Claude Sonnet 4.6: How 1 Million Token Context Changes AI Agents
Anthropic just dropped Sonnet 4.6, and the numbers are striking: 1 million token context window at roughly half the price of Opus ($3M input vs $5M, $15M output vs $25M). This isn't just incremental—it's a complete shift in what's economically feasible for AI agents.
What Changed
Previous models forced developers into painful tradeoffs:
- Dump everything into context and hit limits
- Build complex retrieval systems to chunk documents
- Pay premium for the best reasoning (Opus)
Sonnet 4.6 eliminates most of these constraints:
| Capability | Sonnet 4.5 | Sonnet 4.6 |
|---|---|---|
| Context | ~200K tokens | 1M tokens |
| Input price | $3/M tokens | $3/M tokens |
| Output price | $15/M tokens | $15/M tokens |
| Computer use | 14.9% → 72.5% | Improved |
Real Impact on Agent Workflows
Here's what becomes possible:
Whole codebases in memory: An agent can now hold an entire monorepo, not just the relevant files. This dramatically reduces the engineering complexity of context-aware coding agents.
Multi-hour conversations without loss: Customer service agents can maintain full conversation history plus knowledge base without forgetting context.
Agent "memory" simplifies: Instead of building complex retrieval systems, you can just dump relevant context and let the model reason across it.
The Cost Math
For agent-heavy workflows making hundreds of API calls:
- Old: Using Opus for 500 calls × 10K context each = ~$50/task
- New: Using Sonnet 4.6 = ~$10-12/task
That's a 4-5x budget extension, making sustained agent workflows economically viable for many more use cases.
What This Means for Product Teams
- Simpler architectures: Build retrieval-first later; start with context
- New use cases become viable: Long-document analysis, comprehensive code review, detailed customer context
- Price war begins: Expect other providers to match pricing
The agent cost-performance equation just changed. If you were holding back on agent implementations due to cost, it's time to revisit.
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