+ token context (legal documents, full codebase analysis, long-form content).
- Agentic workflows using Computer Use for browser and desktop automation.
- Enterprise teams prioritizing low hallucination rates and strong instruction following.
Not ideal for
- Image generation — Anthropic doesn't offer image generation; use DALL-E 3 or Stable Diffusion.
- Fastest possible inference — use Groq with Llama models for sub-200ms latency applications.
- Fully offline/on-premise deployment — Anthropic API is cloud-only (AWS Bedrock offers managed alternative).
See also
- Anthropic Python SDK — Detailed SDK documentation and examples.
- OpenAI API — Alternative frontier model API; compare for specific use cases.
- Vercel AI SDK — TypeScript SDK with native Anthropic support for web apps.