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Cosmos3-Super-Text2Image-4Step-INT8-G64-BF16
JuliaML/Cosmos3-Super-Text2Image-4Step-INT8-G64-BF16
Cosmos3-Super-Text2Image-4Step-INT8-G64-BF16 is a text-to-image model from JuliaML. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as other.
Independent transformer-only quantization of nvidia/Cosmos3-Super-Text2Image-4Step. This is not an official NVIDIA release.
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Public
Updated Aug 8, 2026
Parameters
65B
69.5 GB on disk
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Repo makeup
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.safetensors69.5 GB · 100%
Parameter types
How the weights are stored.
I862.4B · 96%
Base models
Model card
From the Hugging Face model README
Cosmos3 Super Text-to-Image 4-Step — INT8 G64 BF16
Independent transformer-only quantization of
nvidia/Cosmos3-Super-Text2Image-4Step.
This is not an official NVIDIA release.
Base revision: 0573a4b26b8e15d13d416e51f4680c8bc8b8c33d.
Runtime, verification and benchmark code:
gtrg55/cosmos3-quant-mlx-cuda.
Format
| Property | Value |
|---|---|
| Quantization | weight-only signed symmetric INT8 (W8A16) |
| Group size | 64 |
| Compute / activations | BF16 |
| BF16 transformer I/O | proj_in, proj_out |
| Quantized matrices | 898 |
| Transformer safetensors | 64.77 GiB |
| SVD / Hadamard / dynamic allocation | disabled |
| Base sampler | original distilled 4-step schedule, guidance 1.0 |
The repository contains the quantized transformer. Tokenizer, VAE and scheduler are loaded from the original NVIDIA model.
Validation status
- Apple MLX / M4 Max: validated end-to-end at 1024×1024.
- Checkpoint packing: exact sample round-trip verified.
- CUDA: loader and test command are supplied in the companion code repo; publish a CUDA performance claim only after completing the included RunPod test.
Reference M4 Max result: 70.54 seconds generation, 67.63 GiB MLX peak memory. Hardware, thermals and software versions affect timings.
Download and run on Apple Silicon
hf download nvidia/Cosmos3-Super-Text2Image-4Step \
--revision 0573a4b26b8e15d13d416e51f4680c8bc8b8c33d \
--local-dir models/Cosmos3-Super-Text2Image-4Step
hf download JuliaML/Cosmos3-Super-Text2Image-4Step-INT8-G64-BF16 \
--local-dir checkpoints/Cosmos3-INT8
python mlx/run_pipeline.py \
--model models/Cosmos3-Super-Text2Image-4Step \
--checkpoint checkpoints/Cosmos3-INT8/transformer \
--prompt prompts/winter-spruce-tall-1024.json \
--latents benchmarks/latents/cpu-seed1143-1024x1024-bf16.safetensors \
--output outputs/int8.png \
--height 1024 --width 1024 --seed 1143
Runtime code and pinned requirements are maintained in the companion GitHub repository.
Reproducibility assets
examples/ contains the exact structured prompt, fixed BF16 latent, generation
configuration, output image and run report. Important hashes:
- prompt SHA-256:
3271fe4b38b1882cde4d3c87a4d4ae260c568cf4ab2d35c5d0f32bb12b1ba936 - latent SHA-256:
6504206b2452a23680cac73d5763e3796260f7582f40ff59e6613cdb33f0aca6 - reference PNG SHA-256:
22e3724df99afa953699f46c6529c042b4d37e505d39fef99da6c03c1f59b8b9
Limitations
- INT8 remains extremely close to the affine W8 control in the included test, but this one prompt is not a comprehensive evaluation.
- This is weight-only quantization, not integer activation inference.
- Safety behavior is inherited from the base pipeline and the user's runtime configuration.
License and attribution
Distributed under OpenMDW-1.1. See LICENSE and NOTICE. The original NVIDIA
notices and license must remain with redistributed model materials.
- Task
- Text-to-Image
- Library
- diffusers
- License
- other
- Created
- Aug 8, 2026
- Updated
- Aug 8, 2026