Model Gallery

34 models from 1 repositories

Filter by type:

Filter by tags:

vllm-omni-wan2.2-i2v
Wan2.2-I2V-A14B via vLLM-Omni - Image-to-video generation model from Wan-AI. Generates high-quality videos from images using a 14B parameter diffusion model.

Repository: localaiLicense: apache-2.0

longcat-video
LongCat-Video served by LocalAI's dedicated CUDA backend. Generates video from a text prompt or a start image. The SDPA attention path works without FlashAttention and is suitable for CUDA 13 ARM64 systems such as DGX Spark. This is a very large checkpoint (roughly 83 GB in Hugging Face storage) and requires Linux with an NVIDIA CUDA GPU plus substantial memory and disk.

Repository: localaiLicense: mit

longcat-video-avatar-1.5
LongCat-Video-Avatar-1.5 served by LocalAI's dedicated CUDA backend. Turns speech plus a prompt into an avatar video, optionally conditioning on a portrait, and continues across multiple segments for longer audio. Avatar generation also loads tokenizer, text encoder, and VAE components from LongCat-Video. Plan for very large downloads and substantial NVIDIA GPU or unified memory; CPU and macOS execution are unsupported.

Repository: localaiLicense: mit

minimax-h3-fl2va-unpruned-q4
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: unpruned. Format: Q4_K_M. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the original time-embedder DiT (~19.9 GB). Render status: verified render (end to end on the vllm.cpp model page). Q3_K_M of the same DiT is verified BAD and is not offered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-q4
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: unpruned. Format: Q4_K_M. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the original time-embedder DiT (~19.9 GB). Render status: verified render (end to end on the vllm.cpp model page). Q3_K_M of the same DiT is verified BAD and is not offered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-unpruned-q4
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: unpruned. Format: Q4_K_M. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the original time-embedder DiT (~19.9 GB). Render status: verified render (end to end on the vllm.cpp model page). Do NOT use the NVFP4 Ref2VA weights: they render a multicolour patch grid. Q3_K_M of the same DiT is verified BAD and is not offered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-q4
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: unpruned. Format: Q4_K_M. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the original time-embedder DiT (~19.9 GB). Render status: verified render (end to end on the vllm.cpp model page). Do NOT use the NVFP4 Ref2VA weights: they render a multicolour patch grid. Q3_K_M of the same DiT is verified BAD and is not offered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-pruned-q8
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: pruned. Format: Q8_0. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~21.4 GB). Render status: loads and renders (vllm.cpp model page, pruned Q8_0 A/B). The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-pruned-q6
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: pruned. Format: Q6_K. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~16.6 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q6_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-pruned-q5
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: pruned. Format: Q5_0. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~13.9 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q5_0 file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-pruned-q4
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: pruned. Format: Q4_K. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~11.4 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q4_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-pruned-q3
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: pruned. Format: Q3_K. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~8.8 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q3_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-pruned-q2
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: pruned. Format: Q2_K. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~6.7 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q2_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-pruned-q8
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: pruned. Format: Q8_0. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~21.4 GB). Render status: loads and renders (vllm.cpp model page, pruned Q8_0 A/B). The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-pruned-q6
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: pruned. Format: Q6_K. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~16.6 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q6_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-pruned-q5
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: pruned. Format: Q5_0. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~13.9 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q5_0 file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-pruned-q4
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: pruned. Format: Q4_K. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~11.4 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q4_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-pruned-q3
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: pruned. Format: Q3_K. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~8.7 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q3_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-ref2va-pruned-q2
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: ref2va. DiT layout: pruned. Format: Q2_K. This entry is the Ref2VA partition, which takes REFERENCE conditioning (reference images, clips and audio) so the subject or voice carries into the clip. It refuses plain text-to-video and first/last-frame requests: for those use the matching fl2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~6.7 GB). Render status: loads, not rendered. The vllm.cpp model page says the pruned Q2_K file loads through the same path as Q8_0; only Q8_0 has been rendered. The vllm.cpp page records its renders with the DiT expanded to bf16. This entry does not expand it and keeps the quantised weights resident, so a render in that mode is not covered by the page. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-pruned-nvfp4
MiniMax-H3 served by vllm.cpp, LocalAI's own C++ port of vLLM. It generates video AND audio jointly, so a clip comes back as an MP4 with a soundtrack. Ask for speech in the prompt and the model lip-syncs it. Runtime: vllm.cpp (backend vllm-cpp). Partition: fl2va. DiT layout: pruned. Format: NVFP4. This entry is the FL2VA partition, which serves text-to-video (t2va) and first/last-frame conditioning (fl2va). It refuses reference conditioning: for that use the matching ref2va entry. The DiT is the pruned DiT (AdaLN curve table in place of the per-block modulation projection; about 20B instead of 33B parameters) (~12.5 GB). Render status: loads, not rendered (vllm.cpp model page: NVFP4 exists and loads, pruned and unpruned). The quantised weights stay resident; nothing here expands them. The weights are one DiT, the Qwen3-VL-32B encoder (~14.6 GB), the video VAE (~10.4 GB), the audio VAE and the tokenizer, plus the two VAE configs that carry the latent statistics. The default canvas is 1344x768 at 124 frames and 24 fps, about 5.2 seconds. Generation is slow: roughly 176 s per denoise step at that canvas on a 20-SM device. Muxing the finished frames needs ffmpeg on the host.

Repository: localaiLicense: other

minimax-h3-fl2va-unpruned-q4-ggml
MiniMax-H3 served by stable-diffusion.cpp. It generates video AND stereo audio jointly from a text prompt, so a clip comes back as an MP4 with a soundtrack. Muxing the finished frames needs ffmpeg on the host. Runtime: stable-diffusion.cpp (backend stablediffusion-ggml). Partition: fl2va. DiT layout: unpruned. Format: Q4_K_M. This entry is the FL2VA partition: text-to-video, first-frame (I2VA) and first/last-frame (FL2VA) conditioning. It refuses reference conditioning (reference image or audio): that needs minimax-h3-ref2va-pruned-q4-ggml, which is a separate checkpoint. Render status: verified render (the stable-diffusion.cpp page shows a text-to-video and an image-to-video render with this file). Weights are the Q4_K_M quantisation of the DiT (~18.8 GB), the Qwen3-VL-32B MiniMax-H3 text encoder (~18 GB), the fp16 video VAE (~5 GB) and the fp32 audio VAE (~0.6 GB). MiniMax-H3 runs at 24 fps and the width and height are rounded up to a multiple of 32. The frame count is rounded up to the 17k + 5 grid.

Repository: localaiLicense: other

Page 1