StillDeadcode/minimax-h3-fp8

MiniMax-H3, FP8 — radiance container

MiniMaxAI/MiniMax-H3 — video with a synchronized stereo soundtrack from text — as a single .rad container for the radiance inference engine (AMD RDNA4, ROCm).

The MiniMax H3 Community License does not cover the European Union, the United Kingdom, the Republic of Korea or the United States of America; see License.

File	minimax-h3-fp8.rad — 60.54 GiB
Weights	every linear of the text encoder (the 50 layers of Qwen3-VL-32B the model reads), the token refiner and the DiT's 50 blocks, and the modulation projections, FP8 E4M3 per 128×128 block (bf16 scales); the video decoder bf16; the audio decoder f32
Latent upscaler	LBH-123-AI/Minimax_h3_latent_Upscaler v1 (3D conv, 345M parameters, bf16; Apache-2.0)
Output	MP4: H.264 at 24 fps, up to 1344x768, 5.17 to 14.4 s; AAC at 32 kHz stereo
Needs	radiance 1.8.1 or newer (the upscaler, and prompts over 128 tokens, need 1.8.1); two 32 GB cards and about 39 GiB of pinned host memory

Serve

radiance --model minimax-h3-fp8.rad --tp 2 --vision-tower-placement ram --host 0.0.0.0 --port 8000

curl -s http://localhost:8000/v1/videos -H 'Content-Type: application/json' -d '{
  "prompt": "A red fox trotting through a snowy pine forest, snow crunching underfoot",
  "seconds": "5", "size": "1344x768", "seed": 7}'          # -> {"id": "video_...", "status": "queued", ...}
curl -s http://localhost:8000/v1/videos/video_...            # poll until "status": "completed"
curl -s http://localhost:8000/v1/videos/video_.../content -o fox.mp4

The server speaks OpenAI's video jobs API (POST /v1/videos, GET /v1/videos/{id}, GET /v1/videos/{id}/content, list and delete), and SGLang's target field:

• prompt is read as written, up to 2048 tokens; the model follows long structured descriptions (the shot, its soundscape, its music) best.
• seconds is rounded up to the model's length steps (17 frames): 5.17 to 14.4 s. size is WIDTHxHEIGHT, multiples of 32, at most 1344x768 pixels of area.
• seed makes a video repeatable on the same deployment; num_inference_steps counts sigma grid points as diffusers does (50 by default, at most 65). The model is guidance-distilled: no guidance scale, no negative prompt.
• Text to video and audio only; the image- and reference-conditioned forms are not in this file.

On two Radeon AI PRO R9700s (gfx1201) a 5.17 s clip at 1344x768 takes about 8.8 minutes at the default 50 steps. The text encoder and the modulation projections are read from pinned host memory, which --vision-tower-placement ram selects. For the eight-step distillation, see StillDeadcode/fasth3-8-step-v2-fp8.

From the same conditioning and noise, the first step's velocity is 5.4% (video) and 4.3% (audio) from diffusers' bf16 pipeline, about what the reference itself moves with its linears rounded to FP8 the same way (6.8% and 4.6%). Given the same latents, the video decoder is 36.9 dB PSNR from the reference's (H.264 included) and the audio decoder 51.0 dB SNR.

Latent upscaling

The container carries LBH-123-AI's latent upscaler. A request with "latent_upscale": 2 runs its first steps at half the size (672x384 for 1344x768), the upscaler enlarges the clean latent, and the last upscale_refine_steps (12 by default) run at the full size from a re-noised copy of it:

curl -s http://localhost:8000/v1/videos -H 'Content-Type: application/json' -d '{
  "prompt": "...", "seconds": "5", "size": "1344x768", "seed": 7, "latent_upscale": 2}'

5.17 s at 1344x768, 50 steps, 2x R9700	time
native	8.8 min
latent_upscale 2, 12 refine steps (the default)	3.4 min
latent_upscale 2, 20 refine steps	4.5 min

The factor goes up to 4, but at 1344x768 a factor of 4 starts from 352x192, which is too small for the model to lay out a clean scene: expect soft, ghosted frames. The video object of an upscaled video reports latent_upscale, upscale_refine_steps and upscale_from (the small size).

How this file was made

rad-convert MiniMaxAI/MiniMax-H3 --recipe minimax-h3-fp8.recipe -o minimax-h3-fp8.rad

MiniMaxAI/MiniMax-H3 is the downloaded pipeline directory; only its text-to-video-and-audio components are read (text_encoder/, transformer/, vae/, audio_vae/, the processor, the tokenizer and both schedulers), and the upscaler as a companion folder latent_upscaler/ (its minimax_h3_latent_upscaler_3d_conv_v1/config.json and bf16 weights, renamed diffusion_pytorch_model.safetensors). This file had it added to the 1.8.0 container in place (rad-convert ... --reuse minimax-h3-fp8.rad --in-place), which leaves every other weight as it was. The recipe (minimax-h3-fp8.recipe in this repository) names what is quantised; everything it does not name is the checkpoint's own dtype:

te.blk.*.attn_qkv.weight             rtn  codes=fp8_e4m3 block=128x128 scale=bf16
te.blk.*.attn_output.weight          rtn  codes=fp8_e4m3 block=128x128 scale=bf16
te.blk.*.ffn_gate_up.weight          rtn  codes=fp8_e4m3 block=128x128 scale=bf16
te.blk.*.ffn_down.weight             rtn  codes=fp8_e4m3 block=128x128 scale=bf16
te.blk.*.attn_norm.weight            cast dtype=f32
te.blk.*.ffn_norm.weight             cast dtype=f32
ref.blk.*.attn_qkv.weight            rtn  codes=fp8_e4m3 block=128x128 scale=bf16
ref.blk.*.attn_output.weight         rtn  codes=fp8_e4m3 block=128x128 scale=bf16
ref.blk.*.ffn_gate_up.weight         rtn  codes=fp8_e4m3 block=128x128 scale=bf16
ref.blk.*.ffn_down.weight            rtn  codes=fp8_e4m3 block=128x128 scale=bf16
dit.blk.*.attn_qkv.weight            rtn  codes=fp8_e4m3 block=128x128 scale=bf16
dit.blk.*.attn_output.weight         rtn  codes=fp8_e4m3 block=128x128 scale=bf16
dit.blk.*.ffn_gate_up.weight         rtn  codes=fp8_e4m3 block=128x128 scale=bf16
dit.blk.*.ffn_down.weight            rtn  codes=fp8_e4m3 block=128x128 scale=bf16
dit.blk.*.ada*.weight                rtn  codes=fp8_e4m3 block=128x128 scale=bf16
vae.blk.*.attn_qkv.weight            cast dtype=bf16
vae.blk.*.attn_out.weight            cast dtype=bf16
vae.blk.*.ffn_up.weight              cast dtype=bf16
vae.blk.*.ffn_down.weight            cast dtype=bf16
vae.proj_out.*                       cast dtype=bf16
aud.*.weight                         cast dtype=f32
ups.embed.*                          cast dtype=f32
ups.*.emb_layers.*                   cast dtype=f32

License

MiniMax H3 is licensed under the MiniMax H3 Community License Agreement, Copyright © 2026 MiniMax (LICENSE in this repository; NOTICE carries its notice). The agreement grants its rights only within its Applicable Territory: worldwide except the European Union, the United Kingdom, the Republic of Korea and the United States of America, where it does not license using, reproducing or distributing the model or this file. Its use restrictions and Acceptable Use Policy (Exhibit A of LICENSE) apply to everyone who downloads or uses this file, and to anyone it is passed on to.

This container is a modified copy of MiniMax H3: the linears named above are re-encoded as FP8, the video decoder's linears cast from f32 to bf16, the audio decoder's weight norms folded, the text encoder's last 14 layers (which the model does not read) left out, and everything repacked into one .rad file. The text encoder is Qwen3-VL-32B, licensed under the Apache License 2.0 (LICENSE-Qwen3-VL). The latent upscaler is LBH-123-AI's Minimax_h3_latent_Upscaler v1, licensed under the Apache License 2.0 (LICENSE-latent-upscaler); its weights are included as published, its embedding MLP cast from bf16 to f32.