Model reference · open weights

Chroma1-HD

Chroma1-HD is an open-weight image model from lodestones, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Image lodestones 1 variants 73k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What Chroma1-HD is

Chroma1-HD Chroma1-HD is an 8.9B parameter text-to-image foundational model based on FLUX.1-schnell. It is fully Apache 2.0 licensed, ensuring that anyone can use, modify, and build upon it. As a base model, Chroma1 is intentionally designed to be an excellent starting point for finetuning. It provides a strong, neutral foundation for developers, researchers, and artists to create specialized models. for the fast CFG "baked" version please go to Chroma1-Flash. Key Features High-Performance Base: 8.9B parameters, built on the powerful FLUX.1 architecture. Easily Finetunable: Designed as an ideal checkpoint for creating custom, specialized models. Community-Driven & Open-Source: Fully transparent with an Apache 2.0 license, and training history. Flexible by Design: Provides a flexible foundation for a wide range of generative tasks. Special Thanks A massive thank you to our supporters who make this project possible. Anonymous donor whose incredible generosity funded the pretraining run and data collections. Your support has been transformative for open-source AI. Fictional.ai for their fantastic support and for helping push the boundaries of open-source AI. You can try Chroma on their platform: [](https://fictional.ai/?ref=chromahf) How to Use diffusers Library install the requirements pip install transformers diffusers sentencepiece accelerate Quantized inference using gemlite ComfyUI For advanced users and customized workflows, you can use Chroma with ComfyUI. Requirements: A working ComfyUI installation. Chroma checkpoint (latest version). T5 XXL Text Encoder. FLUX VAE. Chroma Workflow JSON. Setup: 1. Place the T5xxl model in your ComfyUI/models/clip folder. 2. Place the FLUX VAE in your ComfyUI/models/vae folder. 3. Place the Chroma checkpoint in your ComfyUI/models/diffusionmodels folder. 4. Load the Chroma workflow file into ComfyUI and run. Model Details Architecture: Based on the 8.9B parameter FLUX.1-schnell model. Training Data: Trained on a 5M sample dataset curated from a 20M pool, including artistic, photographic, and niche styles. Technical Report: A comprehensive technical paper detailing the architectural modifications and training process is forth

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makerlodestones
TypeImage models
Parameters (lead)8.9B
Variants1
Runs withdiffusers
Released2025-08-08
Popularity73k downloads / month
Likes399
LicenceOpen weights

How it works

How image models work

Text promptwhat to makeText encoderunderstands itDiffusion stepsdenoise to pixelsImagePNG / JPEGA diffusion model starts from noise and denoises it, guided by your prompt, into a finished image.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
Chroma1-HD8.9BBF16~20.5 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys chroma1-hd for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (chroma1-hd below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"chroma1-hd","prompt":"a red bicycle","size":"1024x1024"}'

Details

Languages, data & research

Tags

diffusers safetensors text-to-image diffusers:ChromaPipeline deploy:azure

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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