MiniMax-H3 FL2VA and Ref2VA (pruned) 4-step and 8-step LightX2V Turbo: INT8 ConvRot

These are the pruned MiniMax-H3 FL2VA and Ref2VA transformers from Comfy-Org/MiniMax-H3 with a full-rank LightX2V Turbo LoRA merged in, quantized to INT8 ConvRot. All four were made the same way and differ only in the base model and the LoRA:

File Base model Steps Same layout as (Comfy-Org diffusion_models/)
minimax_h3_fl2va_pruned_turbo_4step_v1.3_int8_convrot.safetensors FL2VA 4 minimax_h3_fl2va_pruned_int8_convrot.safetensors
minimax_h3_ref2va_pruned_turbo_4step_v1.0_int8_convrot.safetensors Ref2VA 4 minimax_h3_ref2va_pruned_int8_convrot.safetensors
minimax_h3_fl2va_pruned_turbo_8step_v1.1_int8_convrot.safetensors FL2VA 8 minimax_h3_fl2va_pruned_int8_convrot.safetensors
minimax_h3_ref2va_pruned_turbo_8step_v1.1_int8_convrot.safetensors Ref2VA 8 minimax_h3_ref2va_pruned_int8_convrot.safetensors

The tensor names and order, dtypes, shapes, data offsets and .comfy_quant descriptors all match the Comfy-Org file. The difference is that the distillation is baked in, so you don't need a LoRA loader.

Modified files: the weights differ from the MiniMax-H3 release, as described under How they were made.

Layout: every block linear (blocks.N.attn.{qkv_proj,out_proj}, blocks.N.mlp.{fc1,fc2}) is INT8 and has its own .comfy_quant tensor ({"format": "int8_tensorwise", "convrot": true, "convrot_groupsize": 256}) and a per-row F32 weight_scale. Everything else keeps the Comfy-Org dtype.

Examples

FL2VA, 4 steps

Steps CFG Size Frames Seed Sampler Shift (video / audio)
4 1.0 1344×768 124 at 24 fps 42 LightX2V Turbo 6 / 3

A cinematic view of an ancient floating city suspended above a sea of cumulus clouds. The camera begins in a wide establishing shot and slowly dollies in toward the city, gliding forward through the soft pastel cloudscape as its intricate, hand-drawn architecture comes into view. A waterfall cascades from the city's edge into the clouds, while shafts of golden sunlight break through the cumulus clouds and illuminate the ultra-detailed digital painting.

This render used SageAttention with sparse attention at density 0.15 (first step dense) as described here.

Ref2VA, 4 steps

Steps CFG Size Frames Seed Sampler Shift (video / audio)
4 1.0 1344×768 124 at 24 fps 43 LightX2V Turbo 6 / 3

A close-up of a small wooden fishing boat in a stormy green sea at night, rain lashing the deck, while the floating city from <Picture 1> hangs in the sky far above and lightning flashes behind it. Handheld camera. Loud thunder and crashing waves.

<Picture 1> is the first frame of the FL2VA example above, scaled to match the output size. This render used the same attention setup as the FL2VA example: SageAttention with sparse attention at density 0.15 (first step dense).

FL2VA, 8 steps

Steps CFG Size Frames Seed Sampler Shift (video / audio)
8 1.0 1344×768 124 at 24 fps 42 LightX2V Turbo 6 / 3

Same prompt and render setup as the 4-step FL2VA example.

Ref2VA, 8 steps

Steps CFG Size Frames Seed Sampler Shift (video / audio)
8 1.0 1344×768 124 at 24 fps 43 LightX2V Turbo 6 / 3

Same prompt and render setup as the 4-step Ref2VA example. <Picture 1> is the first frame of the 8-step FL2VA example above.

Sampling

Use each LightX2V Turbo student's own operating point: 4 steps for the 4-step files and 8 steps for the 8-step files, CFG 1 (no classifier-free guidance), video time shift 6 and audio shift 3. Workflows are in the LightX2V Turbo repository.

Both examples were rendered in Nox with the LightX2V Turbo sampler (Euler). For Ref2VA, refer to references in the prompt as <Picture i>, <Video k> and <Audio j>.

How they were made

<variant> below is fl2va or ref2va, <lora_variant> is fl2v or ref2v, and <steps> is 4step or 8step. <version> is 1.3 for FL2VA 4-step, 1.0 for Ref2VA 4-step, and 1.1 for both 8-step files.

  1. Source:
    • Base: diffusion_models/minimax_h3_<variant>_pruned_bf16.safetensors from Comfy-Org/MiniMax-H3 (Ref2VA: revision 912b6e38).
    • LoRA: minimax_h3_<lora_variant>_turbo_<steps>_v<version>_768p_comfyui_bf16.safetensors from lightx2v/Minimax-h3-Turbo (revision 30f485ed). These are the authors' ComfyUI conversions, with no rank reduction: rank 128, with q/k/v fused into attn.qkv_proj adapters of rank 384.
    • Layout reference: diffusion_models/minimax_h3_<variant>_pruned_int8_convrot.safetensors from Comfy-Org/MiniMax-H3 (FL2VA: revision d6cfb4e5; Ref2VA: revision 912b6e38).
  2. Merge: the LoRA is merged at strength 1.0 into its 208 targets: attn.{qkv_proj,out_proj} and mlp.{fc1,fc2} in all 50 blocks and both token_refiner blocks. Each merge computes W' = W + (alpha/rank) · up @ down in FP32.
  3. Quantize: the 200 block linears are rotated with a group-256 Hadamard ConvRot, then quantized to INT8 with per-row scales, directly from the FP32 merge result. The 8 merged token_refiner weights go back to BF16, because that layer stays unquantized in the Comfy-Org file.
  4. Copy everything else: tensors the LoRA doesn't touch are copied bit for bit from the layout reference.

Checks

  • Against the Comfy-Org INT8 file, byte for byte (all four files): all 932 tensors match in name, order, dtype, shape and offset. Only 408 tensors have different bytes: the 200 INT8 weights, their 200 scales and the 8 token_refiner weights. The other 524 are identical, including all 200 .comfy_quant tensors.
  • LoRA presence: this projects the change from the base onto the LoRA delta, where 1 means fully present. 4 steps: the overall result is 0.9993 for FL2VA and 0.9995 for Ref2VA. Of the 208 layers, 200 are within 1 ± 0.1 in each file. The lowest is token_refiner.blocks.0.mlp.fc2 (0.0271 for FL2VA, 0.0429 for Ref2VA). 8 steps: the overall result is 0.9990 for FL2VA and 0.9997 for Ref2VA. Of the 208 layers, 199 are within 1 ± 0.1 for FL2VA and 197 for Ref2VA. The lowest is token_refiner.blocks.0.mlp.fc2 (0.0276 for FL2VA, 0.0277 for Ref2VA).

Credits & license

This derivative is released under the MiniMax H3 Community License Agreement, which includes territorial restrictions. See LICENSE and NOTICE.

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