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Can the UDOO BOLT V8 (32 GB) run FLUX 3 Image Klein?

89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.

Yes, but slowly

Slow. At FP8 it needs about 12.4 GB of 16.0 GB usable and takes about 1.9 min per image.

Best precision
FP8
Memory mode
Everything on GPU
Time per image
1.9 min
Output
1024×1024, 16 steps

Best app to run it on the UDOO BOLT V8 (32 GB)

On Windows

ComfyUI

Desktop app · runs on PyTorch (ComfyUI), GGUF via ComfyUI-GGUF

  • Can only use the CPU on this hardware, so it will be slow.
  • Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Get ComfyUI

  • Invoke Can only use the CPU on this hardware, so it will be slow.
  • SwarmUI Can only use the CPU on this hardware, so it will be slow.

On Linux

ComfyUI

Desktop app · runs on PyTorch (ComfyUI), GGUF via ComfyUI-GGUF

  • Can only use the CPU on this hardware, so it will be slow.
  • Runs this model with built-in or popular custom nodes; GGUF files load with ComfyUI-GGUF.

Get ComfyUI

  • Invoke Can only use the CPU on this hardware, so it will be slow.
  • SwarmUI Can only use the CPU on this hardware, so it will be slow.

How we choose: the files published for this model, your operating system and GPU, whether it fits fully in memory, and published speed tests (MLX vs llama.cpp on Apple silicon, vLLM vs llama.cpp vs Ollama on NVIDIA). Details.

Download FLUX 3 Image Klein

Quantized files · GGUF for ComfyUI

Smaller GGUF versions for ComfyUI (with the ComfyUI-GGUF node). No sign-in needed; the model’s license still applies.

huggingface.co/unsloth/flux-3-image-klein-GGUF (opens in a new tab)

Original weights · Hugging Face

Full-precision files from Black Forest Labs, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/black-forest-labs/flux-3-image-klein (opens in a new tab)

Free Hugging Face account needed: accept the license on the model page and the download starts right away.

Official repo · GitHub

Reference code, inference scripts and docs from Black Forest Labs. The weights themselves download from Hugging Face.

github.com/black-forest-labs/flux-3-image-klein (opens in a new tab)

git clone https://github.com/black-forest-labs/flux-3-image-klein

Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at FP8, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Slow
How well it runs on the UDOO BOLT V8 (32 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.40.1 / 45
Memory fitFull marks when the model fits in the share of unified memory the GPU can use; fewer when it goes past that limit.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.4.4 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Match score84.6 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every precision on the UDOO BOLT V8 (32 GB)

Quant Memory needed Available Speed Memory mode Runs Quality Download
FP16 13.5 GB 16.0 GB 2.2 min Text encoder offloaded Very slowencoder unloaded after use 91Excellent quality (A+) · 91 of 100: how capable the model is at FP16, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)
FP8 12.4 GB 16.0 GB 1.9 min Everything on GPU Slow 89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)
Q8 GGUF 12.8 GB 16.0 GB 2.4 min Everything on GPU Very slow 90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)
Q4 GGUF 10.2 GB 16.0 GB 2.6 min Everything on GPU Very slow 84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. GGUF (opens in a new tab)

Other hardware that runs it

Quick answers

How much memory does FLUX 3 Image Klein need on the UDOO BOLT V8 32GB?

At FP8 it needs about 12.4 GB. The UDOO BOLT V8 32GB has 16.0 GB usable.

How long does FLUX 3 Image Klein take on the UDOO BOLT V8 32GB?

About 1.9 min per image at FP8 and default settings, an estimate scaled from a reference timing by this hardware’s compute speed.

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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