Claude (Anthropic) Cheat Sheet

Updated 2026-04-28

Next Topic: Constitutional AI and Alignment Cheat Sheet

Claude is a family of state-of-the-art large language models developed by Anthropic, built using Constitutional AI (CAI)—a safety-first training approach that embeds ethical principles directly into the model during both pre-training and fine-tuning. Unlike traditional RLHF-only methods, Constitutional AI uses AI feedback to self-critique and revise responses before human evaluation, creating models that are helpful, harmless, and honest by design. Claude excels at complex reasoning, coding, multimodal understanding, and agentic workflows, offering context windows up to 1 million tokens (Opus 4.7, Sonnet 4.6) with specialized features like adaptive thinking, prompt caching, tool use, and the Claude Managed Agents platform for production-grade autonomous agents. The current flagship, Claude Opus 4.7 (April 2026), introduces adaptive-only thinking, high-resolution vision (3.75MP), a xhigh effort level, and breaking API changes—while the research-preview Claude Mythos Preview demonstrates frontier cybersecurity capabilities through Project Glasswing.

What This Cheat Sheet Covers

This topic spans 20 focused tables and 132 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Model VariantsTable 2: Context and Token CapabilitiesTable 3: API Parameters and SamplingTable 4: Message Structure and RolesTable 5: Prompt Engineering FundamentalsTable 6: Advanced Prompting PatternsTable 7: Tool Use and Function CallingTable 8: Vision and MultimodalTable 9: Streaming and ResponsesTable 10: Safety and AlignmentTable 11: Cost OptimizationTable 12: Rate Limits and QuotasTable 13: Error Handling and ReliabilityTable 14: SDKs and IntegrationTable 15: Extended Thinking and ReasoningTable 16: Embeddings, RAG, and RetrievalTable 17: Benchmarks and PerformanceTable 18: Pricing (2026)Table 19: Agentic Workflows and AutomationTable 20: Claude Products and Memory

Table 1: Model Variants

Model	Example	Description
Claude Opus 4.7	`claude-opus-4-7`	• Most capable generally available model (April 16, 2026) • adaptive thinking only; high-res vision (3.75MP / 2576px); 128K max output • 1M context window at standard pricing • 70% CursorBench (vs 58% Opus 4.6); 3× more production tasks solved • $5/$ 25 per MTok; updated tokenizer uses 1.0–1.35× more tokens.
Claude Sonnet 4.6	`claude-sonnet-4-6`	• Best balance of speed and intelligence; default for most production workloads • extended thinking + adaptive thinking; 1M context; 64K max output • $3/$ 15 per MTok; ~30–50% faster than Sonnet 4.5.
Claude Haiku 4.5	`claude-haiku-4-5`	• Fastest and most cost-effective model • extended thinking + adaptive thinking; 200K context; 64K max output • $1/$ 5 per MTok; best for high-throughput tasks, classification, customer support.

Table 1: Model Variants

Model	Example	Description
Claude Opus 4.7	`claude-opus-4-7`	• Most capable generally available model (April 16, 2026) • adaptive thinking only; high-res vision (3.75MP / 2576px); 128K max output • 1M context window at standard pricing • 70% CursorBench (vs 58% Opus 4.6); 3× more production tasks solved • $5/$ 25 per MTok; updated tokenizer uses 1.0–1.35× more tokens.
Claude Sonnet 4.6	`claude-sonnet-4-6`	• Best balance of speed and intelligence; default for most production workloads • extended thinking + adaptive thinking; 1M context; 64K max output • $3/$ 15 per MTok; ~30–50% faster than Sonnet 4.5.
Claude Haiku 4.5	`claude-haiku-4-5`	• Fastest and most cost-effective model • extended thinking + adaptive thinking; 200K context; 64K max output • $1/$ 5 per MTok; best for high-throughput tasks, classification, customer support.