Spaces:
Running on Zero
Add verified model-license review to MODEL_RESEARCH.md
Browse filesNew "Model licenses (reviewed 2026-09-08)" section covering every model
ExtractArena can route to (9 shipped) plus the 5 benched candidates:
per-model summary table, per-license notes, an implications matrix for
free Space / internal use / paid product / territory, and sources. Every
claim was checked against the repo LICENSE/NOTICE/README or the linked
license page, not the HF tag alone.
Key findings: 7 of 9 shipped models are plain Apache-2.0; HunyuanOCR's
Tencent license excludes EU/UK/KR, caps MAU, bans output reuse for
training, and requires an end-user provider disclosure; Gemma 4 is
verbatim Apache-2.0 (the Prohibited Use Policy binds only Gemma 3 via
the Gemma Terms); Llama 4's EU exclusion lives in its AUP.
Also: header date, a license step in the refresh checklist, corrected
HunyuanOCR license cell, and a CLAUDE.md pointer to the new section.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
- CLAUDE.md +2 -1
- MODEL_RESEARCH.md +158 -5
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**When adding, replacing, or re-evaluating models, start from `MODEL_RESEARCH.md`** β it holds
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the verified candidate tables (hosted + local), benchmark snapshots, provider-reliability
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notes, per-model transformers quirks,
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since that data goes stale. Update it after any new model research.
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## Commands
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**When adding, replacing, or re-evaluating models, start from `MODEL_RESEARCH.md`** β it holds
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the verified candidate tables (hosted + local), benchmark snapshots, provider-reliability
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notes, per-model transformers quirks, prompting findings, and verified model licenses (with
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per-scenario implications), plus the endpoints to re-check
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since that data goes stale. Update it after any new model research.
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## Commands
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# Model Research
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Consolidated research behind the model choices in `ocr_arena.py`, `extract_arena.py`, and
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`svlm_council.py`. **Research dated 2026-08-25/26** β provider
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go stale fast; re-verify before acting on any table below.
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## How to refresh this research
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[OCRBench v2](https://99franklin.github.io/ocrbench_v2/) (has an Extraction subscore),
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OmniDocBench v1.6 (doc parsing; see the [PaddleOCR-VL-1.6 report](https://arxiv.org/html/2606.03264v1)),
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[Nanonets IDP/KIE](https://benchmarking.nanonets.com/).
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- **Transformers compat**: check `config.json` (`architectures`, `model_type`, MoE fields),
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the model card's install/usage snippets, and the in-tree model doc at
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`https://huggingface.co/docs/transformers/main/en/model_doc/<model_type>`. On Apple Silicon:
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"Serious" providers = dedicated (together, deepinfra, novita, fireworks, cerebras, nebius,
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hyperbolic, ovhcloud, scaleway, nscale, sambanova, groq) or first-party (zai-org, cohere);
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featherless-ai excluded from counts.
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| Repo | Size | Family | Serious providers | Price ($/M inβout, cheapest) | Notes |
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## Local β€10B candidates (transformers on Apple Silicon; host = M2 Max 32GB)
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Selected (all in-tree, dense, no flash-attn requirement, open-ended QA β no prompt-lock
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| Repo | Params / bf16 | Extraction evidence | License | transformers |
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|---|---|---|---|---|
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| `baidu/Qianfan-OCR` | 4.7B / 9.5GB | KIE overall 87.9 (beats Qwen3-VL-235B 84.2, Gemini-3.1-Pro 79.2); OCRBench KIE 95.0; Nanonets KIE F1 86.5; OCRBench 880 ([paper](https://arxiv.org/pdf/2603.13398)) | Apache-2.0 | β₯5.6, zero remote code |
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| `tencent/HunyuanOCR` (1.5) | 1.1B / 2.2GB | IE cards 92.29 / receipts 92.53; OCRBench 860 (SOTA <3B); best scene-text spotting in class ([report](https://arxiv.org/pdf/2607.04884)) | Tencent
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| `ibm-granite/granite-vision-4.1-4b` | 4.0B / 8GB | VAREX KVP extraction 94.2% exact-match zero-shot ([VAREX](https://arxiv.org/abs/2603.15118)) | Apache-2.0 | β₯5.8; needs `peft>=0.19.1` (ships as LoRA) |
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| `Qwen/Qwen3-VL-8B-Instruct` | 8.8B / 17.5GB | OCRBench 0.896 (best sub-10B); OCRBench v2 en 0.654; explicitly blur/tilt/low-light robust | Apache-2.0 | β₯4.57 |
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| `openbmb/MiniCPM-V-4.6` *(bench, not shipped)* | 1.3B / 2.6GB | OCRBench 876, DocVQA 94.7 | Apache-2.0 | β₯5.7 in-tree |
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"-35B-A3B"), NuExtract3 (Qwen3.5-4B base), Ovis2.5 (Qwen3-8B backbone), Qwen3-VL-8B (in
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council), InternVL3.5 (Qwen backbone). Non-Qwen families in play: Moondream, Baidu (Qianfan),
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Tencent (Hunyuan), IBM (Granite), Google (Gemma), Meta (Muse), Z.ai (GLM), OpenBMB (MiniCPM).
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# Model Research
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Consolidated research behind the model choices in `ocr_arena.py`, `extract_arena.py`, and
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`svlm_council.py`. **Research dated 2026-08-25/26; licenses reviewed 2026-09-08** β provider
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availability, leaderboards and license terms go stale fast; re-verify before acting on any table below.
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## How to refresh this research
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[OCRBench v2](https://99franklin.github.io/ocrbench_v2/) (has an Extraction subscore),
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OmniDocBench v1.6 (doc parsing; see the [PaddleOCR-VL-1.6 report](https://arxiv.org/html/2606.03264v1)),
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[Nanonets IDP/KIE](https://benchmarking.nanonets.com/).
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- **License**: `https://huggingface.co/api/models/<repo>?expand[]=cardData` gives the tag +
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`license_link`; then read the repo `LICENSE`/`NOTICE`/`README` and whatever the link points at β
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the tag alone misleads (Gemma 4 tags `apache-2.0` and *is*, but Google's site links a use policy
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beside it; Muse ships a `USAGE_POLICY.md` the LICENSE never mentions). Findings live in
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[Model licenses](#model-licenses-reviewed-2026-09-08).
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- **Transformers compat**: check `config.json` (`architectures`, `model_type`, MoE fields),
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the model card's install/usage snippets, and the in-tree model doc at
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`https://huggingface.co/docs/transformers/main/en/model_doc/<model_type>`. On Apple Silicon:
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"Serious" providers = dedicated (together, deepinfra, novita, fireworks, cerebras, nebius,
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hyperbolic, ovhcloud, scaleway, nscale, sambanova, groq) or first-party (zai-org, cohere);
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featherless-ai excluded from counts. Licenses per row are verified in
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[Model licenses](#model-licenses-reviewed-2026-09-08) (the `Family` column only carries the headline).
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| Repo | Size | Family | Serious providers | Price ($/M inβout, cheapest) | Notes |
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|---|---|---|---|---|---|
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## Local β€10B candidates (transformers on Apple Silicon; host = M2 Max 32GB)
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Selected (all in-tree, dense, no flash-attn requirement, open-ended QA β no prompt-lock; license
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detail for every row is in [Model licenses](#model-licenses-reviewed-2026-09-08)):
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| Repo | Params / bf16 | Extraction evidence | License | transformers |
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|---|---|---|---|---|
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| `baidu/Qianfan-OCR` | 4.7B / 9.5GB | KIE overall 87.9 (beats Qwen3-VL-235B 84.2, Gemini-3.1-Pro 79.2); OCRBench KIE 95.0; Nanonets KIE F1 86.5; OCRBench 880 ([paper](https://arxiv.org/pdf/2603.13398)) | Apache-2.0 | β₯5.6, zero remote code |
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| `tencent/HunyuanOCR` (1.5) | 1.1B / 2.2GB | IE cards 92.29 / receipts 92.53; OCRBench 860 (SOTA <3B); best scene-text spotting in class ([report](https://arxiv.org/pdf/2607.04884)) | Tencent Hunyuan Community (non-OSI; **no EU/UK/KR**, 100M MAU, end-user disclosure β see [licenses](#model-licenses-reviewed-2026-09-08)) | β₯5.13 (backend="pil" needs β₯5.15) |
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| `ibm-granite/granite-vision-4.1-4b` | 4.0B / 8GB | VAREX KVP extraction 94.2% exact-match zero-shot ([VAREX](https://arxiv.org/abs/2603.15118)) | Apache-2.0 | β₯5.8; needs `peft>=0.19.1` (ships as LoRA) |
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| `Qwen/Qwen3-VL-8B-Instruct` | 8.8B / 17.5GB | OCRBench 0.896 (best sub-10B); OCRBench v2 en 0.654; explicitly blur/tilt/low-light robust | Apache-2.0 | β₯4.57 |
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| `openbmb/MiniCPM-V-4.6` *(bench, not shipped)* | 1.3B / 2.6GB | OCRBench 876, DocVQA 94.7 | Apache-2.0 | β₯5.7 in-tree |
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"-35B-A3B"), NuExtract3 (Qwen3.5-4B base), Ovis2.5 (Qwen3-8B backbone), Qwen3-VL-8B (in
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council), InternVL3.5 (Qwen backbone). Non-Qwen families in play: Moondream, Baidu (Qianfan),
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Tencent (Hunyuan), IBM (Granite), Google (Gemma), Meta (Muse), Z.ai (GLM), OpenBMB (MiniCPM).
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## Model licenses (reviewed 2026-09-08)
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Weights licenses only, as published on each HF model card and `LICENSE` file at HEAD on
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2026-09-08. Not covered: HF Inference Providers' own terms, the `GF-John/moondream-pointer`
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Space's terms, ZeroGPU terms. Not legal advice β licenses change; re-verify against the
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Sources before relying on any row. Method: `/api/models/<repo>?expand[]=cardData` for the tag +
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`license_link`, then the repo `LICENSE`/`NOTICE`/`README` and any external page the link names
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(the tag alone is not enough β see Gemma 4 and Muse below).
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Companion analysis: the Moondream rows condense `hfs-moondream-pointer/MOONDREAM_LICENSES.md`
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(sibling repo), which compares moondream2 / 3-preview / 3.1 in depth.
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### Summary
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| Model | Where | License | OSI | Paid API / MaaS | Territory / scale caps | Use policy | Notes |
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| `moondream/moondream3-preview` | hosted (own Space) | BSL 1.1 + Additional Use Grant | No (source-available) | **Prohibited** if it competes with M87's paid versions | None | None | Becomes Apache-2.0 two years after first public release (treat as 2027-09-18); no patent grant |
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| `Qwen/Qwen3.5-9B` | hosted (router) | Apache-2.0 (verbatim, Β© 2026 Alibaba Cloud) | Yes | OK | None | None | `LICENSE` in repo |
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| `meta-models/Muse-Glimmer-30B` | hosted (router) | Apache-2.0 (verbatim) | Yes | OK | None | `USAGE_POLICY.md` alongside (not referenced by the LICENSE) | Policy: no under-18 users, prohibited-use list, trade-compliance language |
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| `google/gemma-4-31B-it` | hosted (router) | Apache-2.0 (verbatim) | Yes | OK | None | Gemma Prohibited Use Policy is *linked*, not incorporated (see below) | No `LICENSE` file in repo; `license_link` β Google page hosting plain Apache-2.0 |
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| `google/gemma-4-26B-A4B-it` | hosted (router) | Apache-2.0 (verbatim) | Yes | OK | None | same as 31B | same as 31B |
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| `baidu/Qianfan-OCR` | local council | Apache-2.0 (verbatim) | Yes | OK | None | None | `NOTICE`: 4 files derived from InternVL (OpenGVLab, MIT) β keep the NOTICE if redistributing |
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| `tencent/HunyuanOCR` 1.5 | local council | Tencent Hunyuan Community License | No | OK inside Territory | **Excludes EU, UK, South Korea**; 100M MAU cap | Exhibit A AUP (20 items, incl. "use outside the Territory", military, high-stakes automated decisions) | Must disclose real provider + Tencent non-affiliation to end users; outputs may not train other models; HK law; no patent grant |
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| `ibm-granite/granite-vision-4.1-4b` | local council | Apache-2.0 | Yes | OK | None | None | No `LICENSE` file; card links apache.org; base `granite-4.1-3b` also Apache-2.0 |
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| `Qwen/Qwen3-VL-8B-Instruct` | local council | Apache-2.0 (tag only) | Yes | OK | None | None | No `LICENSE` file or License section in card |
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| `meta-llama/Llama-4-Scout-17B-16E` | benched | Llama 4 Community License (2025-04-05) | No | OK | **No rights for EU-domiciled licensees** (multimodal clause, in the AUP); 700M MAU cap | Llama 4 AUP | Gated (manual); "Built with Llama" display + "Llama" prefix on derivative names + notice text; California law |
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| `zai-org/GLM-4.6V-Flash` | benched | MIT (tag only) | Yes | OK | None | None | No `LICENSE` file or License section in card |
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| `Qwen/Qwen3-VL-30B-A3B-Instruct` | benched | Apache-2.0 (tag only) | Yes | OK | None | None | No `LICENSE` file |
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| `google/gemma-3-27b/12b/4b-it` | benched | Gemma Terms of Use (rev. 2026-04-01) | No | OK | None | Gemma Prohibited Use Policy, **incorporated** | Gated (manual, must accept terms); notice text on non-hosted distribution; Google may update terms and restrict use remotely; outputs are yours |
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| `openbmb/MiniCPM-V-4.6` | benched | Apache-2.0 (verbatim, Β© OpenBMB, on GitHub) | Yes | OK | None | None | Card: "weights and code are open-sourced under the Apache-2.0 license"; no registration step |
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### Per-license notes
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**Apache-2.0** β 7 of the 9 shipped models (`Qwen3.5-9B`, `Muse-Glimmer-30B`, both Gemma 4s,
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`Qianfan-OCR`, `granite-vision-4.1-4b`, `Qwen3-VL-8B`) plus `Qwen3-VL-30B-A3B` and
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`MiniCPM-V-4.6`. Internal, commercial, hosted-API and fine-tuning use are unrestricted; the only
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obligations bite when you *redistribute* weights or derivatives (license copy, change notices,
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carry any `NOTICE` β Qianfan-OCR's lists InternVL-derived files). Includes a patent grant. Three
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of these repos (`Qwen3-VL-8B`, `Qwen3-VL-30B-A3B`, `GLM-4.6V-Flash`'s MIT) declare the license
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only in the HF card metadata with no license file in the tree β legally the card is the
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publisher's statement, but pin the commit hash if you need to prove what was declared.
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**Gemma 4 vs. Gemma 3** β the HF tag `apache-2.0` on Gemma 4 is accurate: `license_link`
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resolves to a Google page containing the standard Apache-2.0 text with no preamble. Google's
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site still links a Gemma Prohibited Use Policy (last modified 2024-02-21) and an Intended Use
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Statement (2026-04-01) next to it, but the only instrument that *incorporates* the policy is
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the Gemma Terms of Use, and those Terms say "For Gemma 4 terms, see the Gemma 4 license" and
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list only Gemma 1β3/3n and siblings in their appendix. So for Gemma 4 the policy is guidance;
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for the benched Gemma 3 it is a binding condition, along with gating, a required notice on
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non-hosted distribution, and Google's reserved right to update terms and remotely restrict
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use. Net: Gemma 3 is the *more* restrictive family here, not Gemma 4.
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**Muse-Glimmer (Meta)** β `LICENSE` is verbatim Apache-2.0 and the card says "All artifacts
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are released under Apache 2.0". The repo also ships `USAGE_POLICY.md` ("applies to your access
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or use of Muse Glimmer": no under-18 users, the usual prohibited-use list, ITAR/bio-chem
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language). The Apache text does not reference it, so its contractual force is unclear; treat
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it as a compliance expectation rather than a license term. Not a Llama model β none of the
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Llama branding/MAU terms apply.
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**Business Source License 1.1 (moondream3-preview)** β Licensor M87 Labs; Additional Use
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Grant = production use allowed "provided the work is not offered to third parties on a hosted
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or embedded basis to compete with M87 Labs's paid versions"; internal use and free products are
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explicitly non-competitive. Change License Apache-2.0 at "two years after the first public
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release of this version" (no calendar date; conservative anchor = 2025-09-18 blog post β
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**2027-09-18**). No patent grant; any violation terminates all rights. Details, and why
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| 254 |
+
moondream3.1 is a different (non-sunsetting) license, in the sibling doc.
|
| 255 |
+
|
| 256 |
+
**Tencent Hunyuan Community License (HunyuanOCR 1.5)** β release-date anchor 2025-11-25.
|
| 257 |
+
- *Territory*: "THIS LICENSE AGREEMENT DOES NOT APPLY IN THE EUROPEAN UNION, UNITED KINGDOM
|
| 258 |
+
AND SOUTH KOREA"; AUP item 1 prohibits "use outside the Territory". The text does not say
|
| 259 |
+
whether this keys on the licensee's domicile or the end user's location β a worldwide-open
|
| 260 |
+
Space is at least arguably "available" in the EU.
|
| 261 |
+
- *Scale*: >100M MAU across all your products in the month before the release date β must
|
| 262 |
+
request a license.
|
| 263 |
+
- *Output reuse*: "You must not use the Tencent Hunyuan Works or any Output β¦ to improve any
|
| 264 |
+
other AI model" (distillation/synthetic-data clause; outputs themselves are fine to keep).
|
| 265 |
+
- *Deploying to third parties* (hosted included): must "clearly, accurately, and prominently
|
| 266 |
+
disclose to all end users the full legal name and entity of the actual provider" and that
|
| 267 |
+
"Tencent is not affiliated with, associated with, sponsoring, or endorsing" the service.
|
| 268 |
+
"Powered by Tencent Hunyuan" marking is encouraged, not required.
|
| 269 |
+
- *Non-hosted redistribution*: copy of the Agreement + change notices + a `Notice` file with
|
| 270 |
+
the prescribed copyright/trademark text.
|
| 271 |
+
- No patent grant; Hong Kong law and courts; termination requires deletion.
|
| 272 |
+
|
| 273 |
+
**Llama 4 Community License (Scout, benched)** β commercial use OK below 700M MAU; "Built with
|
| 274 |
+
Llama" must be displayed, derivative model names must start with "Llama", distributions carry a
|
| 275 |
+
notice. The EU exclusion is **not** in the license body β it is in the Acceptable Use Policy:
|
| 276 |
+
"With respect to any multimodal models included in Llama 4, the rights granted under Section
|
| 277 |
+
1(a) β¦ are not being granted to you if you are an individual domiciled in, or a company with a
|
| 278 |
+
principal place of business in, the European Union." Scout is multimodal. The fetched license
|
| 279 |
+
text contains no "improve any other LLM" clause (earlier Llama licenses had one). Gated.
|
| 280 |
+
|
| 281 |
+
**MIT (GLM-4.6V-Flash, benched)** β permissive; card metadata only, no license file.
|
| 282 |
+
|
| 283 |
+
### Implications by scenario
|
| 284 |
+
|
| 285 |
+
| Scenario | Apache-2.0 / MIT models | moondream3-preview (BSL) | HunyuanOCR (Tencent) | Gemma 3 (benched) | Llama 4 Scout (benched) |
|
| 286 |
+
|---|---|---|---|---|---|
|
| 287 |
+
| **This free public Space + MCP** | OK. No redistribution happens (weights pulled at runtime), so no notice duty | OK β free demo is expressly non-competitive | OK **with obligations**: add the provider-disclosure + Tencent non-affiliation line to the Space; territory ambiguity for EU/UK visitors | OK; hosted use needs no notice; PUP applies | OK if the operator isn't EU-domiciled; display "Built with Llama" |
|
| 288 |
+
| **Greenfly internal production** | Unrestricted | Explicitly allowed ("internal use within your organization") | Allowed inside the Territory and under 100M MAU; don't use its outputs to train/distill other models | Allowed; PUP binds; Google may change terms | Allowed unless Greenfly's principal place of business is in the EU |
|
| 289 |
+
| **Embedded in a paid Greenfly product** | OK; ship LICENSE (+ Qianfan NOTICE) only if weights are shipped | OK as an integrated feature; **not** OK as a general VLM API / per-customer endpoint / hosted fine-tuning until 2027-09-18 (or a deal with M87) | OK with end-user disclosure of provider + non-affiliation; Notice file if weights ship; HK governing law; customers in EU/UK/KR are outside the license | OK with notice on non-hosted distribution; PUP flows down to users | OK with "Built with Llama", naming rule, notice; EU-domicile exclusion |
|
| 290 |
+
| **Territory exposure** | None | None | **EU, UK, South Korea excluded** | None | EU (licensee domicile, multimodal models) |
|
| 291 |
+
|
| 292 |
+
Key takeaways:
|
| 293 |
+
|
| 294 |
+
- **Seven of the nine shipped models are plain Apache-2.0.** The two exceptions are
|
| 295 |
+
`moondream3-preview` (BSL 1.1) and `HunyuanOCR` (Tencent Community License).
|
| 296 |
+
- **HunyuanOCR is the only shipped model with strings attached to *deployment*:** territory
|
| 297 |
+
(no EU/UK/KR), an end-user disclosure duty, an output-reuse ban, and HK governing law. If
|
| 298 |
+
Greenfly serves EU/UK customers or wants to distill from arena outputs, swap it β Qianfan-OCR
|
| 299 |
+
is the Apache-2.0 model in the same OCR/KIE niche and already outscores it on KIE.
|
| 300 |
+
- **moondream3 only forbids selling Moondream-as-a-service.** The Space and an extraction
|
| 301 |
+
feature inside a Greenfly product are both fine; it sunsets to Apache-2.0 around 2027-09-18.
|
| 302 |
+
- **Gemma 4 is genuinely Apache-2.0; Gemma 3 is not.** Don't "downgrade" to a Gemma 3 size
|
| 303 |
+
on the assumption the terms are the same.
|
| 304 |
+
- **Among benched candidates, Llama 4 Scout carries the most conditions** (EU exclusion via
|
| 305 |
+
AUP, branding, gating); GLM-4.6V-Flash and MiniCPM-V-4.6 are permissive.
|
| 306 |
+
- **Follow-up for this Space (not done here):** add a one-line HunyuanOCR disclosure to the
|
| 307 |
+
Space README/UI ("served by <legal entity>; Tencent is not affiliated with or endorsing this
|
| 308 |
+
service").
|
| 309 |
+
|
| 310 |
+
### Sources (fetched 2026-09-08)
|
| 311 |
+
|
| 312 |
+
- HF card metadata (`license`, `license_link`, `gated`, file list):
|
| 313 |
+
`https://huggingface.co/api/models/<repo>?expand[]=cardData&expand[]=gated&expand[]=siblings`
|
| 314 |
+
for every repo in the summary table
|
| 315 |
+
- https://huggingface.co/moondream/moondream3-preview/raw/main/LICENSE.md and `/raw/main/README.md`;
|
| 316 |
+
https://moondream.ai/blog/moondream-3-preview (2025-09-18)
|
| 317 |
+
- https://huggingface.co/Qwen/Qwen3.5-9B/raw/main/LICENSE
|
| 318 |
+
- https://huggingface.co/meta-models/Muse-Glimmer-30B/raw/main/LICENSE, `/raw/main/README.md`,
|
| 319 |
+
`/raw/main/USAGE_POLICY.md`
|
| 320 |
+
- https://ai.google.dev/gemma/docs/gemma_4_license β https://ai.google.dev/gemma/apache_2 ;
|
| 321 |
+
https://ai.google.dev/gemma/terms (rev. 2026-04-01);
|
| 322 |
+
https://ai.google.dev/gemma/prohibited_use_policy (2024-02-21);
|
| 323 |
+
https://ai.google.dev/gemma/intended_use_statement ;
|
| 324 |
+
https://huggingface.co/google/gemma-4-31B-it/raw/main/README.md (no `LICENSE` file β 404)
|
| 325 |
+
- https://huggingface.co/baidu/Qianfan-OCR/raw/main/LICENSE and `/raw/main/NOTICE`
|
| 326 |
+
- https://huggingface.co/tencent/HunyuanOCR/raw/main/LICENSE and `/raw/main/README.md`
|
| 327 |
+
- https://huggingface.co/ibm-granite/granite-vision-4.1-4b/raw/main/README.md
|
| 328 |
+
- https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct/raw/main/README.md
|
| 329 |
+
- https://developer.meta.com/ai/llama4/license/ (redirect target of llama.com/llama4/license) and
|
| 330 |
+
https://developer.meta.com/ai/llama4/use-policy/
|
| 331 |
+
- https://huggingface.co/zai-org/GLM-4.6V-Flash/raw/main/README.md
|
| 332 |
+
- https://huggingface.co/openbmb/MiniCPM-V-4.6/raw/main/README.md and
|
| 333 |
+
https://raw.githubusercontent.com/OpenBMB/MiniCPM-V/main/LICENSE
|