{
  "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 final `vllm==0.33.0` for this source checkout. The published\n  Cosmos3 container and its historical results use an older runtime and do\n  not qualify the current source. The separate Reasoner environment below,\n  where present, retains its own plugin/runtime requirements.\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": "02286829737a54167e890185bcbb6948ed9afbcf",
    "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": []
  }
}