TokForge-Bonsai-Image-4B-GGUF

TokForge-packaged Bonsai Image 4B / FLUX.2 Klein bundle for on-device Android image generation.

This repository contains the runtime files used by the TokForge Android image-generation route:

bonsai_klein_official_tq2g128.gguf — TokForge/sd.cpp GGUF conversion of the Bonsai Image 4B diffusion transformer.
Qwen3-4B-Q4_K_M.gguf — Qwen3-4B text encoder in GGUF Q4_K_M format.
flux2-vae.safetensors — FLUX.2 Klein VAE, renamed for TokForge bundle discovery.

Attribution: Bonsai Image is by Prism ML. FLUX.2 Klein is by Black Forest Labs, and the text encoder is based on Qwen3-4B by Qwen/Alibaba Cloud. This repository changes the deployment packaging and runtime formats only.

Recommended TokForge Route

This is a guarded beta image-generation bundle, not a universal default for every Android phone.

Device class	Route	Status
16-24 GB Qualcomm/Adreno	512x512, OpenCL, 2 steps	Quality Beta / Lab
12-16 GB Qualcomm/Adreno	512x512, OpenCL, 2-3 steps	Quality Beta / Lab after device proof
CPU, Tensor, Exynos, Mali, Xclipse	sub-512 or CPU preview	Preview only
Q8/OpenCL experiments	varies	Demoted until native quality is fixed

TokForge uses conservative labels:

Quality Beta requires coherent 512x512 output, repeatability, and no flat/corrupt image.
Preview is used for sub-512, CPU, low-memory, or visibly soft/warped outputs.
Lab is used for OpenCL/server paths that require explicit opt-in.

Inference Settings

The Bonsai route expects the published low-guidance FLUX.2 Klein/Bonsai-style recipe:

Setting	Value
Sampler	Euler
Scheduler	simple / FlowMatch-style
CFG scale	1.0
Distilled guidance	1.0
Flow shift	3.0
Default canvas	512x512
Default quality steps	2 on certified Adreno OpenCL

Higher step counts are not automatically better. TokForge currently treats 1-step output as too smeared for Quality Beta.

Files

File	Size	SHA-256
`bonsai_klein_official_tq2g128.gguf`	1.3 GB	`2a6da84102513a3a14a955edeb84ef0e347b51f9f13cc539c939ea78410a3eb7`
`Qwen3-4B-Q4_K_M.gguf`	2.4 GB	`7485fe6f11af29433bc51cab58009521f205840f5b4ae3a32fa7f92e8534fdf5`
`flux2-vae.safetensors`	161 MB	`ca70d2202afe6415bdbcb8793ba8cd99fd159cfe6192381504d6c4d3036e0f04`
`manifest.json`	metadata	Runtime recipe and route policy

Usage with TokForge

This bundle is intended for TokForge, a free Android app for private on-device AI.

Open TokForge.
Go to Models or Image Creation settings.
Download Bonsai Image 4B (TokForge).
Use natural chat phrasing such as generate an image of a red car on a city street, or use the image-generation chip/button path.

TokForge will unload/reload the chat model when needed on memory-constrained devices.

Validation Snapshot

TokForge fleet validation on 2026-05-31 found:

RedMagic high-memory Adreno: 512x512/2 OpenCL Quality Beta, around 80-81 seconds for the required prompt set.
Lenovo 12-16 GB Adreno: 512x512/2 OpenCL Quality Beta, around 130 seconds with normal one-shot helper; faster warm-server lab mode exists but is not part of the normal APK.
Tensor/Exynos/Mali/Xclipse and CPU routes remain Preview unless separately certified.

The sample contact sheet in samples/adreno_quality_beta_contact_sheet.png shows certified Adreno Quality Beta outputs for car, tree, restaurant, beach, house, and person prompts.

Limitations

This is a runtime bundle, not a standard Diffusers training checkpoint.
OpenCL acceleration is guarded and currently targeted at high-memory Qualcomm/Adreno devices.
Non-Adreno GPU paths are not release-green.
Low-memory CPU routes are Preview only.
The output quality gate is visual/coherence-first; faster blurry or flat routes are demoted.

Attribution

This bundle is derived from:

All credit for the model architecture, training, and source releases goes to the original authors. This repository packages converted/runtime files for TokForge mobile deployment.

Per the upstream notice: "Created using Bonsai Image by Prism ML."