Damkohler/FLUX.2-dev-Fun-Controlnet-Union-2602-JLC-FP8

FLUX.2-dev-Fun-Controlnet-Union-2602 — JLC FP8

A reproducibly generated mixed-FP8 E4M3FN quantized derivative of Alibaba-PAI's FLUX.2-dev-Fun-Controlnet-Union-2602.safetensors, produced independently by the JLC project.

This release is intended for the FLUX.2-dev Union ControlNet path in ComfyUI. It is not a FLUX.2 Klein ControlNet.

License: FLUX Non-Commercial License v2.1. Non-commercial use only. See LICENSE and NOTICE.md.

This is an independent derivative release. It is not an official product of, and has not been endorsed, approved, or validated by, Black Forest Labs Inc. or Alibaba-PAI.

Checkpoint

File: FLUX.2-dev-Fun-Controlnet-Union-2602-JLC-fp8mixed-e4m3fn.safetensors
Size: 4,306,658,528 bytes
Precision: 48 FP8 E4M3FN weights · 28 protected BF16 tensors · 96 FP32 scale tensors
Tensor keys: 172
SHA-256 fingerprint: b4f41f3e…b4360634ec — full checksum

The published checkpoint is byte-identical to the authoritative reproducibly generated and validated release artifact.

Examples

The examples below were generated with the release checkpoint. Each uses a single preprocessed ControlNet hint at strength 0.50, active across the full 0.00–1.00 inference interval. Only the hint / generated-output pair is shown; the licensed Adobe Stock source photographs are not embedded in these example files.

The selected set intentionally spans several different conditioning representations while showing two challenging articulated subjects.

DWPose — Ballerina

Pose-skeleton conditioning.

HED — Skater

Edge / line-structure conditioning.

DepthAnythingV2 — Skater

Depth / volume conditioning.

DSINE Normal Map — Ballerina

Surface-orientation / normal-map conditioning.

Color — Ballerina

Low-frequency color / spatial-layout conditioning.

ComfyUI workflow

This sample ComfyUI workflow demonstrates multi-control conditioning with the JLC FP8 checkpoint. It combines DWPose, HED, and DepthAnythingV2 hints and can be used as a starting point for reproducing examples like those shown above. Both the PNG and JSON are ready for direct loading into ComfyUI; the PNG can also be drag-and-dropped onto the ComfyUI canvas.

Download the workflow JSON

What was quantized

This is a selective mixed-precision checkpoint, not a global FP8 cast.

The JLC quantization policy stores 48 large weight tensors as FP8 E4M3FN, retains 28 protected tensors in BF16, and adds 96 FP32 scale tensors used by the mixed-precision execution path.

The immediate source checkpoint is:

• Publisher: Alibaba-PAI
• Repository: alibaba-pai/FLUX.2-dev-Fun-Controlnet-Union
• Checkpoint: FLUX.2-dev-Fun-Controlnet-Union-2602.safetensors
• Source SHA-256 fingerprint: 516532a8…b0a7a794 — full checksum

Validation

The release artifact passed the following acceptance checks:

• toolkit-driven quantization: PASS
• independent reopened-file verification: PASS
• 172 / 172 tensor payloads reproduced byte-for-byte against the independently generated FP8 validation reference
• native ComfyUI mixed-precision load: PASS
• matched runtime validation at 1024 × 1536: pixel-identical against the validated FP8 reference artifact

These results establish deterministic reproduction and successful execution in the validated environment. They do not claim universal numerical identity across every hardware platform, workflow, attention backend, resolution, or future software version.

ComfyUI use

This checkpoint is supported through JLC Flux2 ControlNet v1.1.0 or later:

https://github.com/Damkohler/JLC-Flux2-ControlNet

Place the checkpoint in your ComfyUI ControlNet model directory and select it with JLC Flux2 ControlNet Loader.

The unified loader automatically supports compatible dense BF16 FLUX.2 Fun ControlNet checkpoints and the JLC mixed FP8/BF16 Union-2602 checkpoint through the same runtime node family. No separate FP8 loader, Apply node, or FP8-specific workflow path is required.

The remaining JLC Flux2 ControlNet nodes—including Apply, Orchestrator, reference-image conditioning, cache preparation, and experimental in/out-paint support—operate through the same shared ControlNet runtime interface.

Validated example workflows are provided with the JLC Flux2 ControlNet release.

Reproducibility

The quantization/calibration toolkit and detailed reproducibility, validation, provenance, and methodology materials used to produce this checkpoint are currently being prepared for public release.

The release artifact itself has already completed the validation summarized above.

The toolkit publication will provide the supporting material for reproducing and independently verifying the mixed FP8/BF16 checkpoint from the original BF16 source. Model inference does not depend on the toolkit and is supported through the public JLC Flux2 ControlNet package linked above.

License and attribution

The checkpoint is a derivative of a FLUX model and is not relicensed under MIT, Apache-2.0, GPL, or another permissive software/model license.

The model derivative is distributed under the FLUX Non-Commercial License v2.1 included in LICENSE. No commercial or production rights are granted by this repository.

The required Black Forest Labs attribution, source-model attribution, modification statement, and non-endorsement statement are reproduced in NOTICE.md.

The JLC software used to produce and run the model is licensed separately in its respective software repositories; those software licenses do not relicense this checkpoint.

Author / derivative project

Independent mixed-FP8 quantization and validation work:

JLC / José Luis Cordova

The repository metadata points to Black Forest Labs' current FLUX.2-dev license page; the complete license text is also included locally in this repository.