Anthropic Launches Claude Opus 5 with Frontier Coding Capabilities at Lower Cost

Anthropic Launches Claude Opus 5 with Frontier Coding Capabilities at Lower Cost Anthropic has released Claude Opus 5, a model approaching the intelligence of Claude Fable 5 at half the price while maintaining the same pricing as Opus 4.8. Claude Opus 5 achieves state-of-the-art scores on Frontier-Bench v0.1 and comes within 0.5% of Fable 5 on CursorBench 3.2 at half the cost per task. The model improves on Opus 4.8 across all life sciences benchmarks, gaining 10.2 percentage points in molecular structure inference and 7.7 percentage points in protein variant effect prediction. Anthropic behavioral audits show Opus 5 is its most aligned model to date, while deliberately remaining behind Mythos 5 in biological research and offensive cyber exploitation. Pricing is set at $5 per million input tokens and $25 per million output tokens, matching Opus 4.8, with an optional 2.5x Fast mode at double the price. Software Engineering and Problem-Solving Performance Claude Opus 5 becomes the new default model on Claude Max and the top model on Claude Pro. On Frontier-Bench v0.1, the model surpasses all competing systems and more than doubles the performance of Opus 4.8 at a lower cost per task. At maximum effort on CursorBench 3.2, Opus 5 performs within 0.5% of Fable 5 while halving the task cost, alongside establishing new state-of-the-art benchmarks on GDPval-AA. Domain Gains Across Science and Industry Workflows In life sciences evaluations covering structural biology, organic chemistry, and bioinformatics, Opus 5 exceeded Opus 4.8 across every test. Notable improvements include a 10.2 percentage point gain on spectroscopy-based molecular structure inference and a 7.7 percentage point increase on protein sequence function predictions. Early-access partners reported major gains across financial modeling, automation sequences, and multi-step codebase architecture tasks, noting stronger self-verification and reduced execution variance. Safety Profile and Dual-Use Capability Limits Pre-deployment testing found Opus 5 achieved the highest adherence to Claude's Constitution and lowest rates of deceptive behavior among Anthropic models, outperforming Opus 4.8, Sonnet 5, and Fable 5. Anthropic avoided training Opus 5 on cyber tasks to restrict dual-use hazards; although it approaches Mythos 5 in finding source code vulnerabilities, evaluations on OSS-Fuzz show it lags substantially behind Mythos 5 in exploit generation. Mythos 5 also remains more capable in long-running autonomous biological research. Safeguards, Integration, and Commercial Terms Opus 5's cybersecurity classifiers allow source code vulnerability discovery but block binary-based scanning, exploit generation, and penetration testing, triggering roughly 85% less often than those on Fable 5. Blocked cyber requests fall back to Opus 4.8 by default, while vetted users can access fewer restrictions via the Cyber Verification Program. The model is available on the Claude API and supported interfaces for $5 per million input tokens and $25 per million output tokens, with a 2.5x speed Fast mode priced at twice the base rate.

Anthropic 发布 Claude Opus 5：性能大幅提升且保持原价 Anthropic 推出新模型 Claude Opus 5，在编程、专业知识及科学研究基准上取得显著提升，以与 Opus 4.8 相同的价格提供了接近 Claude Fable 5 的智能水平。 Opus 5 维持每百万输入词元 5 美元、输出词元 25 美元的定价，并提供约 2.5 倍速的 Fast 模式。 在 Frontier-Bench v0.1 等编码基准及生命科学任务中表现超越前代，具备更强的工作自检与多步骤自主处理能力。 模型在对齐测试中欺骗行为率最低，在网络漏洞利用及高风险生物研究方面未推进前沿，仍落后于 Mythos 5。 基准评估与专业任务表现 Opus 5 成为 Claude Max 的默认模型和 Claude Pro 的最强模型。在 Frontier-Bench 和 GDPval-AA 等评估中创下新高，在 CursorBench 上以一半成本达到接近 Fable 5 峰值得分的表现。在生命科学评估中，Opus 5 全面超越 Opus 4.8，尤其在有机化学推断分子结构和蛋白质序列变异预测任务中表现提升明显。此外，模型在视觉输出和错误自我检查方面也有实质改进。 早期客户落地应用反馈 来自 Devin、Cursor、Zapier、Box 及 JetBrains 等早期接入团队的测试表明，Opus 5 在复杂调试、端到端自动化流程、金融建模与法律分析中展现出更强的稳定性和判断力。客户反馈指出，模型在长流程智能体工作中能够主动规划、反思假设，并在保持或提高准确率的同时显著减少轮次与词元消耗。 对齐安全与防护边界 测试显示 Opus 5 恪守宪法原则的表现优于前代模型，误导与鲁莽操作率更低。在双重用途风险控制上，该模型有意避免了专门的网络安全训练；虽然其发现漏洞的能力接近 Mythos 5，但在漏洞利用开发上仍远落后。其安全分类器放宽了源码漏洞排查，但阻断二进制扫描和漏洞利用生成，并提供网络验证计划（CVP）供合规机构使用。 定价与可用性 Claude Opus 5 即日起在所有平台开放，开发者可通过 Claude API 调用，基准价格为输入每百万词元 5 美元、输出每百万词元 25 美元。双倍价格下支持约 2.5 倍速的 Fast 模式。通用访问继续保持无数据保留的要求。

Claude Opus 5 is available today. It’s a thoughtful and proactive model that comes close to the frontier intelligence of Claude Fable 5 at half the price. On coding and knowledge work evaluations like [Frontier-Bench](https://www.frontierbench.ai/) and [GDPval-AA](https://artificialanalysis.ai/evaluations/gdpval-aa), Opus 5 is the new state-of-the-art, though it remains behind Mythos 5 on cybersecurity tasks. Opus 5 is designed to be used every day: it works more efficiently than other models. It’s the new default model on Claude Max, and the strongest model on Claude Pro. Claude Opus 5 provides greatly improved performance for the same cost as its predecessor, Opus 4.8. The charts in this section show how performance changes according to the model’s effort setting, which customers can use to optimize for intelligence or conserve tokens for faster and cheaper results. Opus 5 excels on valuable software engineering tasks. For example, on **Frontier-Bench v0.1,** Opus 5 surpasses all other models, and more than doubles Opus 4.8’s performance at a lower cost per task. On **CursorBench 3.2**, at max effort, the model performs within 0.5% of Fable 5’s peak score, but at half the cost per task; it also achieves greater performance at a given cost than all other models on high, xhigh, and max effort. We see similar results on knowledge work and problem-solving tasks. For example: It’s also our best and most cost-efficient model on several related evaluations: Opus 5 is a meaningful improvement over Opus 4.8 for scientific research. It shows better performance than Opus 4.8 on every one of our life sciences evaluations, which cover topics including structural biology, organic chemistry, and bioinformatics. Its improvements are most notable on organic chemistry tasks, like inferring molecular structures from spectroscopy data (it scores 10.2 percentage points higher than Opus 4.8 on our internal benchmark), and on protein-related tasks like predicting how variations in a protein’s sequence affect how it functions (here, it scores 7.7 percentage points higher). Finally, Opus 5 is capable of producing much stronger visual outputs: Claude Opus 5 is much stronger at verifying its work and iterating carefully until it succeeds. In evaluations and early-access testing, we and our users found many examples of Opus 5’s agency and thoroughness: Below are further reports from our early-access customers on their experience of working with Opus 5: On FrontierCode 1.1, Claude Opus 5 approaches Fable-level performance at half the cost. Within Devin, it also shows particular strength on difficult debugging and root-cause analysis tasks.Scott Wu CEO Claude Opus 5 delivers near Fable 5 intelligence at Opus speed and cost. On CursorBench it’s just under Fable 5 and has many of the same behaviors. We are excited to see how developers use it in Cursor.Sualeh Asif Co-Founder Claude Opus 5 topped Zapier’s AutomationBench leaderboard without spending more tokens than prior Claude models. It took a raw account-health workbook and ran a full churn-prevention sequence end to end: flagging at-risk accounts, alerting the right owner, and summarizing for retention ops. Previous models didn’t pass; Opus 5 hit 100%.Wade Foster CEO On our genomics analysis work, Claude Opus 5 behaves more like a careful scientist than any model we’ve run. It reaches for the right statistical tests to rule out confounders, cross-checks its own results by independent methods, and stays on track through long multi-step analyses.Alfredo Andere CEO Claude Opus 5 came out ahead of every model in its family on our internal evals. It isn’t just better on our hardest agentic coding tasks, up 22% over Opus 4.7, it’s steadier, with far less variance run to run. For the millions of builders on Lovable, that consistency is the whole game. Reliable results, build after build.Fabian Hedin Co-Founder Claude Opus 5 is the biggest leap in the Opus family since 4.5. On the same full-stack app builds, the front end shows it first: the best animations, games, and 3D work we have seen from an Opus model.Madhav Jha Co-Founder and CTO We’re loving Claude Opus 5. For the kind of open-ended analytical work our agent handles, it’s a strict upgrade over Opus 4.8, and the gains are biggest exactly where it matters: the harder, vaguer tasks. Responses are clearer and more concise, and we see improved efficiency at higher effort levels too.Izzy Miller AI Research Lead Claude Opus 5 is a striking improvement over Opus 4.8 for the financial research workflows our analysts run every day. It stands out on numerical reasoning, table work, and sharper critical thinking where precision matters.Shirley Zhang Senior AI Engineer, Applied AI Claude Opus 5 delivers the industry intelligence and accuracy that is essential for the analysis of specialized enterprise content. Box found that Opus 5 outperforms Opus 4.8 by 8% and delivers notable performance gains in the data analysis (11% improvement) and due diligence (17% improvement) workflows that technology, healthcare, and public sector organizations rely on daily.Ben Kus CTO Claude Opus 5 is a clear generational step up from Opus 4.8. Over one weekend I gave it a chief-of-staff role over my dev environments: it built its own monitor, drove each box, and pulled me in only for the judgment calls.Cristian Rivera Staff Software Engineer Claude Opus 5 made large scale changes across our Fundamental Research Assistant codebase, adapting to feedback throughout an agentic workflow and explaining its reasoning more clearly than any model we’ve used. It handled work we would normally have broken into much smaller pieces.Conor Kiernan CTO On some of our hardest financial-modeling tasks, Claude Opus 5 is a clear step up from Opus 4.8 in both accuracy and efficiency. Its performance floor is materially higher, especially on deep finance domain logic. Across effort levels it averaged 9 percentage points higher accuracy with a third fewer turns and tool calls and 60% less time.Richard Pham Evals and Product Lead Claude Opus 5 checks its own work the way a real frontend developer would. On our benchmark it opened its pages in a browser at desktop and phone widths, caught a product hidden below the mobile fold and an off-screen checkout button, and fixed both before handing the work back.AJ Orbach Co-Founder and CEO Claude Opus 5 is a clear step up in performance on legal agent work compared to prior Opus models, and we saw the biggest gains in practice areas like corporate governance and arbitration. We were also impressed with Opus 5’s ability to maintain quality at lower reasoning levels, achieving similar performance while generating 26% fewer tokens on average compared to Opus 4.8 at max reasoning.Niko Grupen Head of Applied Research Claude Opus 5’s biggest gains for us are on longer-horizon work: building a full deck, then revising it. Artifact quality is what decides which model we ship, and this is the clearest step up we’ve seen — better visual understanding, cleaner formatting, fewer slide issues.Alex Wang Applied AI Claude Opus 5’s judgment is what stands out. Handing off a PR, it doesn’t rush to publish: it verifies the branches, checks the template, and thinks through test implications so the handoff is clean. The older models tended to jump ahead and get caught on our checks.Zimu Li Member of Technical Staff During a rearchitecting session, Claude Opus 5 pushed back on a design I proposed, and it didn’t fold when I insisted. Instead, it explained exactly what was valuable in my idea, narrowed its objection to a single design question, and proposed a compromise that kept the good part while fixing the flaw. That’s the kind of judgment that lets us trust it with less oversight.Marquis Wang Principal AI Engineer On first-turn redlines, Claude Opus 5 scored the highest of any model we tested, nearly double Opus 4.8. Commenting is better too: on NDAs it gets to the redline in less time and with fewer passes, with accuracy maintained or better.Ryan Tanenholz Member of Technical Staff Claude Opus 5 writes clean, tight diffs with no dead code, and it’s the stronger hazard spotter on subtle, codebase-specific issues. We’re adopting it for production workloads.Neeraj Deshmukh Director of Engineering We will definitely migrate a number of use cases in Cosmos, our unified agent platform. We’re looking forward to increasingly using Claude Opus 5 for code review, and I am confident in saying we would rather people be using Opus 5 than Opus 4.8.Igor Ostrovsky Co-Founder and CTO What stands out about Claude Opus 5 is judgment. It thinks harder before it writes a single line, catches its own logical faults during planning rather than after the fact, and reasons about why an answer is right, not just whether it works. It’s the clearest jump in problem-solving we’ve seen from one Claude model to the next, and we’re looking forward to seeing it adopted in JetBrains IDEs.Denis Shiryaev Head of AI in IDE Claude Opus 5 is the strongest Opus model we’ve tested on our trading benchmark, and it gets there using roughly a seventh of the reasoning tokens and under half the latency of Opus 4.8. Better answers at a fraction of the compute.Matt Nassr Head of Global Data Engineering and AI Transformation Claude Opus 5 lets monitoring agents manage parts of their own memory in production, making them more autonomous and reliable over longer horizons. The agent treats its context as a living document: after flagging a potential anomaly in one of our services, it re-checked its own assumption against production, found the signal was benign, wrote the correction into its memory, and retired its monitoring queries on its own.Tanapat Ratanaruengjumrune Manager, Applied AI Claude Opus 5 is a strong agentic coding model built for long-running, multi-step work. It deeply understands your codebase, holds the thread across complex tasks, and pins down requirements for feature development and bug-fixing more effectively than Opus 4.8. Developers can now build with Opus 5 in Kiro, accessing its advanced capabilities to tackle ambitious projects.Deepak Singh VP of Agentic AI *Alignment.* During pre-deployment testing, our automated behavioral audit found Opus 5 to be our most aligned model to date (as shown in the graph below). It adheres to [Claude’s Constitution](https://www.anthropic.com/constitution) better than Opus 4.8, Sonnet 5, or Fable 5; exhibits the lowest rates of deceptive behavior; and is the least susceptible to being tricked into misuse. It’s also our safest model yet in terms of avoiding reckless actions that could have hard-to-reverse side effects. *Safety.* Opus 5 does not advance the frontier in risky, dual-use capabilities. In rigorous evaluations conducted alongside private-sector and government partners, we found it remains behind Mythos 5 in both biology research and offensive cybersecurity. More information about these evaluations can be found in our [System Card](https://www.anthropic.com/claude-opus-5-system-card). As with its predecessor, Opus 4.8, we’ve intentionally avoided training Opus 5 on cyber tasks. The model has nevertheless improved substantially on these tasks as a result of becoming more generally capable, and it comes close to Mythos 5 at *finding* cybersecurity vulnerabilities. However, it remains substantially behind Mythos 5 on the *exploitation* of those vulnerabilities—that is, in turning vulnerabilities into material cyber threats. This is illustrated by Opus 5’s performance on OSS-Fuzz, an evaluation we’ve developed to assess how well models can find and then exploit vulnerabilities without extensive human guidance. Although Mythos 5 and Opus 5 identify vulnerabilities with similar success, Opus 5’s score on the development of exploits is far behind that of Mythos 5. Claude Opus 5’s safeguards are designed to allow beneficial uses of the model in both cybersecurity and biology. They are similar to those we applied to Opus 4.8, with the exception of some stronger guardrails on a narrow range of cyber tasks. *Cybersecurity.* Opus 5’s cyber classifiers are proportionally less restrictive than those on Fable 5. They allow Opus 5 to find vulnerabilities in source code, but block “binary-based” vulnerability scanning (a method more likely to be associated with malicious actors), penetration testing, and exploit generation. Based on our testing, we expect the classifiers to intervene around 85% less often than they do for Fable 5. In [Claude.ai](http://claude.ai/redirect/website.v1.b7bb6367-c8bf-453d-bdd5-d35fdd301201), Claude Code, and Claude Cowork, any flagged requests will fall back to Opus 4.8 by default. Fallbacks to Opus 4.8 can also be enabled on the API. Our [Cyber Verification Program](https://support.claude.com/en/articles/14604842-real-time-cyber-safeguards-on-claude-opus-and-sonnet) (CVP) facilitates cybersecurity work that would otherwise be impeded by the model’s safeguards. Enterprises and researchers who are already part of the CVP have immediate access to a version of Opus 5 with fewer security restrictions. *Biology.* Since Opus 5 has a similar suite of safeguards to Opus 4.8, it is now our most capable generally available model for scientific research. Nevertheless, the model still shows important limitations on long-running, autonomous research tasks, which is where we expect AI models to pose the most substantial biology-related risks. (Mythos 5 remains the stronger model for this type of biological work.) As part of this launch, biology-related requests that are blocked on Fable 5 will now route to Opus 5 rather than Opus 4.8. Claude Opus 5 is available today on all platforms, priced at $5 per million input tokens and $25 per million output tokens (the same as Opus 4.8). Developers can get started with claude-opus-5 on the Claude API. It’s also offered in Fast mode, where it runs around 2.5 times the default speed. As with Opus 4.8, Fast mode is available at twice Opus 5’s base price on the Claude Platform and through usage credits in Claude Code. Alongside Opus 5, we’re releasing two updates in beta: Consistent with prior Opus models, Opus 5 does not have data retention requirements for general access. For more guidance on how to get the best out of Opus 5, see our [prompting guide](https://platform.claude.com/docs/en/build-with-claude/prompt-engineering/prompting-claude-opus-5). **Frontier-Bench v0.1, Effort plot:** These results are from an internal run of Frontier-Bench v0.1, on the mini-SWE-agent harness and a GKE backend, mean reward over 5 attempts per task. Opus 4.8 served as fallback on safety-classifier refusals for Opus 5 and Fable 5.