HunyuanOCR 1.5 vs Xiaomi-OCR-0

HunyuanOCR 1.5 60

Memory 30, the only build from Tencent is the BF16 safetensors file at the root, 2.24 GB, and 2.24 GB × 1.2 = 2.7 GB, within 16 GB. ggml-org's GGUF (Q8_0 0.58 GB with a 0.73 GB projector) dates from 21 May 2026 and wasn't matched to version 1.5. Runtimes 15, Released Transformers 5.22.2 has the hunyuan_vl model, vLLM 0.33.0 registers HunYuanVLForConditionalGeneration, and llama.cpp b12242 has the architecture, which the card says the community build runs after conversion. Builds 0, Tencent publishes the BF16 weights only and tells users to convert to GGUF themselves. Terms 5, A custom licence that allows free commercial use under a use policy and below 100 million monthly active users, but not for anyone: it doesn't apply in the European Union, the United Kingdom or South Korea. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no Tencent API that serves it. 30 + 15 + 0 + 5 + 10 + 0 = 60.

Xiaomi-OCR-0 80

Memory earns the full 30, since the only build is a 1.75 GB BF16 file that needs about 2.1 GB with the fifth added. Runtimes reach the 25 cap. The checkpoint keeps Qwen3.5's architecture, which released vLLM, SGLang, Transformers and llama.cpp run natively, and Ollama v0.40.14 pins llama.cpp b11963, which has the qwen35 architecture and the Qwen3-VL projector; LM Studio couldn't be checked. Builds score 0, as Xiaomi publishes no quantised build and every GGUF or MLX copy is someone else's. Terms get 15 for Apache 2.0 with nothing added on an Apache 2.0 base. Download gets 10 for an ungated repository, and hosted too 0, with no inference provider on 4 November and a static project Space. 30 + 25 + 0 + 15 + 10 + 0 = 80.

HunyuanOCR 1.5 45

File safety 25, safetensors only, no .bin, .pt or .pth files, and no Python at the root. Provenance 15, the files sit in the tencent organisation, which Tencent's GitHub repository for the model links to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or use section, and nothing on text in an image that tries to instruct the reader. Licence risk 0, 15 less 5 for limits beyond the law (an acceptable use policy and three territories where the licence doesn't apply), 5 for terms the licensor can change (Tencent may update the policy from time to time) and 5 for the 100 million monthly active user threshold. Security programme 5, Tencent's Security Response Center takes vulnerability reports company-wide, as the Hy3 listing records (5). 25 + 15 + 0 + 0 + 0 + 5 = 45.

Xiaomi-OCR-0 65

File safety gets 25, one safetensors file with no Python in the repository and native loading everywhere. Provenance gets 15 for files in the xiaomi-research organisation that Xiaomi's GitHub repository links, with hashes for every file, though neither organisation is verified. Licence risk keeps 15, since Apache 2.0 has none of the deductions. Agent guidance gets 5 for general cautions in Xiaomi's Skill, and the security programme 5 for Xiaomi's company security centre, carried from the 28 October reading. Safety evaluation scores 0, with no results published.

HunyuanOCR 1.5 48

Model card 8, Intended use, the architecture by reference to 1.0's unchanged backbone, and the context (128K) are on the card. Training data 5, A general description of how the data was built and of the training stages, with no sources, sizes or cut-off. Last change 15, the last commit, on 28 August 2026, changed config.json, 74 days before this check and within 90. Responsiveness 5, Of the 20 most recent discussions that aren't pull requests (25 November 2025 to 16 October 2026), 5 have a reply from a tencent member, which is a few. Version policy 5, Version 1.5 replaced 1.0 at the root of the same repository. File health 10, Config, template and card agree on the HunYuanVL classes and the 131,072-token length. 8 + 5 + 15 + 5 + 5 + 10 = 48.

Xiaomi-OCR-0 65

The card covers intended use and parameters and misses limitations, architecture, context length, languages and a cut-off (5). Training data is described by size and labelling with no datasets named and no cut-off (5). The last change to the repository is the card commit of 29 October 2026, 6 days before this check, after the 23 October eval file deletion; card and documentation commits count on this line (20). The one question on the Hub was answered the same day by a Xiaomi Research member, and no new question has been opened since (20). It's a first release (5), and the files agree with the card (10). 5 + 5 + 20 + 20 + 5 + 10 = 65.

HunyuanOCR 1.5 80

Chat template 20, chat_template.jinja in the repository (930 characters). Tool-calling format 25, Read for a document parser as what it takes and returns. Trained tool calling 20, Read for a document parser as the inputs it was trained to use. Structured output 5, Read for a document parser as typed outputs. Reasoning control 0, A document parser with no reasoning. Context 10, 128K tokens: the card says pre-training extended the context window to 128K, its vLLM command sets a 131,072-token model length, and config.json gives the language model 131,072 positions. 20 + 25 + 20 + 5 + 0 + 10 = 80.

Xiaomi-OCR-0 70

Read for a document parser, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. Xiaomi documents the image, the five task prompts and the Markdown, OTSL, LaTeX and JSON outputs, and ships the converters and an MCP server (25). It reads one image per request (10). JSON for key fields and Markdown with tables are documented with how to ask for them (15). The Jinja template is in the repository (20). Reasoning control scores 0, as thinking is only switched off, and context 0, at the 16,384 tokens Xiaomi documents.