⏱️ Lectura: 12 min
Anthropic raised the price-to-performance ceiling of its models: Claude Opus 5 is now available and, according to the company, comes close to Claude Fable 5’s frontier intelligence while costing half as much per task. The announcement landed on July 24, 2026, and makes Opus 5 the default model for Claude Max and the most powerful model available on Claude Pro.
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The leap isn’t just about price. On Frontier-Bench v0.1, the software engineering evaluation Anthropic uses internally, Opus 5 more than doubles the score of its predecessor Opus 4.8 and beats every model evaluated on that test, at a lower cost per task.
TL;DR
- Anthropic launched Claude Opus 5 on July 24, 2026, available immediately across all plans.
- It approaches Claude Fable 5’s performance on key benchmarks, but costs half as much per task.
- It’s now the default model on Claude Max and the strongest one available on Claude Pro.
- On Frontier-Bench v0.1 it more than doubles the score of its predecessor, Opus 4.8, at a lower cost.
- On ARC-AGI 3 it scores three times higher than the second-best model evaluated.
- On OSWorld 2.0 it beats Fable 5’s best result while using just over a third of its cost.
- It improves by up to 10.2 percentage points over Opus 4.8 on organic chemistry tasks.
- It still trails Claude Mythos 5 on cybersecurity evaluations, as Anthropic itself acknowledges.
Introduction
Every new Anthropic model answers a different question. Fable 5 aimed for pure intelligence, without worrying much about cost. Mythos 5 was tuned for cybersecurity. Claude Opus 5 answers a more practical question: how much frontier intelligence can be packed into a model someone uses every day, for real work, without the bill spiking.
Anthropic’s answer is that Opus 5 keeps the same cost as Opus 4.8, its direct predecessor, while substantially improving on code evaluations, knowledge work, and computer use. It is, in the company’s words, a thoughtful and proactive model, designed for daily use.
What happened
On July 24, 2026, Anthropic published the official announcement of Claude Opus 5 and made it available immediately across its subscription plans and the API. Two product changes accompany the launch: Opus 5 becomes the default model on Claude Max, the highest-volume subscription tier, and it’s the strongest model available within Claude Pro.
Anthropic positions Opus 5 as the new state of the art on code and knowledge-work evaluations like Frontier-Bench and GDPval-AA. The one caveat the company itself acknowledges: on cybersecurity tasks, Opus 5 trails Claude Mythos 5, the family’s model specifically tuned for that domain.
Context and background
Opus 5 arrives as the direct successor to Opus 4.8 and joins a family that already includes Fable 5, the model with the highest raw intelligence, and Mythos 5, the one specialized in cybersecurity. Anthropic’s strategy for the Opus line was always different from Fable’s: instead of chasing the highest possible score regardless of cost, Opus aims for the best point on the cost-performance curve for sustained production use.
That logic shows in how Anthropic measures Opus 5: not just by its peak score, but by its score at every effort level. Claude models let you adjust that effort between low, high, xhigh, and max, so whoever uses it can decide whether to prioritize intelligence or save on tokens and response time. Opus 5 improves across that whole curve, not just at the most expensive end.
Technical details and Claude Opus 5 performance
Code and agents
On Frontier-Bench v0.1, Opus 5 outperforms every other model evaluated and more than doubles Opus 4.8’s performance at a lower cost per task. On CursorBench 3.2, with effort set to max, Opus 5 comes within 0.5 percentage points of Fable 5’s top score, but at half the cost per task; at the high, xhigh, and max effort levels it achieves better performance per cost than any other model evaluated.
Devin reports that on FrontierCode 1.1, Claude Opus 5 approaches Fable 5’s level at half the cost, with a particular strength in difficult debugging and root-cause analysis. Cursor agrees: on CursorBench it lands just below Fable 5 and reproduces much of its behavior, at the speed and cost of an Opus model.
One example Anthropic highlights: Opus 5 was given a drawing of a mechanical part and asked to reconstruct it as a 3D model in FreeCAD via code, without being given any direct way to view the drawing. The model wrote its own computer vision pipeline to extract the geometry from the raw pixels and reconstructed the complete part, repeatably. No competing model, under the same setup, solved the task in five attempts.
Science and reasoning
On ARC-AGI 3, the evaluation designed to measure novel problem-solving, Opus 5’s score is triple that of the next-best model. On Zapier’s AutomationBench, which measures whether a model completes business tasks end to end, Opus 5 passes roughly 1.5 times more tasks than the second-best model at the same cost per task; even at its lowest effort level, it passes more tasks than any other model evaluated.
On OSWorld 2.0, the computer-use benchmark, Opus 5 beats every other model at any cost level and even surpasses Fable 5’s best result while using just over a third of its cost. Anthropic also flags it as the strongest and most cost-efficient model on GDPval-AA v2, HLE, AutomationBench, and DeepSearchQA.
For scientific research, Opus 5 improves over Opus 4.8 on all of Anthropic’s life sciences evaluations, covering structural biology, organic chemistry, and bioinformatics. The most notable improvement is in organic chemistry: 10.2 percentage points higher than Opus 4.8 when inferring molecular structures from spectroscopy data. On protein tasks, such as predicting how a sequence variation affects function, the improvement is 7.7 percentage points.
Verification and agentic work
Anthropic insists that Opus 5’s central improvement isn’t just the score: it’s the ability to verify its own work and carefully iterate until it reaches the correct result. An engineer at a trading firm used Opus 5 to build, in a single session, a market data feed for a new exchange; previous models couldn’t complete the task even with extensive plans prepared in advance. With no live feed to validate against, Opus 5 built its own test harness to confirm that its code correctly parsed the exchange’s data.
In a case involving a real bug in a popular open source package manager, Opus 5 found the root cause and fixed an edge case that the community patch had missed. A competing model, faced with the same bug, only fixed the surface-level symptom and reported the issue as resolved.
💡 Tip: the effort level is the most important dial for controlling cost on Opus 5: at low it already beats other models on AutomationBench, so it’s worth testing there before moving up to high or max.
How to try it
Claude Opus 5 is already active on Claude Max and Claude Pro with no extra steps: if you have one of those subscriptions, the model selector in the app or web should already show it as the default or an available option. To integrate it via API, the flow is the same as with any recent Claude model, just change the model identifier.
A minimal API call, using curl (works the same on Windows with PowerShell, macOS, and Linux):
curl https://api.anthropic.com/v1/messages \
-H "content-type: application/json" \
-H "x-api-key: $ANTHROPIC_API_KEY" \
-H "anthropic-version: 2026-07-24" \
-d '{
"model": "claude-opus-5",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "Summarize in three points what Frontier-Bench v0.1 is."}
]
}'That call returns a JSON object with a model field: check there that it says claude-opus-5 and not the Opus 4.8 identifier, especially if your code still points to the previous model by default.
For real agentic work, like reviewing a pull request or debugging production code, it’s worth using the SDK and adjusting the effort level depending on the case:
import anthropic
client = anthropic.Anthropic()
response = client.messages.create(
model="claude-opus-5",
max_tokens=4096,
effort="high",
messages=[
{
"role": "user",
"content": "Review this pull request and explain the root cause of the bug in the CSV parser, not just the symptom."
}
],
)
print(response.content[0].text)With effort set to low or medium the cost drops, but for deep debugging tasks, which is where Devin reports Opus 5’s biggest strength, it’s worth starting at high and only moving up to xhigh or max if the result isn’t good enough:
flowchart TD
A["Task to solve with Opus 5"] --> B["Effort: low"]
B --> C{"Good enough result?"}
C -->|"Yes"| D["Use response"]
C -->|"No"| E["Effort: high"]
E --> F{"Good enough result?"}
F -->|"Yes"| D
F -->|"No"| G["Effort: xhigh or max"]
G --> DImpact and analysis
Anthropic’s message with Opus 5 is that frontier intelligence no longer demands a frontier price. The table below summarizes where each model in the family stands, according to Anthropic’s own reporting:
| Model | Strength | Relative cost | Limitation |
|---|---|---|---|
| Claude Opus 5 | New state of the art on Frontier-Bench and GDPval-AA | Same as Opus 4.8 | Trails Mythos 5 on cybersecurity |
| Claude Opus 4.8 | Direct predecessor, baseline for comparison | Reference (1x) | Frontier-Bench score doubled by Opus 5 |
| Claude Fable 5 | Frontier intelligence, the family’s ceiling | Higher per task (up to ~3x on OSWorld 2.0) | Much higher cost per task |
| Claude Mythos 5 | Specialized in cybersecurity tasks | Not specified by Anthropic | Not designed for general daily use |
For businesses already integrating Claude into their workflows, Zapier’s case is the most concrete: Opus 5 topped the AutomationBench leaderboard without spending more tokens than previous Claude models. It took a raw account health spreadsheet and ran a complete churn-prevention sequence: flagged at-risk accounts, alerted the right owner for each account, and summarized everything for the retention team. Previous models didn’t pass that task; Opus 5 hit 100%.
Lovable, which builds its product on Claude models, reports that Opus 5 came out ahead of every previous model in its family on Lovable’s internal evaluations, with a 22% improvement over Opus 4.7 on its hardest agentic coding tasks and, something they specifically highlight, less variance from run to run.
📌 Note: Anthropic is explicit that Opus 5 isn’t the strongest model for everything: on cybersecurity, Mythos 5 remains ahead. Choosing a model based on the domain, not just its name or release date, is still the right call.
Anthropic also showed two examples of visual output generated by Opus 5: an interactive wind tunnel simulation that visualizes airflow over aerodynamic and non-aerodynamic objects, and a simplified interactive illustration of a cell. These are product examples, not a quantified benchmark, but they show the improvement isn’t limited to code and text.
What’s next
Anthropic didn’t give a date for the next model in the Opus line, but the company’s release pattern (Opus 4.8, now Opus 5, alongside Fable 5 and Mythos 5 as specialized sibling models) suggests the three-family strategy, with distinct roles of maximum intelligence, cybersecurity, and cost-efficient daily use, is holding. In the short term, more platforms that already integrate Claude, like Devin, Cursor, and Lovable, will likely move their default model to Opus 5 and publish their own numbers, something that already started happening the same day of the announcement.
📖 Summary on Telegram: View summary
Try it yourself: if you already have an Anthropic API key, change the model in your last call to claude-opus-5 and compare the model field in the response against your previous version.
Frequently Asked Questions
What is Claude Opus 5?
It’s the newest model in Anthropic’s Opus line, launched on July 24, 2026. According to Anthropic, it approaches Claude Fable 5’s performance on several key evaluations while costing half as much per task, and it’s now the default model for Claude Max and the strongest one available on Claude Pro.
How much does it cost to use Claude Opus 5?
Anthropic didn’t publish a new pricing table with the announcement: it stated that Opus 5 keeps the same cost as its predecessor, Opus 4.8, while improving performance on most of the reported evaluations.
How does Opus 5 differ from Claude Fable 5?
Fable 5 is the family’s model with the highest raw intelligence; Opus 5 aims to get close to that level at a much lower cost. On CursorBench 3.2, for example, Opus 5 comes within 0.5 percentage points of Fable 5’s top score, but at half the cost per task.
Is Opus 5 better than Mythos 5?
Not in every domain. Mythos 5 remains ahead of Opus 5 specifically on cybersecurity tasks, as Anthropic itself acknowledges in the announcement.
Is it already available in Cursor, Devin, and Lovable?
Yes. All three platforms published comments about Opus 5 on the same day of the launch, with their own results from internal benchmarks, such as FrontierCode 1.1 for Devin and CursorBench for Cursor.
How do I confirm I’m using Opus 5 and not a previous model?
Check the model field in the API’s JSON response: it should return the Opus 5 identifier and not the Opus 4.8 one. In the Claude Max or Claude Pro interface, the model selector at the top of the chat shows the active model.
References
- Anthropic’s official announcement: full details on benchmarks, early access cases, and Claude Opus 5 availability.
- Anthropic: official site of the company that develops the Claude model family.
- Anthropic API documentation: technical reference for integrating Claude models, including effort parameters.
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Imagen destacada: Foto de Andres Siimon en Unsplash
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