{"slug": "cloudflare-open-sources-clef-to-challenge-openai-and-amazon-on-ai-agent", "title": "Cloudflare Open Sources Clef to Challenge OpenAI and Amazon on AI Agent Decisions", "summary": "Cloudflare released Clef on October 1, two open-weight decision models that return probabilities instead of generated text, making it the only one of three competing agent-decision models to publish its weights. Clef is a 27 billion parameter model and Clef-flash is a 9 billion parameter version, both built on a Qwen backbone with a 64,000 token context window and shipped under the Apache 2.0 license on Hugging Face, following OpenAI's Decisions API on September 30 and Amazon's Strands Decider 2B on October 1. Cloudflare's benchmark post reports Clef classified a website in 2.2 seconds versus 4.7 seconds for gpt-oss-120b, and ran 2.5 times faster than TypeSafe AI's Jev at the median across 43 benchmark runs, with Clef-flash 13 times faster.", "body_md": "*Cloudflare released Clef on October 1, open-weight decision models that pick an AI agent's next move instead of writing a paragraph about it. It's the third such model to show up in two days, after OpenAI's Decisions API and Amazon's Strands Decider 2B, and Cloudflare is the only one of the three giving away the weights.*\n\nMost AI agents still work the same dumb way underneath the hood. You ask a large language model a yes-or-no question, and it generates a full sentence of text to answer it, burning time and tokens just to say \"yes.\" Cloudflare's answer, announced on its blog this week, is Clef: a pair of models that skip the sentence entirely and return a probability instead. Send it some data and a typed question, and it sends back a number: how likely the answer is yes, which option from your list fits best, where something sits on a scale you defined.\n\nCloudflare built two sizes. Clef is a 27 billion parameter model aimed at the most accurate calls, and Clef-flash is a 9 billion parameter version built for answers in a few tens of milliseconds. Both run on a Qwen backbone and use a 64,000 token context window. Both ship under the Apache 2.0 license with weights posted to Hugging Face, so a developer can download them and run them on their own hardware instead of calling an API. That's the detail that matters most here: this is Cloudflare, a company whose business is routing and securing other people's internet traffic, handing out the actual model weights for free rather than metering access to them.\n\nThe technical trick is skipping autoregressive generation altogether. Instead of producing output token by token, Clef uses what Cloudflare calls non-autoregressive, prefill-only scoring - essentially reading the whole question at once and scoring the possible answers directly. According to Cloudflare's own benchmark post, Clef classified a website in 2.2 seconds in a real workflow test, against 4.7 seconds for gpt-oss-120b doing the same job, and still only returning two classifications where Clef returned more. Across 43 benchmark runs Cloudflare says Clef ran 2.5 times faster than TypeSafe AI's Jev model at the median, with Clef-flash coming in 13 times faster.\n\nJev is where this race started. TypeSafe AI released it as a model built specifically around bounded, machine-readable decisions rather than open-ended text. It caught on fast: a hackathon demo from QueryStory's Shapor Naghibzadeh reportedly used Jev to monitor an AI agent's actions for $2.94, versus $372 running the same check through a frontier LLM. That kind of cost gap is why everyone else piled in within days. OpenAI introduced its Decisions API at Dev Day on September 30, built on its Luna model, aimed at the same bounded-answer use case: classification, routing, picking the next step in an agent loop. Amazon followed on October 1 with Strands Decider 2B, a 2 billion parameter model out of its Strands Labs division, built on a Qwen3.5 base with what AWS calls a \"pointer head\" that scores predefined options directly. TechCrunch described it as Amazon's own Jev clone. It started, apparently, as an internal prototype from AWS distinguished engineer Marc Brooker that briefly topped the JevBench leaderboard for its size class, before AWS cleaned it up and shipped it as a product.\n\n[Cloudflare Launches Wallets That Let AI Agents Autonomously Hold and Spend Money](https://startupfortune.com/cloudflare-launches-wallets-that-let-ai-agents-autonomously-hold-and-spend-money/)\n\nCloudflare launched Cloudflare Wallets on August 4, letting AI agents hold stablecoins and autonomously pay for APIs through the x402 protocol, with spend limits set by human account owners. The move builds on Cloudflare's October 2025 Trusted Agent Protocol deal with Visa and lands amid a broader fight between Visa, Mastercard, Stripe, and... - [AI agents autonomous wallet payments](https://startupfortune.com/cloudflare-launches-wallets-that-let-ai-agents-autonomously-hold-and-spend-money/) - [Cloudflare wallets for AI spending](https://startupfortune.com/cloudflare-launches-wallets-that-let-ai-agents-autonomously-hold-and-spend-money/)\n\nHere's the split that actually matters for developers. OpenAI's Decisions API lives inside OpenAI's own hosted stack, tied to Luna. Amazon's Strands Decider is open-weight but small, a 2B model scoring around 72% accuracy on the public JevBench v19 set. Cloudflare's Clef is open-weight at two sizes, including a 27B model aimed squarely at accuracy rather than just speed, and it claims it beats Jev in three of four evals on Jev's own benchmark suite. Vendor lock-in is the real cost here, not just inference pricing. A team that builds its agent pipeline against a closed API is betting its production workflow on one company's uptime and pricing decisions. A team that pulls Clef's weights down from Hugging Face owns its own copy of the model, forever, regardless of what Cloudflare charges for it next year.\n\nThe release landed well with the audience that cares most about that distinction. On r/LocalLLaMA, the Clef announcement picked up 154 points and 45 comments within its first stretch online, a strong showing for a niche model category most casual AI users have never heard of.\n\nClef also does something neither Jev nor Decider claims: it takes images. Cloudflare says Clef can accept up to four images alongside a text state, giving it a vision encoder that lets it classify a screenshot or a photo the same way it classifies text. Cloudflare is pairing the release with a new reinforcement learning fine-tuning platform. It's starting with a forward-deployed engineer team working directly with early customers before it opens up to self-serve, and it's built on Cloudflare's existing AI Gateway and Containers products, plus a new piece called Trainer for redeploying fine-tuned models back onto Workers AI.\n\nFrankly, the interesting story isn't the model, it's who's publishing it. Cloudflare doesn't need Clef to be the smartest decision model on the market. It needs developers building agent pipelines to run them through Cloudflare's edge network. An open-weight model that developers can self-host while still training and serving through Workers AI is a bet that infrastructure wins this fight before any single model does.\n\n**Also read:** [How To Price An AI Agent Per Seat Versus Per Task Right Now](https://startupfortune.com/how-to-price-an-ai-agent-per-seat-versus-per-task-right-now/) • [Kevin O'Leary's $100 Billion Utah Data Center Is Drowning in Its Own Promises](https://startupfortune.com/kevin-olearys-100-billion-utah-data-center-is-drowning-in-its-own-promises/) • [Yann LeCun calls Dario Amodei deluded and crazy over AI cybersecurity claims](https://startupfortune.com/yann-lecun-calls-dario-amodei-deluded-and-crazy-over-ai-cybersecurity-claims/)\n\n*This article is posted in [AI News](https://startupfortune.com/category/ai/), check it out for more related stories.*\n\n[Cloudflare Launches Kitesurf, a Browser Engine Built Only for AI Agents](https://startupfortune.com/cloudflare-launches-kitesurf-a-browser-engine-built-only-for-ai-agents/)\n\nCloudflare launched Kitesurf on August 7, a browser engine built from scratch in Rust specifically for AI agents, using 3-7x less memory and roughly 3x less CPU than Chromium. It's free in beta through Cloudflare's Browser Run product, with open-source plans to follow, and it targets the growing cost of running headless Chromium fleets for agentic... - [headless browser for AI agents](https://startupfortune.com/cloudflare-launches-kitesurf-a-browser-engine-built-only-for-ai-agents/) - [browser automation infrastructure cloudflare](https://startupfortune.com/cloudflare-launches-kitesurf-a-browser-engine-built-only-for-ai-agents/)\n\n## Join the discussion\n\n[Open in the community →](https://startupfortune.com/community/)\n\nAlmost there. Sign in and your reply posts straight away.", "url": "https://wpnews.pro/news/cloudflare-open-sources-clef-to-challenge-openai-and-amazon-on-ai-agent", "canonical_source": "https://startupfortune.com/cloudflare-open-sources-clef-to-challenge-openai-and-amazon-on-ai-agent-decisions/", "published_at": "2026-10-01 20:21:23+00:00", "updated_at": "2026-10-01 21:44:25.241387+00:00", "lang": "en", "topics": ["ai-agents", "artificial-intelligence", "large-language-models", "ai-tools", "ai-products"], "entities": ["Cloudflare", "Clef", "Clef-flash", "OpenAI", "Amazon", "Strands Decider 2B", "TypeSafe AI", "Hugging Face"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/cloudflare-open-sources-clef-to-challenge-openai-and-amazon-on-ai-agent", "markdown": "https://wpnews.pro/news/cloudflare-open-sources-clef-to-challenge-openai-and-amazon-on-ai-agent.md", "text": "https://wpnews.pro/news/cloudflare-open-sources-clef-to-challenge-openai-and-amazon-on-ai-agent.txt", "jsonld": "https://wpnews.pro/news/cloudflare-open-sources-clef-to-challenge-openai-and-amazon-on-ai-agent.jsonld"}}