Anthropic releases Opus 5.5 and cuts pricing by 20%. Your agent calls might secretly get routed to an older model.

Anthropic releases Opus 5.5 and cuts pricing by 20%. Your agent calls might secretly get routed to an older model. Claude Opus 5.5 is here, and Anthropic has lowered the price. The new model, released on Tuesday, costs $4 per million input tokens and $20 per million output tokens, 20% less than Opus 5, with cache reads dropping to $0.20 per million from $0.50 and cache writes falling to $5 from $6.25. Anthropic puts overall savings closer to 40% because Opus 5.5 uses fewer tokens to complete a task and generates output more than 30% faster. Claude Code and the Claude Platform also get a fast mode that runs up to 2.5 times faster, priced at $8 per million input tokens and $40 per million output tokens. Anthropic says Opus 5.5 performs at roughly the level of Fable 5.1 on most work, though it comes out ahead on several agentic coding benchmarks. Opus 5.5 scored 66.4% on Terminal-Bench 4.0 compared with Fable 5.1’s 55.8%, and 54.4% on FrontierCode compared with 50.3%. The company suggests not reading too much into those margins. At this level, the company says a few points on a benchmark don’t translate into a noticeable difference in real-world use. Fable 5.1 costs $10 per million input tokens and $50 per million output tokens, more than twice the price of Opus 5.5. At default effort on FrontierCode, Opus 5.5 beats GPT-6 Astra at roughly 20% of the per-task cost. On CursorBench, it tops GPT-5.6 Sol by 11 points at about a third of the cost. Developers will still need to run their own evals before moving production workloads, but the cost difference could change which model makes sense for agentic coding. Developers will still need to run their own evals before moving production workloads, but the difference in cost could change which model makes sense for agentic coding. Fewer tokens, fewer agent steps The early enterprise numbers suggest the efficiency gains are real, at least on certain task profiles. Box reported that Opus 5.5 used about a third as many tokens as Opus 5 in its evaluations while producing answers that were 40% less verbose without losing accuracy. GitHub tested the model inside Copilot CLI and VS Code and found it completed more terminal tasks than Opus 5 in less than half the steps. Deloitte said Opus 5.5’s lowest-effort setting caught 72% of known bugs in code reviews, compared with 56% for Opus 5 at high effort, with fewer false alarms and less output. | Prices per 1M tokens | Claude Opus 5.5 | Claude Opus 5 | |---|---|---| | Cache reads | $0.20 | $0.50 | | Input tokens | $4 | $5 | | Output tokens | $20 | $25 | | Cache writes | $5 | $6.25 | Anthropic’s own internal testing backs up the pattern. In one head-to-head, both Opus 5.5 and Fable 5.1 translated HAProxy from C into Rust; both rewrites passed nearly all of HAProxy’s regression tests, but Opus 5.5 finished in 9.5 hours compared to 12 and cost 51% less. An early tester audited and fixed a 200,000-line codebase in under three hours, whereas Opus 5 took over 20 hours and burned 2.5x as many tokens. Another completed a 680,000-line code migration in less than a day. Although these were customer and internal evaluations, not standardized independent benchmarks, they point in the same direction - fewer tokens and fewer steps to finish the job. That pattern tracks with what’s happening across the industry. Agent performance depends heavily on the harness and runtime around the model, not only the model itself - agent failures often trace back to the orchestration layer rather than the model. Nvidia’s research showed that swapping the harness while keeping the model fixed could meaningfully change agent performance. | Benchmark | Opus 5.5 | Fable 5.1 | Opus 5 | GPT-6 Astra | GPT-5.6 Sol | |---|---|---|---|---|---| | Agentic coding (Terminal-Bench 4.0) | 66.4% | 55.8% | 52.3% | 57.9% | 37.3% | | Agentic coding (FrontierCode v1.1) | 54.4% | 50.3% | 48.0% | 53.3% | 47.5% | | Agentic coding (CursorBench 4.0) | 57.8% | 51.8% | 46.6% | - | 41.7% | | Knowledge work (GDPval-AA v2.1) | 1846 | 1735 | 1708 | 1542 | 1588 | | Business workflows (AutomationBench) | 40.0% | 31.4% | 26.9% | 41.4% | 28.8% | | Multidisciplinary reasoning (HLE) | 67.7% | 65.6% | 63.6% | 57.2% | - | | Agentic scientific research (TBS 0.1) | 58.7% | 52.6% | 29.0% | 64.6% | 22.4% | | Computer use (OSWorld 2.0) | 81.8% | 80.7% | 74.0% | - | - | | Visual chart recognition (Chartography) | 89.0% | 88.4% | 83.4% | - | - | Safety classifiers reroute mid-chain Opus 5.5 ships with the same class of safety classifiers already running on Fable 5.1 for cybersecurity, biology, and frontier LLM development. When a classifier fires, Anthropic reroutes the request transparently to an older model. Most flagged cybersecurity requests go to Opus 4.8. Biology and frontier LLM flags go to Opus 5. Anthropic says users can still identify and fix bugs in their own code with Opus 5.5. For anyone building agent workflows, this is the detail that needs architectural attention. A request sent to Opus 5.5 could, in fact, be handled by Opus 4.8 or Opus 5 instead, depending on whether Anthropic’s safeguards intervene. In a multi-turn agent workflow, that creates the possibility that individual requests are being handled by models with different capabilities, which could affect downstream steps. It’s also a source of inconsistency that may not show up in evals built on the assumption that every request goes to the same model. Vetted organizations can apply to Anthropic’s Life Sciences Verification Program to use Opus 5.5 without the biology classifier, and the company plans to expand its Cyber Verification Program to include the model in the coming weeks. The new cyber program will include three tiers for increasingly permissive trusted access, including access to Claude Mythos models. Opus 5.5 ships with the same class of safety classifiers already running on Fable 5.1 for cybersecurity, biology, and frontier LLM development. Alignment gains from cleaner training Anthropic says Opus 5.5 posted the strongest results of any model it has tested on its most comprehensive internal alignment evaluation, with improvements in behaviors the company says contributed to recent cybersecurity incidents, including biased reasoning and attempts to escape sandboxed environments. Frontier Design and METR evaluated the model before release. On the training side, Anthropic is tightening how it filters reinforcement learning environments after identifying flawed environments as a major source of misaligned behavior. That’s relevant beyond the safety framing because RL environment quality directly affects how a model behaves in agentic settings, where it chooses its own tools and decides when to change approach. The company is also building automated methods to generate new safety training scenarios and improve alignment rewards. Pricing pressure meets routing tradeoffs Opus 5.5 is the first model in the Claude 5.5 family, with Sonnet 5.5 and Haiku 5.5 expected over the coming weeks. Subscription users get a 20% increase in five-hour usage limits across all plans, while Anthropic says the lower cost of Opus 5.5 will make five-hour and weekly limits go 25% further. Subscribers will also get a banked rate-limit reset they can save for when they need more capacity. The release comes as API pricing across the frontier labs continues to fall. OpenAI cut its own API prices this summer, and Opus 5.5 pushes the competition beyond the headline price per token by reducing how many tokens some workloads require in the first place. Opus 5.5 pushes the competition beyond the headline price per token by reducing how many tokens some workloads require in the first place.