LongCat Video and Avatar

LocalAI’s longcat-video backend serves Meituan’s official LongCat video-generation models through the /video API and the Studio Video page.

Gallery modelUpstream checkpointInputsOutput
longcat-videomeituan-longcat/LongCat-Videotext, optional start imagevideo
longcat-video-avatar-1.5meituan-longcat/LongCat-Video-Avatar-1.5text, audio, optional portraitvideo with the source audio

The base checkpoint supports text-to-video and image-to-video. Avatar 1.5 adds audio-driven character animation, optional portrait conditioning, and continuation segments for longer speech.

Warning

LongCat is a large, CUDA-only model family. LocalAI publishes this backend for Linux with NVIDIA CUDA 12 or CUDA 13 on x86_64 and CUDA 13 on ARM64. CPU, ROCm, and macOS images are not available. Avatar 1.5 also loads components from the base checkpoint, so reserve substantial disk and GPU or unified memory.

Install one or both recipes from Models in the web UI, or use the CLI:

local-ai models install longcat-video
local-ai models install longcat-video-avatar-1.5

You can also import either official Hugging Face URL. The importer recognizes the two repositories and writes a longcat-video model config with the appropriate use case and input/output modalities.

The required OCI backend is installed automatically when LocalAI first loads the model. The hardware detector selects the CUDA 12, CUDA 13, or CUDA 13 ARM64 variant.

DGX Spark and NVIDIA ARM64

Use a LocalAI CUDA 13 ARM64 image as described in GPU acceleration. The backend defaults to PyTorch SDPA, avoiding the FlashAttention dependency that is commonly unavailable on Blackwell ARM64 systems.

For unified-memory systems, start with BF16 (use_int8:false, the default). INT8 lowers steady-state DiT memory but can have a higher load-time peak because the full model is materialized before the quantized weights are applied.

Generate in Studio

  1. Open Studio, then choose Video.
  2. Select longcat-video or longcat-video-avatar-1.5.
  3. Enter a prompt and choose 832x480 or 1280x720.
  4. Expand Reference media to upload a start image. For Avatar 1.5, upload or record the speech under Avatar audio.
  5. Select Generate.

The base model can run without a reference image for text-to-video. Avatar 1.5 requires audio; the portrait is optional.

API examples

Text-to-video

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d '{
    "model": "longcat-video",
    "prompt": "A cinematic tracking shot through a misty redwood forest",
    "width": 832,
    "height": 480,
    "num_frames": 93,
    "fps": 15
  }'

Image-to-video

start_image accepts raw base64, a browser-style data URI, or a public HTTP(S) URL:

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d "{
    \"model\": \"longcat-video\",
    \"prompt\": \"The subject turns toward the camera as leaves move in the breeze\",
    \"start_image\": \"$(base64 --wrap=0 portrait.png)\",
    \"params\": {
      \"resolution\": \"480p\"
    }
  }"

Avatar from speech and a portrait

audio accepts raw base64, a data URI, or a public HTTP(S) URL. Each staged image or audio input is limited to 128 MiB.

curl http://localhost:8080/video \
  -H "Content-Type: application/json" \
  -d "{
    \"model\": \"longcat-video-avatar-1.5\",
    \"prompt\": \"A friendly presenter speaking naturally to camera\",
    \"start_image\": \"$(base64 --wrap=0 portrait.png)\",
    \"audio\": \"$(base64 --wrap=0 speech.wav)\",
    \"width\": 832,
    \"height\": 480,
    \"params\": {
      \"offload_kv_cache\": \"true\"
    }
  }"

Avatar output is generated at 25 FPS and is muxed with the submitted audio. When neither num_frames nor params.num_segments is provided, LocalAI derives the continuation count from the audio duration, up to the model’s max_segments setting.

Model configuration

The gallery and importer make each model self-describing. A manual Avatar 1.5 config looks like this:

name: longcat-video-avatar-1.5
backend: longcat-video
known_usecases:
  - video
known_input_modalities:
  - text
  - image
  - audio
known_output_modalities:
  - video
options:
  - attention_backend:sdpa
  - use_distill:true
  - max_segments:8
parameters:
  model: meituan-longcat/LongCat-Video-Avatar-1.5

The explicit modality declarations are used by GET /v1/models/capabilities and attachment-aware clients. They avoid inferring model behavior from backend or checkpoint names.

Load options

Model load options use key:value entries in options:

OptionDefaultDescription
attention_backendsdpasdpa, auto, flash2, flash3, or xformers; packaged images guarantee sdpa
use_distillAvatar: true; base: falseUse the checkpoint’s accelerated distillation path
use_int8falseUse Avatar 1.5’s INT8 DiT; unsupported by the base model
base_modelmeituan-longcat/LongCat-VideoBase tokenizer, text encoder, and VAE used by Avatar 1.5
max_segments8Maximum continuation segments accepted for one request
resolution480pDefault image-conditioned resolution: 480p or 720p

The initial backend supports one GPU per process. Tensor or context parallel sizes above one are rejected.

Per-request parameters

The /video request’s params object accepts string values:

ParameterDescription
num_segmentsExplicit number of Avatar continuation segments
audio_guidance_scaleAudio classifier-free guidance when distillation is disabled
offload_kv_cacheOffload continuation KV cache (true or false)
ref_img_indexReference-frame index used during continuation
mask_frame_rangeNumber of frames blended around continuation boundaries
resolutionPer-request image-conditioned resolution (480p or 720p)

With distillation enabled, Avatar uses eight inference steps and fixed text/audio guidance of 1.0. Disable use_distill in the model config before tuning step, cfg_scale, or audio_guidance_scale.

Troubleshooting

  • HTTP 400, audio is required: Avatar 1.5 was selected without audio.
  • HTTP 400, request needs too many segments: trim the audio or raise max_segments in the model options.
  • HTTP 412: the installed LocalAI runtime cannot select a compatible NVIDIA backend image.
  • Out of memory while loading: use BF16 on unified-memory hardware, close other GPU workloads, or reduce model concurrency. INT8 is not guaranteed to reduce peak load memory.
  • Slow first request: the backend and checkpoints are downloaded and loaded on demand; subsequent requests reuse the loaded pipeline.

See the general /video API reference for the complete request and response schema.