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Large Language ModelsTHE DECODERPublished: Oct 3, 2026, 04:00 JST

Cloudflare Clef-flash hits 39 milliseconds, outpacing Jev

Cloudflare Clef-flash hits 39 milliseconds, outpacing Jev

3 Key Points

  1. What happened

    Cloudflare released Clef and Clef-flash, decision models that return classifications with probabilities instead of text. It reports median latency of about 39 milliseconds for Clef-flash and about 209 milliseconds for Clef, versus just over 524 milliseconds for TypeSafe AI's Jev.

  2. Why it matters

    If those latency figures hold in practice, agents could classify a support ticket or a domain and act on the result without a person checking each step, which is what Cloudflare means by saying a human no longer necessarily needs to be in the loop.

  3. What to watch

    The speed and accuracy claims are Cloudflare's own, so the test is whether independent users reproduce them. Cloudflare also plans a self-service fine-tuning platform for Clef, after forward deployed engineers handle fine-tuning with customers first.

WHO IT HITSTeams that route support tickets, triage abuse reports, or classify websites could replace slow language-model calls with a faster decision model; Cloudflare is already testing Clef on website classification through its threat intelligence team. Data and platform engineers evaluating agent workflows are the likeliest early users.

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Context & Analysis

Cloudflare has mainly been known for its global network for content delivery, DNS, and security services, and its recent AI headlines have centered on giving website owners control over access, such as letting site operators block or allow AI bots based on their purpose in July. Clef marks a shift toward Cloudflare's own AI models, aimed at a niche between large language models, which can reason and call tools but vary in output and can be slow, and traditional classifiers, which are fast but need retraining for every new category.

The approach was popularized by TypeSafe AI, the startup founded by former OpenAI researcher Diogo Almeida, which introduced Jev in mid-September and markets it as a model "without hallucinations" — though that only guarantees it stays within predefined answer options and doesn't prevent it from choosing incorrectly. In late September, OpenAI followed with a Decisions API built on GPT-6 Luna that also accepts context as text or images. Cloudflare keeps its API fully compatible with Jev so customers can switch easily, and it built Clef on Qwen models while leaving the base models unchanged and training extra components on its own synthetic data.

The stakes likely hinge on whether Cloudflare's self-reported benchmarks survive outside scrutiny, and on how quickly the planned self-service fine-tuning platform arrives, since the launch version relies on forward deployed engineers working directly with customers. Buyers weighing a switch from Jev gain from the compatible API, but the real test is whether the latency and accuracy advantages hold on their own tasks rather than on Cloudflare's.

FAQ
What does a decision model actually return?
It answers multiple predefined questions about one input at once, returning a probability for each answer option instead of a long text response. For a customer support message, Clef assesses urgency and identifies the team that should handle it.
Can Clef be customized for a company's own tasks?
Yes. Cloudflare is rolling out a reinforcement learning service for fine-tuning, initially handled by forward deployed engineers, with a self-service platform planned for later.
How does Clef compare with Jev on accuracy?
Cloudflare reports that Clef delivers the highest decision quality while Clef-flash nearly matches Jev's accuracy at a fraction of the latency, and that Clef leads on the Jev Decision Index in its own benchmarks.

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