Clef-Flash

About

Clef-Flash is a 9B multimodal decision model from Cloudflare, released on October 1, 2026 under the Apache-2.0 license. It turns a state plus a schema of typed questions into decisions: Clef-Flash reads the state as text, JSON, images, or video and returns a probability for every allowed option of every question in a single forward pass - there is no free-form text generation and no output parsing. The Clef-Flash API is fully compatible with Jev and SystemOne, and Clef-Flash is post-trained from Qwen/Qwen3.5-9B. It is the smaller, faster variant of Clef (27B), and both are the first models trained by the Cloudflare Workers AI team.

Architecture

Clef-Flash consists of the Qwen3.5-9B backbone with its vision encoder (stored as standard sharded safetensors, 9B parameters, BF16) plus a joint schema head - a small transformer head that reads the backbone's final hidden states, routes evidence from the state to each question, and scores all options of all questions jointly in a single forward pass. The output is one logit per allowed option for each question; a softmax per question gives probabilities. Qwen3.5-9B itself is a hybrid linear attention transformer: 32 layers in a 3:1 pattern of 24 gated linear attention layers (16 key / 32 value heads at head_dim 128) and 8 GQA full-attention layers (16 query heads / 4 KV heads at head_dim 256, partial rotary factor 0.25, interleaved MRoPE with theta 1e7 and mrope_section [11, 11, 10]), hidden size 4096, intermediate size 12288, vocab 248320, native context 262144 tokens.

Input format and typed questions

A record contains a state (any string or JSON value), optional images/video frames, and a questions mapping. Each typed question declares its allowed answers up front via type (noul true/false, choice named options, or score ordered options), optional instructions, and criteria. encode_record bounds the input at a default max_length of 16,384 tokens (with max_state_tokens), and text-only and multimodal records can be mixed in one batch. The systemone function mirrors the Jev/SystemOne POST /v1/systemone endpoint and returns answers with choice/confidence/probabilities, expected score/legend/probabilities, or the probability of true for noul.

Training and deployment

Clef-Flash is post-trained from Qwen3.5-9B (card tag post-train), with the joint schema head trained alongside it; the card documents no post-training data or hyperparameters. Tested with torch 2.11 and transformers 5.10.2 on a single H200 (pillow needed for images/videos). In Cloudflare's internal Decision Index 0.2.1 suite it is the fastest accurate decision model of the family: median latency 38.8 ms and p95 122.4 ms (Clef 27B: 209.3/238.6 ms) while leading several quality rows (BFCL 98.8, API-Bank 93.1, MMLU 91.8, ARC-Easy 99.5, WinoGrande 97.5, GPQA Diamond 51.0, ForecastBench Brier 10.6 - family best). On four Typesafe Evals business workflows (invoice processing, customer service, security incidents, agent trace observability) it scores 57.1/73.3, 77.0/76.0, 61.7, 61.7/69.8 - near Jev and ahead of Clef on customer service exact actions.

Training Data Post-trained from Qwen/Qwen3.5-9B (backbone Qwen/Qwen3.5-9B-Base with its vision encoder); no training data recipe documented.