{
  "hf_id": "nvidia/Cosmos3-Super-Image2Video",
  "meta": {
    "title": "Cosmos3-Super-Image2Video",
    "slug": "cosmos3-super-image2video",
    "provider": "NVIDIA",
    "description": "64B Cosmos3-Super specialization for temporally coherent image-to-video generation",
    "date_added": "2026-06-02",
    "date_updated": "2026-06-02",
    "tasks": [
      "omni"
    ],
    "performance_headline": "Temporally coherent image-to-video — ~55s/video on 8×H200",
    "related_recipes": [
      "nvidia/Cosmos3-Super",
      "nvidia/Cosmos3-Nano",
      "nvidia/Cosmos3-Super-Text2Image"
    ],
    "hardware": {
      "h200": "verified",
      "h100": "verified"
    }
  },
  "model": {
    "model_id": "nvidia/Cosmos3-Super-Image2Video",
    "min_vllm_version": "0.21.0",
    "docker_image": "vllm/vllm-omni:cosmos3",
    "architecture": "dense",
    "parameter_count": "64B",
    "active_parameters": "64B",
    "context_length": 262144,
    "base_args": [
      "--host",
      "0.0.0.0",
      "--port",
      "8000",
      "--cfg-parallel-size",
      "2",
      "--ulysses-degree",
      "4",
      "--use-hsdp",
      "--hsdp-shard-size",
      "8",
      "--init-timeout",
      "1800"
    ],
    "base_env": {},
    "install": {
      "pip": {
        "command": "uv venv\nsource .venv/bin/activate\nuv pip install -U vllm --torch-backend auto"
      },
      "docker": {
        "command": "docker pull vllm/vllm-omni:cosmos3",
        "note": "Release-tested vLLM-Omni image bundling the Cosmos3 omni handlers."
      }
    }
  },
  "omni": {
    "tasks": [
      {
        "id": "i2v",
        "description": "Image → temporally coherent video",
        "curl": "curl -X POST http://localhost:8000/v1/videos/sync \\\n  -H \"Accept: video/mp4\" \\\n  -F \"input_reference=@assets/example_first_frame.png\" \\\n  -F \"prompt=$(cat assets/example_prompt.json)\" \\\n  -F \"size=1280x720\" \\\n  -F \"num_frames=189\" \\\n  -F \"fps=24\" \\\n  -F \"num_inference_steps=35\" \\\n  -F \"guidance_scale=6.0\" \\\n  -F \"max_sequence_length=4096\" \\\n  -F \"flow_shift=10.0\" \\\n  -F \"seed=1111\" \\\n  --output output.mp4\n"
      }
    ]
  },
  "features": {},
  "opt_in_features": [],
  "variants": {
    "default": {
      "precision": "bf16",
      "vram_minimum_gb": 154,
      "description": "BF16 weights — 8×H200/H100/A100 node recommended"
    }
  },
  "hardware_overrides": {},
  "guide": "## Overview\n\n**Cosmos3-Super-Image2Video** is a 64B specialization of NVIDIA's Cosmos3-Super\nomnimodal world model, tuned for **temporally coherent image-to-video\ngeneration**: given one input image and text instructions, it produces video\nsequences consistent with the provided visual content. It is served via\n**vLLM-Omni**.\n\nFor best quality, text prompts should be JSON-upsampled (see the\n`scripts/upsample_prompt.py` helper in the model repo).\n\n## Prerequisites\n\n- 8× H200, H100, or A100 for the documented full-node profile\n- The release-tested `vllm/vllm-omni:cosmos3` container, or vLLM-Omni installed\n  on top of `vllm==0.21.0`\n\n## Launch command (vLLM-Omni)\n\nRecommended configuration on 8×H200, 8×H100, or 8×A100:\n\n```bash\ndocker pull vllm/vllm-omni:cosmos3\n\nvllm serve nvidia/Cosmos3-Super-Image2Video \\\n  --omni \\\n  --host 0.0.0.0 \\\n  --port 8000 \\\n  --cfg-parallel-size 2 \\\n  --ulysses-degree 4 \\\n  --use-hsdp \\\n  --hsdp-shard-size 8 \\\n  --init-timeout 1800\n```\n\nWith this configuration, 50-step video generation takes ~55 seconds on H200.\nFor **2×H200**, use `--cfg-parallel-size 2 --use-hsdp --hsdp-shard-size 2`\n(a video takes ~3 minutes). Tensor parallelism is also supported via\n`--tensor-parallel-size`. On memory-constrained GPUs,\n`--enable-layerwise-offload` reduces VRAM usage at a performance cost.\n\n### Example: image-to-video\n\n```bash\ncurl -X POST http://localhost:8000/v1/videos/sync \\\n  -H \"Accept: video/mp4\" \\\n  -F \"input_reference=@assets/example_first_frame.png\" \\\n  -F \"prompt=$(cat assets/example_prompt.json)\" \\\n  -F \"size=1280x720\" \\\n  -F \"num_frames=189\" \\\n  -F \"fps=24\" \\\n  -F \"num_inference_steps=35\" \\\n  -F \"guidance_scale=6.0\" \\\n  -F \"max_sequence_length=4096\" \\\n  -F \"flow_shift=10.0\" \\\n  -F \"seed=1111\" \\\n  --output output.mp4\n```\n\n## References\n\n- [Model card](https://huggingface.co/nvidia/Cosmos3-Super-Image2Video)\n- [vLLM-Omni](https://github.com/vllm-project/vllm-omni)\n- [Cosmos](https://github.com/nvidia/cosmos)\n",
  "source": {
    "source": "vllm-omni",
    "repo": "vllm-project/vllm-omni",
    "ref": "main",
    "sha": "cda4a1ef83b295ba332146a7709e6277725edc9f",
    "path": "recipes/models/nvidia/Cosmos3-Super-Image2Video.yaml",
    "edit_url": "https://github.com/vllm-project/vllm-omni/edit/main/recipes/models/nvidia/Cosmos3-Super-Image2Video.yaml",
    "overlays": []
  }
}