NANI-Nithin/clef-flash-GGUF overview
Clef Flash — GGUF quants language tower Cloudflare/clef flash https://huggingface.co/Cloudflare/clef flash quantized for llama.cpp. The source is a 9.4B parame…
Runs locally from ~1.83 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| clef-flash-BF16.gguf | GGUF | BF16 | 16.69 GB | Download |
| clef-flash-IQ1_M.gguf | GGUF | IQ1_M | 2.68 GB | Download |
| clef-flash-IQ1_S.gguf | GGUF | IQ1_S | 2.55 GB | Download |
| clef-flash-IQ2_M.gguf | GGUF | IQ2_M | 3.36 GB | Download |
| clef-flash-IQ2_S.gguf | GGUF | IQ2_S | 3.19 GB | Download |
| clef-flash-IQ2_XS.gguf | GGUF | IQ2_XS | 3.06 GB | Download |
| clef-flash-IQ2_XXS.gguf | GGUF | IQ2_XXS | 2.89 GB | Download |
| clef-flash-IQ3_M.gguf | GGUF | IQ3_M | 4.11 GB | Download |
| clef-flash-IQ3_S.gguf | GGUF | IQ3_S | 4.07 GB | Download |
| clef-flash-IQ3_XS.gguf | GGUF | IQ3_XS | 3.95 GB | Download |
| clef-flash-IQ3_XXS.gguf | GGUF | IQ3_XXS | 3.67 GB | Download |
| clef-flash-IQ4_NL.gguf | GGUF | IQ4_NL | 5.05 GB | Download |
| clef-flash-IQ4_XS.gguf | GGUF | IQ4_XS | 4.84 GB | Download |
| clef-flash-Q1_0.gguf | GGUF | Q1_0 | 1.83 GB | Download |
| clef-flash-Q2_0.gguf | GGUF | Q2_0 | 3.14 GB | Download |
| clef-flash-Q2_K.gguf | GGUF | Q2_K | 3.56 GB | Download |
| clef-flash-Q2_K_S.gguf | GGUF | Q2_K_S | 3.44 GB | Download |
| clef-flash-Q3_K_L.gguf | GGUF | Q3_K_L | 4.59 GB | Download |
| clef-flash-Q3_K_M.gguf | GGUF | Q3_K_M | 4.31 GB | Download |
| clef-flash-Q3_K_S.gguf | GGUF | Q3_K_S | 3.97 GB | Download |
| clef-flash-Q4_0.gguf | GGUF | Q4_0 | 4.95 GB | Download |
| clef-flash-Q4_1.gguf | GGUF | Q4_1 | 5.41 GB | Download |
| clef-flash-Q4_K_M.gguf | GGUF | Q4_K_M | 5.24 GB | Download |
| clef-flash-Q4_K_S.gguf | GGUF | Q4_K_S | 4.98 GB | Download |
| clef-flash-Q5_0.gguf | GGUF | Q5_0 | 5.87 GB | Download |
| clef-flash-Q5_1.gguf | GGUF | Q5_1 | 6.33 GB | Download |
| clef-flash-Q5_K_M.gguf | GGUF | Q5_K_M | 6.02 GB | Download |
| clef-flash-Q5_K_S.gguf | GGUF | Q5_K_S | 5.87 GB | Download |
| clef-flash-Q6_K.gguf | GGUF | Q6_K | 6.85 GB | Download |
| clef-flash-Q8_0.gguf | GGUF | Q8_0 | 8.87 GB | Download |
Model Details
| Model ID | NANI-Nithin/clef-flash-GGUF |
|---|---|
| Author | NANI-Nithin |
| Pipeline | — |
| License | apache-2.0 |
| Base model | Cloudflare/clef-flash |
| Last modified | 2026-10-04T17:28:33.000Z |
Model README
---
base_model: Cloudflare/clef-flash
license: apache-2.0
tags:
- gguf
- llama.cpp
- quantized
- clef
- cloudflare
- qwen3.5
- qwen3_5
- decision-model
- structured-output
---
Clef-Flash — GGUF quants (language tower)
Cloudflare/clef-flash quantized for llama.cpp. The source is a 9.4B-parameter model (architecture Qwen3_5ForConditionalGeneration, 32 layers, hidden size 4096, vocab 248,320), post-trained by Cloudflare from Qwen/Qwen3.5-9B and released under Apache-2.0. This repo has 30 verified files: 29 GGUF quants plus the full-precision BF16 source.
⚠️ What these files do and don't contain
Clef-Flash is a decision model: it reads a state (text, JSON, images, or video) plus a schema of typed questions and returns a probability for every allowed option of every question in a single forward pass — no free-form text generation, no output parsing. That behavior comes from a backbone plus a separate joint schema head (and optionally the vision encoder).
This repo contains the language tower only.
- The vision encoder is not included — there is no
--mmprojfile here, so image and video inputs are not available from these GGUFs. - The joint schema head is not included (
joint_head.safetensorsis a separate component in the source release). Per-question probabilities and the Jev / SystemOne API behavior therefore cannot be reproduced from these files.
For the full decision-model behavior, use Cloudflare/clef-flash directly with transformers (5.10.2) and torch (2.11) per its README. What you get from this repo in llama.cpp is the post-trained Qwen3.5-9B language tower.
About Clef-Flash
From the Cloudflare announcement: Clef-Flash turns a state plus a schema of typed questions into decisions. Each question is one of three types — noul (true/false), choice (named options), or score (ordered options) — and the model's joint schema head reads the backbone's final hidden states, routes evidence from the state to each question, and scores all options of all questions jointly. The Clef-Flash API is compatible with Jev and SystemOne. Clef-Flash is the smaller sibling of Cloudflare/clef.
Files
All 30 files below are verified present on the Hub.
| File | Size (GB) | Notes |
|---|---|---|
| clef-flash-BF16.gguf | 16.69 | Full precision source. Every quant below is cut from this file. |
| clef-flash-Q8_0.gguf | 8.87 | Effectively lossless. Use when disk and RAM are not the constraint. |
| clef-flash-Q6_K.gguf | 6.85 | Near-lossless; the last stop before quality becomes measurable. |
| clef-flash-Q5_1.gguf | 6.33 | Legacy. Prefer Q5_K_M. |
| clef-flash-Q5_K_M.gguf | 6.02 | Very good quality, noticeably smaller than Q6_K. |
| clef-flash-Q5_K_S.gguf | 5.87 | Slightly smaller than Q5_K_M for a slight quality cost. |
| clef-flash-Q5_0.gguf | 5.87 | Legacy. Prefer Q5_K_M. |
| clef-flash-Q4_K_M.gguf | 5.24 | The usual default. Best quality-per-byte for most people. |
| clef-flash-Q4_1.gguf | 5.41 | Legacy. Prefer Q4_K_M. |
| clef-flash-IQ4_NL.gguf | 5.05 | Non-linear 4-bit; good on hardware without fast K-quant kernels. |
| clef-flash-Q4_K_S.gguf | 4.98 | A little smaller than Q4_K_M, a little worse. |
| clef-flash-Q4_0.gguf | 4.95 | Legacy round-to-nearest. Prefer Q4_K_M unless a runtime needs this. |
| clef-flash-IQ4_XS.gguf | 4.84 | Best sub-4.5bpw option; usually beats Q4_K_S at a smaller size. |
| clef-flash-Q3_K_L.gguf | 4.59 | Small, with real quality loss. Usable when RAM is tight. |
| clef-flash-Q3_K_M.gguf | 4.31 | Smaller again; noticeable degradation. |
| clef-flash-IQ3_M.gguf | 4.11 | Strong at ~3.7bpw, clearly better than Q3_K_M. |
| clef-flash-IQ3_S.gguf | 4.07 | Slightly smaller than IQ3_M. |
| clef-flash-Q3_K_S.gguf | 3.97 | Aggressive. Prefer IQ3_M at a similar size. |
| clef-flash-IQ3_XS.gguf | 3.95 | Aggressive but coherent. |
| clef-flash-IQ3_XXS.gguf | 3.67 | Very aggressive; the last coherent step down. |
| clef-flash-Q2_K.gguf | 3.56 | Very small, heavily degraded. For experimentation. |
| clef-flash-Q2_K_S.gguf | 3.44 | Smaller than Q2_K, at a further quality cost. |
| clef-flash-IQ2_M.gguf | 3.36 | The smallest size most people find usable. |
| clef-flash-IQ2_S.gguf | 3.19 | Below the usual usability line. |
| clef-flash-Q2_0.gguf | 3.14 | Extreme, group-64. Included for completeness. |
| clef-flash-IQ2_XS.gguf | 3.06 | Experimental. |
| clef-flash-IQ2_XXS.gguf | 2.89 | Experimental. |
| clef-flash-IQ1_M.gguf | 2.68 | Extreme. Expect substantial degradation. |
| clef-flash-IQ1_S.gguf | 2.55 | Extreme. Expect substantial degradation. |
| clef-flash-Q1_0.gguf | 1.83 | Extreme. Included for completeness. |
Quantized 2026-10-04. The importance matrix was computed on the full BF16 weights, not on a lower-precision surrogate.
Usage
# run directly from the Hub
llama-cli -hf NANI-Nithin/clef-flash-GGUF:Q4_K_M -p "Hello"
# or serve it
llama-server -hf NANI-Nithin/clef-flash-GGUF:Q4_K_M
# or download a single file
huggingface-cli download NANI-Nithin/clef-flash-GGUF clef-flash-Q4_K_M.gguf --local-dir .
llama-cli -m clef-flash-Q4_K_M.gguf -p "Hello"
These files are llama.cpp GGUF. They are not loaded by vLLM, SGLang or transformers the way the source repo is — for that, use Cloudflare/clef-flash.
Which file?
- Q4_K_M (5.24 GB) — the default choice; best quality-per-byte for most setups.
- Q8_0 (8.87 GB) — effectively lossless, when resources allow.
- Q6_K (6.85 GB) — near-lossless middle ground.
- IQ4_XS (4.84 GB) — the best pick under ~4.5 bits per weight.
- IQ2_M (3.36 GB) — the smallest size most people find usable.
- Everything smaller than IQ2_M is experimental or extreme; expect substantial degradation. The lowest-bit files exist for completeness only.
Results
Cloudflare publishes decision-model benchmark results in the source README and on the Decision Index leaderboard. In Cloudflare's internal run of the Decision Index 0.2.1 suite, Clef-flash posts the best score among the compared decision models in the majority of listed rows — for example BFCL 98.8 (case exact accuracy), MMLU 91.8, HellaSwag 98.6, WinoGrande 97.5, and a median request latency of 38.8 ms — with ForecastBench reported as a Brier score (10.6), where lower is better. These numbers describe the source model with its joint head on Cloudflare's own harness; the quantized files in this repo were not re-evaluated.
Licence
Apache-2.0, following the base model Qwen/Qwen3.5-9B. Clef-Flash was created by Cloudflare; these quants are an independent llama.cpp conversion of the published weights.
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