10Eros-Max-ref2va-Beta2

About

What 10Eros-Max-ref2va-Beta2 is

10Eros-Max-Ref2VA-Beta2-Pruned (GGUF) This repository contains heavily optimized GGUF quantizations of TenStrip/10Eros-Max (specifically the 10ErosMaxh3ref2vabeta2pruned version). These models are designed to run in ComfyUI natively via ComfyUI-GGUF, allowing users with consumer GPUs (12GB - 16GB VRAM) to run this massive 40GB+ MiniMax-H3 model locally. The ref2va version features TenStrip's specific grafting recipe combining weights from LTX, Wan, and Krea. 📦 Available Quantizations 🚀 How to Use in ComfyUI 1. Install Custom Node: Install ComfyUI-GGUF (by city96) via the ComfyUI Manager. 2. Download Model: Download your preferred .gguf file (Q4KM is recommended). 3. Placement: Place the downloaded .gguf file inside your ComfyUI/models/unet directory. 4. Workflow: Replace your standard Load Diffusion Model node with the Unet Loader (GGUF) node. ⚙️ Recommended Inference Settings Note: This is the Standard / Pruned Beta 2 version, NOT the Turbo version. Steps: 20 to 30 CFG Scale: ~3.5 to 4.5 Sampler/Scheduler: Standard MiniMax flow matching settings (e.g., euler / simple or flowmatch) 📜 Original Model Information & Credits All credit for the underlying model architecture, grafting methodology, and training goes to TenStrip and the MiniMax team. From the Original Creator (TenStrip): For TURBO model use: multires/simple 6 steps, ersde/simple 6 steps, or I prefer and merged it for ersde with custom 7 step sigmas to get rid of motion noise details. Ersde/simple and custom sigma string instead of basic scheduler: [1.00, 0.94, 0.83, 0.72, 0.55, 0.30, 0.10, 0.00] Turbo from silveroxides/MiniMax-H3tests/tree/main with silu(temb) grid restored before merge. Due to a ton of confusion I've let Claude compile a full MD on the grafting, including code and methodology as it was mostly used to create code, document, and manage the graft project while I tested, architected, and mixed. I was keeping that to myself since maybe it'd actually be nice to have something to myself but after a handful of ignorant comments I'm open sourcing everything from it except the scripts themselves. You can hand the md back to claude or any competent agent and graft in the same way or have them expl

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

Specifications

What it is

How it works

How video models work

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.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys 10eros-max-ref2va-beta2 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (10eros-max-ref2va-beta2 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/videos/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"10eros-max-ref2va-beta2","prompt":"a drone shot over a forest"}'

Details

Languages, data & research

Licence

Commercial licence needed

Sources

Weights & code

Explore

More video models