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vllm-omni-wan2.2-t2v
Wan2.2-T2V-A14B via vLLM-Omni - Text-to-video generation model from Wan-AI. Generates high-quality videos from text prompts using a 14B parameter diffusion model.

Repository: localaiLicense: apache-2.0

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-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-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

wan-2.1-t2v-1.3b-ggml
Wan 2.1 T2V 1.3B — text-to-video diffusion model, GGUF-quantized for the stable-diffusion.cpp backend. Generates short (33-frame) 832x480 clips from a text prompt. Cheapest Wan variant, suitable for CPU-offloaded inference with ~10 GB of usable RAM.

Repository: localaiLicense: apache-2.0