Model overview
An **NVFP4 (4-bit) Qwen3-VL-32B text encoder** for MiniMax-H3, made with `convert-to-quant`. It is a drop-in replacement for the H3 conditioning text encoder (ComfyUI `CLIPLoader`, type `minimax`). The H3 video weights are unchanged — only the text encoder is quantized to 4-bit, to bring the full H3 stack onto consumer GPUs. This encoder deliberately keeps more of the network in bf16 than a minimum-size 4-bit encoder does. The `--qwen_vlm` filter protects — at bf16 — the token embeddings, the **first and last language layers**, and the **entire vision tower**, quantizing only the middle language-layer linears to NVFP4. The result is 16.64 GiB, about 2 GiB above the most aggressively quantized community NVFP4 encoders (≈14.6 GiB, e.g. the AWQ-quantized encoder in `Comfy-Org/MiniMax-H3`), in exchange for leaving the precision-sensitive layers (embeddings, boundary layers, vision) untouched. It is a fidelity-first tradeoff: spend ~2 GiB more VRAM to keep the layers that most affect conditioning at full precision. Everything still fits a 24 GB card with offload. Everything is held constant except encoder precision — the bf16 encoder vs this NVFP4 encoder, same prompts, same seeds, same DiT — over a 16-clip paired set.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
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Source prices & cost analysis
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| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
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Public benchmarks & run configuration
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Sources & traceability
许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。