{ "hf_id": "zai-org/GLM-OCR", "meta": { "title": "GLM-OCR", "slug": "glm-ocr", "provider": "GLM (Z-AI)", "description": "GLM-OCR image-to-text model with built-in MTP speculative decoding for high-throughput OCR serving", "date_added": "2026-01-26", "date_updated": "2026-04-17", "tasks": [ "multimodal" ], "performance_headline": "Multilingual end-to-end OCR VLM with MTP-accelerated decoding", "related_recipes": [] }, "recommended_command": { "hardware": "h200", "strategy": "single_node_tp", "variant": "default", "node_count": 1, "deploy_type": "single_node", "env": {}, "docker_image": "vllm/vllm-openai:latest", "command": "vllm serve zai-org/GLM-OCR \\\n --tensor-parallel-size 1 \\\n --speculative-config.method mtp \\\n --speculative-config.num_speculative_tokens 1", "argv": [ "vllm", "serve", "zai-org/GLM-OCR", "--tensor-parallel-size", "1", "--speculative-config.method", "mtp", "--speculative-config.num_speculative_tokens", "1" ], "docker_command": "docker run --gpus all \\\n --privileged --ipc=host -p 8000:8000 \\\n -v ~/.cache/huggingface:/root/.cache/huggingface \\\n vllm/vllm-openai:latest zai-org/GLM-OCR \\\n --tensor-parallel-size 1 \\\n --speculative-config.method mtp \\\n --speculative-config.num_speculative_tokens 1", "docker_argv": [ "docker", "run", "--gpus", "all", "--privileged", "--ipc=host", "-p", "8000:8000", "-v", "~/.cache/huggingface:/root/.cache/huggingface", "vllm/vllm-openai:latest", "zai-org/GLM-OCR", "--tensor-parallel-size", "1", "--speculative-config.method", "mtp", "--speculative-config.num_speculative_tokens", "1" ], "strategy_spec": { "name": "single_node_tp", "deploy_type": "single_node", "display_name": "Tensor Parallel", "short_label": "TP", "orientation": "latency", "description": "Single-node tensor parallel. Splits the model across all local GPUs. TP size is set to the GPU count at deploy time. The simplest multi-GPU strategy — works for all model architectures.\n", "hardware_match": { "min_gpus": 1, "max_gpus": 8, "multi_node": false }, "vllm_args": [], "parallel_flag": "--tensor-parallel-size" }, "hardware_profile": { "brand": "NVIDIA", "generation": "hopper", "compute_arch": "sm90", "display_name": "H200", "description": "NVIDIA H200 SXM 141 GB HBM3e · 8-GPU HGX node", "gpu_count": 8, "vram_gb": 1128, "multi_node": false }, "alternatives": { "multi_node_tp": "/zai-org/GLM-OCR/strategies/multi_node_tp.json", "kv_store_centralized_mooncake": "/zai-org/GLM-OCR/strategies/kv_store_centralized_mooncake.json", "kv_store_distributed_mooncake": "/zai-org/GLM-OCR/strategies/kv_store_distributed_mooncake.json" }, "by_hardware": { "h200": "/zai-org/GLM-OCR/hw/h200.json", "h100": "/zai-org/GLM-OCR/hw/h100.json", "b200": "/zai-org/GLM-OCR/hw/b200.json", "gb200": "/zai-org/GLM-OCR/hw/gb200.json", "b300": "/zai-org/GLM-OCR/hw/b300.json", "gb300": "/zai-org/GLM-OCR/hw/gb300.json", "mi300x": "/zai-org/GLM-OCR/hw/mi300x.json", "mi325x": "/zai-org/GLM-OCR/hw/mi325x.json", "mi350x": "/zai-org/GLM-OCR/hw/mi350x.json", "mi355x": "/zai-org/GLM-OCR/hw/mi355x.json" } }, "model": { "model_id": "zai-org/GLM-OCR", "min_vllm_version": "0.16.0", "architecture": "dense", "parameter_count": "0.9B", "active_parameters": "0.9B", "context_length": 131072, "base_args": [], "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-openai:latest" }, "extras": [ { "note": "GLM-OCR requires the nightly vllm wheel", "command": "uv pip install -U vllm --pre --extra-index-url https://wheels.vllm.ai/nightly" }, { "note": "transformers from source for GLM-OCR tokenizer support", "command": "uv pip install git+https://github.com/huggingface/transformers.git" } ] } }, "features": { "spec_decoding": { "description": "Multi-Token Prediction speculative decoding using the model's built-in MTP layers", "args": [ "--speculative-config.method", "mtp", "--speculative-config.num_speculative_tokens", "1" ] }, "text_only": { "description": "Skip loading the vision encoder for text-only workloads — frees VRAM for KV cache. Mutually exclusive with encoder_parallel.", "args": [ "--language-model-only" ] }, "encoder_parallel": { "description": "Run the vision encoder in data-parallel mode — avoids TP comm overhead on the small encoder. Mutually exclusive with text_only.", "args": [ "--mm-encoder-tp-mode", "data" ] } }, "opt_in_features": [ "text_only", "encoder_parallel" ], "variants": { "default": { "precision": "bf16", "vram_minimum_gb": 2, "description": "Full precision BF16 — single-GPU deployment" } }, "kv_offload_support": { "offloading_cpu": "verified", "offloading_fs": "verified" }, "hardware_overrides": {}, "guide": "## Overview\n\nGLM-OCR is a vision-language model for end-to-end OCR. It includes built-in\nMulti-Token Prediction (MTP) layers enabling speculative decoding for higher\nthroughput generation.\n\n## Prerequisites\n\n- **vLLM version:** nightly recommended (or latest stable with MTP support)\n- **Transformers:** >= 5.0.0 (install from source for latest)\n\n### Install vLLM\n\n```bash\nuv venv\nsource .venv/bin/activate\nuv pip install -U vllm --torch-backend auto\n```\n\nOr nightly:\n\n```bash\nuv pip install -U vllm --pre --extra-index-url https://wheels.vllm.ai/nightly\nuv pip install git+https://github.com/huggingface/transformers.git\n```\n\n## Launching the Server\n\n### With MTP Speculative Decoding\n\n```bash\nvllm serve zai-org/GLM-OCR \\\n --speculative-config.method mtp \\\n --speculative-config.num_speculative_tokens 1\n```\n\n## Client Usage\n\n### OpenAI SDK\n\n```python\nfrom openai import OpenAI\n\nclient = OpenAI(api_key=\"EMPTY\", base_url=\"http://localhost:8000/v1\", timeout=3600)\n\nmessages = [{\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image_url\", \"image_url\": {\"url\": \"https://ofasys-multimodal-wlcb-3-toshanghai.oss-accelerate.aliyuncs.com/wpf272043/keepme/image/receipt.png\"}},\n {\"type\": \"text\", \"text\": \"Text Recognition:\"}\n ]\n}]\n\nresponse = client.chat.completions.create(\n model=\"zai-org/GLM-OCR\",\n messages=messages,\n max_tokens=2048,\n temperature=0.0,\n)\nprint(response.choices[0].message.content)\n```\n\n### cURL\n\n```bash\ncurl -s http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"zai-org/GLM-OCR\",\n \"messages\": [{\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image_url\", \"image_url\": {\"url\": \"https://example.com/receipt.png\"}},\n {\"type\": \"text\", \"text\": \"Text Recognition:\"}\n ]\n }],\n \"max_tokens\": 2048,\n \"temperature\": 0.0\n }'\n```\n\n## Troubleshooting\n\n- **Greedy sampling recommended:** Use `temperature=0.0` for optimal OCR accuracy.\n- **Transformers version:** Requires `transformers >= 5.0.0`.\n\n## References\n\n- [Model card](https://huggingface.co/zai-org/GLM-OCR)\n", "source": { "source": "vllm", "repo": "vllm-project/vllm", "ref": "main", "sha": "389ffebe555705c85337025d5df108d0384d365e", "path": "recipes/models/zai-org/GLM-OCR.yaml", "edit_url": "https://github.com/vllm-project/vllm/edit/main/recipes/models/zai-org/GLM-OCR.yaml", "overlays": [] } }