In Fable 5.1, AI's cost war comes for Anthropic

September 2, 2026

Welcome back. Perplexity's new Hybrid Compute agent automatically routes sensitive tasks to local models while sending general tasks to frontier-class models in the cloud, a privacy-first approach other tech companies and AI labs look likely to emulate. CrowdStrike is tackling the growing fear of agents running amok with an aggressive three-part strategy for eliminating malicious AI activity before it spreads. And Anthropic's new Fable 5.1 model touts a big efficiency win that effectively cuts agentic workload costs by 45% without sacrificing performance. —Jason Hiner

PRODUCTS

Anthropic's latest model release addresses one of the biggest pain points with its models.

On Tuesday, the company announced Claude Fable 5.1 and Mythos 5.1, the latest version of the most powerful models in its line-up. While Fable is generally available, Mythos, which has additional cybersecurity capabilities, is available only through trusted access programs.

And with many enterprises clamping down on AI costs, Anthropic is taking the hint: The company said that Fable 5.1 will cost an estimated 25% less than Fable 5 for typical workloads "wherever usage is billed by token." Notably, agentic workloads will see much higher savings, Anthropic said, estimating around 45%.

The company said that this is because it is reducing its costs for cache reads, or when the model reads inputs that it had already previously processed and stored.
And these reduced prices don't come at the cost of performance: Anthropic claims that Fable 5.1 "sets a new standard" for coding, knowledge work, and long-running problem-solving, beating out previous generations and OpenAI's GPT-5.6 Sol on benchmarks for these tasks.
Additionally, the models come with a new system for data retention, called Enterprise Frontier Safeguards, which gives customers the same right to privacy as a zero data retention (ZDR) policy. Anthropic also introduced safeguards that reduce false positives in cybersecurity contexts.
However, outside of the potential caching savings, Fable 5.1’s pricing is otherwise the same as Fable 5’s at $10 per million input tokens and $50 per million output tokens. That still makes it one of the most expensive models on the market.

The model was tested by a number of Anthropic's early-access partners, including Cognition, Rakuten, Red Hat, Block, Ramp and Canva.

"Fable-level intelligence, Opus-level price, Sonnet-speed," Dan Shipper, CEO of Every and one of the early testers of the model, said in the release. "In our tests it was about twice as fast as Opus 5 and used half as many tokens, so for anyone used to using Opus as their daily driver it's an obvious upgrade."

Anthropic is highlighting cost savings with this release at a particularly opportune moment, as some enterprises grow weary of tokenmaxxing sticker shock. It's led to an uptick in the popularity of open-source models and driving down token costs. Recent data from the LLM Token Expenditure Index finds that, as of August 31, users are spending an average of 97 cents per million tokens, down from a high of $2.07 per million in late May.

Anthropic making its most powerful flagship AI cheaper was the most consequential move it could have made at this point. Of course, it didn't technically cut prices, but rather made its models more token-efficient. Enterprises are surrounded with viable alternatives to proprietary frontier AI, whether that be Chinese open-source models, domain-specific models, or simply settling for efficient SLMs that get the job done. Additionally, rival OpenAI is trying to lure in customers with cost efficiency, too, chopping prices for its models more than once. While this is certainly good news for customers seeking out frontier AI, cutting prices may not address the elephant in the room: As model routing services become popular, customers may start to care less about which models they're actually using. That effectively turns these frontier models into interchangeable commodities rather than unique systems, meaning that the price may become the most important frontier in the race towards widespread adoption.

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GOVERNANCE

CrowdStrike offered an answer for the growing fear around AI agents getting out of control and breaking critical systems.

On Tuesday at its Fal.con event in Las Vegas, CrowdStrike unveiled Falcon Guardian, a new enterprise visibility and protection platform that monitors everything agents do on your network and blocks malicious activity at the endpoint before it escalates.

The new product grows out of CrowdStrike's September 2025 acquisition of Pangea, one of the pioneers of generative AI cybersecurity, and it combines CrowdStrike's endpoint monitoring and protection with Pangea's intelligence in detecting malicious AI activity. The move is an attempt to create a new category of software called AIDR: AI detection and response.

"The industry has seen what happens when agentic autonomy outpaces the authority that those agents should have," said CrowdStrike's chief product officer, AJ Shipley, in a briefing with the media.

We've learned over the past month that OpenAI, Anthropic, and Meta have all had AI agents that broke through their guardrails and launched their own attacks that were unplanned and unintended by the teams running them.

"This was a watershed moment in security," said CrowdStrike CEO George Kurtz in the opening keynote at Fal.con on Tuesday.

And in recent days, over 100 leading tech and AI companies have united to call for collective action in prioritizing cyber defenses to protect critical infrastructure against the next wave of AI advances.

CrowdStrike Falcon Guardian wants to address the problem with multiple components in one platform:

Agent monitoring and detection: Automatically detects all agents operating on the network, no matter who started them or where.
Telemetry for tracking actions: This plays to CrowdStrike's strengths in endpoint telemetry (process, file, network activity) to capture the full causal chain of everything an agent does.
Agent access control and policy enforcement: Organizations can define which agents are allowed to run on which devices, and it blocks unauthorized agents to make AI governance policies enforceable.
Real-time AI threat containment: Identifies compromised or malicious agents, determines their blast radius in real time, and neutralizes threats before they spread.

"Falcon Guardian will discover every approved and shadow AI agent across the enterprise. It'll provide a live inventory of every agent, who deployed it, [and] its security status. And it is continuously updated," said Shipley.

Beyond just Falcon Guardian, which is focused on helping companies understand and control what's happening in their corporate infrastructure, CrowdStrike also announced two other big moves. It's launching the CrowdStrike Cyber Super Intelligence Lab as a factory to churn out the knowledge and understanding to stay ahead of attackers and malicious AI. It's also launching its own harness, SafeMind, and its own AI models, Red Tempest and Blue Solano. The models are built on Nvidia's open Nemotron models and the harness is aimed at creating a proactive, offensive system that's constantly evolving to counter the ways AI agents change and adapt to launch attacks. CrowdStrike claims it detects 52% more legitimate threats and remediates them 48x faster than general-purpose models. That sounds a lot like Cloudflare's Adaptive Intelligence, which just launched to give companies a security solution that adapts in real-time to the way AI evolves. Giving enterprises more dynamic solutions to protect against agentic AI attacks is a welcome development.

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PRODUCTS

Perplexity is at it again, launching something other AI companies seem likely to emulate.

On Tuesday, the AI startup announced Perplexity Hybrid Compute, a version of its AI agent that automatically detects sensitive data and PII and routes those parts of a task to local models to preserve data privacy and data sovereignty. This will launch inside Perplexity's Personal Computer on the Perplexity app on Apple devices running Apple silicon. It's available starting today for all Perplexity Enterprise customers who opt in, and it's also available to all Pro and Max subscribers.

The magic here is that while the sensitive tasks are split off to run locally, other parts of the task can be handed to sub-agents to run on frontier models in the cloud to take advantage of the cutting edge capabilities of the latest models.

"Tasks like this aren't possible in a fully local or fully cloud setup. It's this marriage of them together, and it gives you the security of local [models] and the intelligence of the frontier," said Jonathon Staff, lead engineer for Perplexity Hybrid Compute, in a briefing with the media. "We're very glad to be able to consolidate this down into something where you just have one input and one output."

Other details about the product:

Examples of the kinds of files Hybrid Compute will detect and run locally include: legal briefs, customer information, and patient data (in health care)
Enterprises can set sensitivity policies that apply across the org and can observe which data gets sent to the cloud
Users can start a task in the Perplexity app on their iPhone and have certain parts of the task run locally on their Mac
To start, you'll be able to choose from a couple open models that can run locally: Google's Gemma E4B and Alibaba's Qwen3.6 35B-A3B (a special version of Qwen3.6 35B that Perplexity has post-trained and tuned for this product)

The company's AI agent, Perplexity Computer, launched in early 2026 right around the same time that OpenClaw burst into popularity. But Perplexity Computer, and later the version called Personal Computer that could run locally on a Mac mini, have gained a reputation for being easier and safer to set up and use than OpenClaw and other DIY agents.

"Velocity has always been in our DNA here at Perplexity," said Staff. "We love to move quickly. We also love to move with intentionality. This is a long-term bet, something that we think is going to continue to be more and more important as the models develop."

As AI gets more deeply integrated into enterprises to handle critical tasks and workflows, there's a great push happening for more efficiency, data privacy, and control. If Perplexity's Hybrid Compute can deliver the kind of intelligent routing that it claims, then it would be a welcome development for a lot of professionals, enterprises, and tech decision makers. Perplexity is an obvious candidate to pull off something like this because it's a model-agnostic orchestrator. It's incented to deliver the best and simplest experiences for teams and individuals to reap the benefits of agents while mitigating the risks. Just as impressive is Perplexity again getting out in front of the frontier labs and enterprise software vendors to deliver a feature that feels obvious enough that all of them are likely to be doing it within the next 12-18 months.

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