Anthropic Sonnet 4.6 Delivers Opus-level Results at One-Fifth the Token Cost

Anthropic's Sonnet 4.6 collapses the cost-performance trade-off for enterprise AI: it reaches near-Opus accuracy while costing about one-fifth per million tokens. With a 1,000,000-token context window and headline pricing at $3/$15 per million tokens, Sonnet 4.6 turns continuous, agent-driven workloads into a practical production expense for organizations that make thousands of API calls daily.

Benchmarks show the model closing gaps that previously justified moving to expensive tiers. On core coding tests Sonnet 4.6 posts a 79.6% SWE-bench score versus Opus 4.6's 80.8%. Its 72.5% OSWorld computer-use result nearly matches Opus 4.6's 72.7%, and it posts a higher office-task Elo (1633 vs 1606 for Opus).

Real-world tests reinforce the numbers. Users favored Sonnet 4.6 over Sonnet 4.5 about 70% of the time, and preferred it to Opus 4.5 59% of the time for day-to-day developer work. In a long-horizon business simulation Sonnet 4.6 finished near $5,700 versus Sonnet 4.5's ~$2,100, evidence of stronger strategic planning across months, not minutes.

Operational capabilities matter here: the model's improved screen-automation proficiency unlocks legacy systems without custom connectors. Anthropic reports a near fivefold rise in computer-use scores over 16 months, from under 15% to roughly 72.5%, lowering integration friction for ERPs, insurance portals, and medical scheduling tools. The company also highlights stronger resistance to prompt-injection vectors, a critical hardening for agents that browse and interact autonomously.

Sonnet's commercial timing intersects with Opus 4.6's platform-focused advances: Opus raises context capacity to one million tokens and expands output length support, while Anthropic's Claude platform has been adding agent-oriented engineering primitives—coordinated agent teams and durable Task graphs—that make multi-step engineering work resumable and auditable. That combination matters because buyers now decide on two linked questions: which model delivers the desired agent behavior and long-context reasoning, and which model makes the recurring token bill affordable at production scale. Sonnet 4.6's price-performance shifts that second axis dramatically.

Market consequences are immediate. Firms that ran small pilot fleets can now scale agents continuously because the marginal token cost has dropped materially. Strategic partnerships and regional expansion—most notably an India office and an integration agreement with Infosys—signal Anthropic is pushing Sonnet 4.6 into regulated enterprise stacks. The model is live across Claude plans, developer tools, and the API under the identifier claude-sonnet-4-6, so migration can start without delay.

Ecosystem activity around Opus and Claude underscores the enterprise framing: integrations with productivity and IT platforms (examples announced across the ecosystem include Asana, ServiceNow and GitHub integrations for agent workflows), growing commercial run‑rates for Claude Code, and competing platform plays such as OpenAI's Frontier preview all shift evaluation away from raw benchmarks toward governance, connector quality, auditability and billing models. For procurement teams, Sonnet 4.6 therefore reframes trade-offs—teams can prioritize orchestration and connectors while using Sonnet to control inference costs, or choose Opus-class instances when specific feature primitives or longer native output lengths are required.

For competitors, the dynamic is stark: either justify premium tiers with features that materially improve developer/productivity outcomes (resumability, multi-agent coordination, native long outputs), or compress pricing to reflect Sonnet-level marginal economics. For customers, the net effect is faster rollouts, more aggressive agent pilots, and a sharper vendor focus on integration, governance, and safety tooling rather than solely on single-run model accuracy.