schema = "m64/capsule@1"description = "MiniMax-H3-Image text-to-image on GB10 (diffusers). MiniMax's 33B open-weight image model (MiniMax-H3 family, guidance-distilled, 6 steps) with its Qwen3-VL-32B text encoder cut to the 51 layers it uses and quantized to 4-bit, at 2048x2048. MiniMax-H3-Image Community License: not licensed in the EU, UK, US or South Korea. Runs fully offline."kinds = ["image.generate"]authors = ["dh7"]license = "other"[hardware]platform = "linux-aarch64"gpu = "NVIDIA GB10"gpu_count = 1vram_gb = 88driver = ">=580"disk_gb = 140[runtime]sandbox = "container"# No image: the Dockerfile builds on nvcr.io/nvidia/pytorch:25.09-py3 + diffusers 0.41.0, pinned by digest.gpu = trueshm_gb = 8internal_port = 8000health = "/health"expected_load_seconds = 2400model_name = "minimax-h3-image"user = "65534:65534"[[artifacts]]type = "hf"repo = "MiniMaxAI/MiniMax-H3-Image"revision = "5f90473023975e6271b0ed1dd84c4e88e4bbc6d3"include = [  ".gitattributes",  "LICENSE",  "README.md",  "model_index.json",  "modular_model_index.json",  "processor/*",  "scheduler/*",  "text_encoder/*",  "tokenizer/*",  "transformer_diffusers/*",  "vae_diffusers/*",]mount = "/weights/minimax-h3-image"# The server's own defaults (minimax_h3_image_server.py), which every request gets: callers can only send# prompt and seed. Returned as params_used.[params]size = "2048x2048"num_inference_steps = 6[routes]extra = ["/v1/config"]