Reference to video · Ref2VA · Measured on a 12GB card

video_minimax_h3_r2v.json explained

Use this page to understand the R2V template's reference behavior, install its required files, and interpret two measured runs without treating the results as a promise for another machine.

Measured 2026-08-11 · Two independent runs · Independent guide, not affiliated with MiniMax or Comfy-Org

Reference behavior

What this template does

R2V uses an image, video or audio as a semantic and motion reference for a newly generated clip. It does not guarantee frame-by-frame alignment, and it does not provide the denoise-strength control found in traditional diffusion editing.

The template may reconstruct the scene, crop the reference, or reorder actions and shots. If the job requires frame-by-frame preservation, an exact lip-sync timeline or a pixel-level mask, evaluate a dedicated video-editing tool for that requirement.

Install and verify

Files this template needs

ComfyUI/
└── models/
    ├── diffusion_models/
    │   └── minimax_h3_ref2va_pruned_int8_convrot.safetensors
    ├── text_encoders/
    │   └── qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors
    └── vae/
        ├── minimax_h3_video_vae_fp16.safetensors
        └── minimax_h3_audio_vae_fp32.safetensors

The R2V template loads minimax_h3_ref2va_pruned_int8_convrot.safetensors, approximately 20.97GB. Ref2VA and the FL2VA file loaded by T2V and I2V are separate diffusion-model downloads.

Sources: ComfyUI MiniMax H3 tutorial and Comfy-Org MiniMax-H3 repository. Checked 2026-08-13.

1

Update ComfyUI

Use ComfyUI 0.30.0 or newer and restart it before importing the template.

2

Download the Ref2VA weights

The R2V template loads the Ref2VA diffusion model, which is a separate download from the FL2VA file used by T2V and I2V.

3

Place the files

Put diffusion models in ComfyUI/models/diffusion_models, the Qwen3-VL encoder in ComfyUI/models/text_encoders, and both VAE files in ComfyUI/models/vae.

4

Set the CLIP loader type

Select minimax as the CLIP Loader type, otherwise the text encoder will not load.

5

Run one short test

Run a short clip at a small canvas first, confirm one success, then change one variable at a time.

Site test card

Our measured run

Conditions for every figure in this test card: physical GPU 0 was an RTX 3060 12GB; Proxmox VE VM 100 had 16 vCPU, 47.05 GiB RAM and no swap; ComfyUI 0.31.0 used PyTorch 2.13.0+cu130; the official R2V template loaded Ref2VA pruned INT8 at 1344×768 for 124 frames with a fixed seed; audio, Turbo LoRA and SageAttention were not enabled.

FieldRun 1Run 2
Test IDSITE-3060-R2V-GPU0-B1SITE-3060-R2V-GPU0-B1-RUN2
Wall time2,581.8 s2,579.8 s
Peak VRAM11,649 MiB / 12,288 MiB (94.8%)11,649 MiB / 12,288 MiB (94.8%)
Peak system RAM43,587 MiB43,907 MiB
GPU temp peak74 °C74 °C
Output SHA-256cc2a6f75…be6060fSame as Run 1

The two output SHA-256 values were identical. In this fixed environment with a fixed seed, the result was deterministically reproducible.

The site run and the community “3060 / 10 minutes” claim have different conditions. Therefore, these measured figures are neither a comparison with nor evidence for that community timing claim.

Failure boundary

The hardware failure we hit

Conditions for this same-load incident telemetry: physical GPU 1 was used for the failed attempt and physical GPU 0 for the comparison; Proxmox VE VM 100 had 16 vCPU, 47.05 GiB RAM and no swap; ComfyUI 0.31.0 used PyTorch 2.13.0+cu130; the official R2V template loaded Ref2VA pruned INT8 at 1344×768 for 124 frames with a fixed seed; audio, Turbo LoRA and SageAttention were not enabled.

One attempt on physical GPU 1 froze the entire host VM and required a manual cold start. The root cause was abnormal cooling at that card's physical location: under the same load, GPU 1 reached 79 °C while GPU 0 reached 60 °C, a 19 °C difference. After moving the work to GPU 0, both formal runs completed without the fault.

The root cause was not memory exhaustion. Sampling during the freeze showed MemAvailable on an approximately 4.9GB plateau, without the pattern of progressive depletion.

FAQ

Frequently asked questions

Conditions for the site-measured figures below: physical GPU 0 was an RTX 3060 12GB; Proxmox VE VM 100 had 16 vCPU, 47.05 GiB RAM and no swap; ComfyUI 0.31.0 used PyTorch 2.13.0+cu130; the official R2V template loaded Ref2VA pruned INT8 at 1344×768 for 124 frames with a fixed seed; audio, Turbo LoRA and SageAttention were not enabled.

How long does video_minimax_h3_r2v.json take on an RTX 3060 12GB?

On our test machine one 1344x768 run of 124 frames took 2,581.8 seconds, or about 43 minutes. A second identical run took 2,579.8 seconds and produced a byte-identical output file.

Does video_minimax_h3_r2v.json fit in 12GB of VRAM?

Yes, but with almost nothing to spare. Peak VRAM was 11,649 MiB of the card's 12,288 MiB, which is 94.8 percent. The same run peaked at 43,587 MiB of system RAM, so system memory is the tighter constraint.

Which diffusion model does the R2V template load?

Ref2VA. The T2V and I2V templates both load FL2VA instead, so running R2V requires downloading a second diffusion model of about 20.97GB.

Next checks

Related guides