MiniMax H3 Image on LattePanda Sigma (32 GB)

Can the LattePanda Sigma (32 GB) run MiniMax H3 Image?

No, it doesn’t fit

No. MiniMax H3 Image needs about 16.0 GB even at FP8; the LattePanda Sigma (32 GB) has 16.0 GB usable.

Download MiniMax H3 Image

Original weights · Hugging Face

Full-precision files from MiniMax, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/MiniMaxAI/MiniMax-H3-Image (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from MiniMax. The weights themselves download from Hugging Face.

github.com/MiniMax-AI/MiniMax-H3-Image (opens in a new tab)

git clone https://github.com/MiniMax-AI/MiniMax-H3-Image

Links checked 7 hours ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 12/100 (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 Won't run: How well it runs on the LattePanda Sigma (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.	12.3 / 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.	0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	0.0 / 15
Match score	12.3 / 100

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

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

Every precision on the LattePanda Sigma (32 GB)

Quant	Memory needed	Available	Speed	Memory mode	Runs	Quality	Download
`FP16`	27.5 GB	16.0 GB	—	—	Won't run	93Excellent quality (A+) · 93 of 100: how capable the model is at FP16, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)
`FP8`	16.0 GB	16.0 GB	—	—	Won't run	91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Hardware that can run it

91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 96/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell FP8 · 6.6 s · Runs great
91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. AMD Ryzen AI Max+ 395 (128 GB) FP8 · 17 s · Runs well
91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX Spark N1X (6144-core GPU) (128 GB) FP8 · 20 s · Runs well
91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GB10 (128 GB) FP8 · 19 s · Runs well
91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Apple M2 Ultra (192 GB) FP8 · 39 s · Runs well
91Excellent quality (A+) · 91 of 100: how capable the model is at FP8, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Apple M3 Ultra (256 GB) FP8 · 38 s · Runs well

Models that do run on the LattePanda Sigma (32 GB)

76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4B FP8 · 17 s
89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image Klein FP8 · 1.6 min
82Great quality (A) · 82 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. Z-Image Turbo FP8 · 42 s
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image Turbo FP8 · 53 s
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 9B FP8 · 31 s

Quick answers

How much memory does MiniMax H3 Image need on the LattePanda Sigma 32GB?

Even at FP8 it needs about 16.0 GB; the LattePanda Sigma 32GB has 16.0 GB usable.

What can the LattePanda Sigma 32GB run instead?

FLUX.2 [klein] 4B, FLUX 3 Image Klein and Z-Image Turbo run best on it; the page lists more, each with its speed.

What hardware can run MiniMax H3 Image?

NVIDIA RTX PRO 6000 Blackwell 96GB, AMD Ryzen AI Max+ 395 128GB and NVIDIA RTX Spark N1X (6144-core GPU) 128GB run it; the page lists more, each with its 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.