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Ideogram4 Image Model Optimized for 16GB Apple Silicon Macs

A developer has successfully optimized the Ideogram4 image generation model to run on a 16GB Apple Silicon Mac, specifically an M2 Pro. This optimization, achieved through native MLX kernels and NF4 quantization, allows for 512x512 image generation in approximately 11 minutes with a peak memory usage of 11.51 GB. The developer has also released the code and a live demo, noting that this NF4 version is faster than mFLUX FP8 and GGUF Q4 on comparable hardware. AI

IMPACT Enables running advanced image generation models on consumer-grade hardware with limited RAM.

RANK_REASON This is a user-created optimization and demo of an existing model, not a release from the original model creators.

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Ideogram4 Image Model Optimized for 16GB Apple Silicon Macs

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/amateur_Engineer ·

    I made Ideogram4 NF4 run on 16GB: 512x512 in ~11 min at 11.51 GB peak on a 16GB M2 Pro. You can run it yourself. Demo live on the little box right now.

    <table> <tr><td> <a href="https://www.reddit.com/r/StableDiffusion/comments/1u5o958/i_made_ideogram4_nf4_run_on_16gb_512x512_in_11/"> <img alt="I made Ideogram4 NF4 run on 16GB: 512x512 in ~11 min at 11.51 GB peak on a 16GB M2 Pro. You can run it yourself. Demo live on the little…