Models / Clef

A decision model from the company that routes a fifth of the web. Cloudflare shipped Clef (27B) and Clef-flash (9B) on October 1, 2026, Apache 2.0, fine-tuned from the Qwen3.5 27B backbone. Both are decision models in the Jev sense: hand one a question with a fixed set of answers (which inbox does this email route to, is this request abusive, which of these five actions should the agent take) and it returns one answer with a confidence number instead of a paragraph. Clef adds an image input, so a screenshot of a dashboard is a legal question. In a week Clef collected 1,859 likes and Clef-flash 17,600 downloads on Hugging Face.

What the flash size buys. Clef-flash at 9B is the laptop-runnable end of the decision-model map: about 5.4GB in 4-bit, which is a comfortable fit on a 16GB machine with the OS still loaded. Clef at 27B wants more: about 15.7GB in 4-bit, still one-card territory but with a KV cache that matters at length - 256MB per 1,000 tokens means a full 262k context costs about 67GB of cache on top, so the honest serving statement is that the 27B card runs whole-document decisions at 32k context in about 24GB, and short-prompt routing anywhere Qwen3.5 27B already runs.

Why a CDN company ships models. Cloudflare runs Workers AI as a serving platform and the decision-model shape (fast, typed, cheap at scale) is the exact shape a router wants for abuse detection, request classification, and agent-tool gating at the edge. The open weights are the credibility move: any customer can read what the classifier does before trusting it with their traffic, which is the same trust argument Clef’s own blog makes.

decision-model classification routing vision
Parameters
27.4B
Context
262k
License
apache 2.0
Developer
Cloudflare
Origin
πŸ‡ΊπŸ‡Έ USA
Released
Oct 2026

Related models

Guides covering Clef

Save your hardware and every model page answers the real question: will it run on your machine, and how fast?

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Run it locally

Per-quant memory needs and a static "can you run it?" reference - no rig entry required

Q4_K_M
15.7GB 16.0GB min 24.0GB rec
Balanced - the usual local sweet spot
FP16
54.7GB 55.0GB min 64.0GB rec
Full quality, largest

The reference hardware

Schematic of the NVIDIA Jetson Orin NX 16GB reference rig - 16GB unified memory, 102 GB/s aggregate bandwidth
Schematic of the Single GTX 1080 Ti (11GB) reference rig - 11GB VRAM, 484 GB/s aggregate bandwidth
Schematic of the 4x H100 80GB (320GB) reference rig - 320GB VRAM, 13400 GB/s aggregate bandwidth
Schematic of the NVIDIA DGX Station 748GB reference rig - 748GB unified memory, 8000 GB/s aggregate bandwidth
Schematic of the 8x RTX 3090 rack (192GB) reference rig - 192GB VRAM, 7489 GB/s aggregate bandwidth
Schematic of the 4x RTX 5090 (128GB) reference rig - 128GB VRAM, 7168 GB/s aggregate bandwidth
Schematic of the AMD Instinct MI300X (192GB) reference rig - 192GB VRAM, 5324 GB/s aggregate bandwidth
Schematic of the 4x RTX 4090 (96GB) reference rig - 96GB VRAM, 4032 GB/s aggregate bandwidth
Schematic of the 2x RTX 5090 (64GB) reference rig - 64GB VRAM, 3584 GB/s aggregate bandwidth
Schematic of the 2x RTX 3090 (48GB) reference rig - 48GB VRAM, 1872 GB/s aggregate bandwidth
Schematic of the Single RTX 5090 (32GB) reference rig - 32GB VRAM, 1792 GB/s aggregate bandwidth
Schematic of the RTX PRO 6000 Blackwell (96GB) reference rig - 96GB VRAM, 1792 GB/s aggregate bandwidth
Schematic of the Mac Studio M4 Ultra 192GB reference rig - 192GB unified memory, 1092 GB/s aggregate bandwidth
Schematic of the Mac Studio M4 Ultra 512GB reference rig - 512GB unified memory, 1092 GB/s aggregate bandwidth
Schematic of the Single RTX 4090 (24GB) reference rig - 24GB VRAM, 1008 GB/s aggregate bandwidth
Schematic of the MacBook Pro M5 Max 128GB reference rig - 128GB unified memory, 614 GB/s aggregate bandwidth
Schematic of the Dual EPYC 9004 + 768GB DDR5-4800 reference rig - 768GB unified memory, 460 GB/s aggregate bandwidth
Schematic of the DGX Spark 128GB unified reference rig - 128GB unified memory, 273 GB/s aggregate bandwidth
Schematic of the Ryzen AI Max+ 395 128GB reference rig - 128GB unified memory, 256 GB/s aggregate bandwidth
Schematic of the Jetson AGX Orin 64GB reference rig - 64GB unified memory, 204 GB/s aggregate bandwidth
Schematic of the Epyc + 512GB DDR4-3200 + 2x RTX 3090 reference rig - 560GB unified memory, 204 GB/s aggregate bandwidth
Schematic of the Epyc + 512GB DDR4-2400 + 2x RTX 3090 reference rig - 560GB unified memory, 153 GB/s aggregate bandwidth

22 reference configs, drawn in-house. Scroll for more.

Can you run it? - reference rigs

Rig Q4_K_M FP16
NVIDIA Jetson Orin NX 16GB tight no -> cloud
Single GTX 1080 Ti (11GB) offload no -> cloud
4x H100 80GB (320GB) fast 440.7t/s fast 132.3t/s
NVIDIA DGX Station 748GB fast 263.1t/s fast 79.0t/s
8x RTX 3090 rack (192GB) fast 246.3t/s fast 73.9t/s
4x RTX 5090 (128GB) fast 235.7t/s fast 70.8t/s
AMD Instinct MI300X (192GB) fast 175.1t/s fast 52.6t/s
4x RTX 4090 (96GB) fast 132.6t/s fast 39.8t/s
2x RTX 5090 (64GB) fast 117.9t/s fast 35.4t/s
2x RTX 3090 (48GB) fast 61.6t/s offload
Single RTX 5090 (32GB) fast 58.9t/s no -> cloud
RTX PRO 6000 Blackwell (96GB) fast 58.9t/s ok 17.7t/s
Mac Studio M4 Ultra 192GB fast 39.2t/s ok 11.8t/s
Mac Studio M4 Ultra 512GB fast 39.2t/s ok 11.8t/s
Single RTX 4090 (24GB) fast 33.2t/s no -> cloud
MacBook Pro M5 Max 128GB fast 22.0t/s slow 6.6t/s
Dual EPYC 9004 + 768GB DDR5-4800 ok 15.2t/s slow 4.6t/s
DGX Spark 128GB unified ok 9.0t/s slow 2.7t/s
Ryzen AI Max+ 395 128GB ok 8.4t/s slow 2.5t/s
Jetson AGX Orin 64GB slow 6.7t/s slow 2.0t/s
Epyc + 512GB DDR4-3200 + 2x RTX 3090 slow 6.7t/s slow 2.0t/s
Epyc + 512GB DDR4-2400 + 2x RTX 3090 slow 5.1t/s slow 1.5t/s

Fit tiers use the same will-it-run logic as the rig finder. For comfortable fits, the badge reflects decode speed: fast >=20 t/s, ok 8-20 t/s, slow <8 t/s. t/s is a bandwidth estimate, not a measured benchmark.

Download options

Q4_K_M community
15.7GB dl 16.0GB min 24.0GB rec
REC RAM vs largest quant
15.7GB q4 weights + KV at 256MB/1k (full 262k ctx = ~67GB cache); 16GB card fits routing workloads, long-doc decisions want 24GB+
FP16 official
54.7GB dl 55.0GB min 64.0GB rec
REC RAM vs largest quant
54.7GB fp16 weights + KV 256MB/1k

Or run it in the cloud

No per-token API provider pricing tracked for Clef yet. For flagship list prices, see the calculator.

PRICE HISTORY

Inference cost over time

Data accumulates from the first daily sync - longer ranges populate over time. Prices come from OpenRouter snapshots, not a historical API.

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