Anthropic Claude 4: Opus 4.7, Sonnet 4.6 and What's New

Understanding the Claude 4 Family Structure

Anthropic organises Claude into three tiers that serve different use cases and budgets. Claude Opus is the most capable model, designed for complex reasoning, nuanced analysis, and tasks where quality is the primary concern over speed or cost. Claude Sonnet is the mid-tier workhorse — competitive capability at a fraction of Opus cost, suited for the majority of production applications. Claude Haiku is the lightweight, fast, cheap model ideal for high-volume, lower-complexity tasks.

The latest updates bring Opus 4.7 as the top-of-family model and Sonnet 4.6 as the default model recommended for most API use cases. Sonnet 4.6 is also the model powering Claude Code — Anthropic's AI coding tool — making it one of the most widely deployed Claude models for developer-facing applications.

Claude Opus 4.7 — What Is New

Opus 4.7 builds on Opus 4's strong foundation in complex reasoning and multi-step planning. The key improvements in 4.7 are:

• Better long-context coherence: When working with very long documents (200,000+ tokens), Opus 4.7 maintains argument coherence and cross-references information across the full context more accurately than 4.0. This is particularly valuable for legal document analysis, large codebase review, and lengthy research synthesis.
• Improved instruction following at scale: Complex system prompts with many conditional instructions are followed more precisely, reducing the need for prompt engineering workarounds
• Extended thinking improvements: The extended thinking mode — where Claude reasons step-by-step through a problem before answering — is noticeably more systematic and less likely to reach conclusions that contradict the reasoning chain
• Tool use reliability: Multi-tool agentic workflows where Claude must call multiple tools in sequence show fewer errors and better error recovery when a tool call fails

Claude Sonnet 4.6 — The Default Workhorse

Sonnet 4.6 is where most production workloads will run. At roughly one-fifth the cost of Opus while delivering 80–90% of its capability on typical tasks, Sonnet 4.6 is the right choice for the vast majority of API use cases. Key Sonnet 4.6 improvements include:

• Code generation quality: Sonnet 4.6 closes the gap with Opus on standard coding tasks — writing functions, debugging, code review, and documentation generation. For most coding assistant applications, Sonnet 4.6 is now sufficient without needing Opus.
• Faster response times: Latency improvements across the board — particularly on shorter completions — make Sonnet 4.6 more responsive for interactive applications
• Better structured output: JSON mode and tool use return more reliably formatted outputs with fewer truncation or formatting errors, reducing the need for client-side parsing workarounds

Claude Code — Major Updates

Claude Code is Anthropic's terminal-based AI coding assistant powered by Sonnet 4.6. The latest version brings several significant updates that affect how developers use it day-to-day:

The Agent SDK now supports multi-agent workflows where Claude Code can spawn sub-agents for parallel tasks — for example, one agent handling test writing while another handles implementation, then a third reviews the combined output. This enables significantly more complex automated development workflows than single-agent interactions allowed.

The Claude Code CLI now has persistent memory across sessions — it can remember project-specific context, coding conventions, and architectural decisions across multiple working sessions without requiring re-explanation each time. For Indian developers working on large projects over weeks or months, this eliminates a significant friction point.

The MCP (Model Context Protocol) integration is now production-stable, allowing Claude Code to connect to external data sources — databases, APIs, documentation sites, issue trackers — and use them as context in real time. Indian developers can connect Claude Code to their company's internal Confluence wikis, GitHub issues, or SQL databases directly.

Extended Thinking Mode — When to Use It

Extended thinking is Anthropic's implementation of visible chain-of-thought reasoning. When enabled, Claude works through a problem step-by-step in a thinking block before producing the final response. This costs more (thinking tokens are billed) and takes longer, but produces substantially better results on hard problems.

Extended thinking is worth enabling when:

• The problem has multiple valid approaches and you need Claude to evaluate trade-offs (system design decisions, algorithm selection)
• Mathematical or logical reasoning is required with multiple dependent steps
• You need a decision with explicit justification that can be reviewed and audited
• The task involves risk — medical, legal, financial — where error cost is high

For most routine tasks (content generation, code completion, classification), standard mode without extended thinking delivers equivalent quality at lower cost and latency.

Prompt Caching — Essential for Cost Control

Anthropic's prompt caching feature — where repeated prefixes in system prompts or large documents are cached and billed at 90% less than regular input tokens on cache hits — is one of the most important cost-reduction tools available on the Claude API. For Indian developers building production applications with large system prompts or document contexts, enabling cache_control on the cacheable prefix reduces per-request costs dramatically.

A practical example: if you have a 20,000-token system prompt describing your application's context, and you send 10,000 API calls per day, without caching that system prompt costs approximately ₹12,000/day at Sonnet rates. With caching active, after the first call the system prompt portion costs 90% less — reducing to approximately ₹1,800/day for the system prompt component. For high-volume Indian applications, this is a significant operational cost item.

Claude vs GPT-5 vs Gemini Ultra 2 — Where Claude Wins

In the context of the current frontier model competition, Claude 4 retains clear advantages in specific areas:

• Instruction following precision: Claude consistently follows complex, multi-part instructions more precisely than GPT-5 or Gemini in evaluation. This matters for enterprise applications with detailed system prompts.
• Long document analysis: On 100,000+ token documents, Claude Opus 4.7 is among the best at maintaining accuracy throughout without drifting or losing track of earlier context
• Safety and refusal calibration: Claude is notably better calibrated — it refuses genuinely harmful requests while being helpful on edge cases that less calibrated models refuse unnecessarily
• Code review and architectural feedback: Claude Opus and Sonnet are preferred by many developers specifically for code review — the explanations are clear, the suggestions are actionable, and the model accurately identifies the root cause rather than surface symptoms