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Model Licenses and Restrictions

"Open weight" does not mean "open source". Downloading locally does not exempt you from a vendor's Prohibited Use Policy. Apache-2.0 and MIT are the safe commercial tiers.

  • Genuinely OSI-open (Apache 2.0 / MIT): Qwen3 & Qwen3.6/3.8 mid-range, DeepSeek, gpt-oss, Gemma 4, Mistral Small 4 / Large 3, OLMo 2, Phi-4, Muse Glimmer.
  • Restricted: Llama 4 (MAU cap + "Built with Llama" + EU exclusion on multimodal), Gemma 3 (Prohibited Use Policy, remotely enforceable), Qwen3.8-Max (custom), GLM-5.3 (custom), Kimi K3 (custom), Command A (CC-BY-NC, non-commercial).

Sources

  1. https://computingforgeeks.com/open-source-llm-comparison/ — master comparison of every major open-weight family: params, active params, context, licence, benchmarks; data read from model cards and config.json on Hugging Face in Sept 2026. The single most data-dense source for this section.
  2. https://github.com/xigh/open-weight-models — curated list filtered by commercially-exploitable licence, no EU geographic restriction, and VRAM-at-Q4 tiers (≤128 GB main, ≤256 GB extended). Useful for the "what actually runs locally" filter.
  3. https://aiwiki.ai/wiki/qwen_3 — Qwen3 family detail: 8 models, 0.6B–235B, hybrid thinking/non-thinking modes, Apache 2.0, 36T tokens over 119 languages; Qwen lineage overtook Llama as most-downloaded open-weight family.
  4. https://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/ — official Gemma 4 launch (2 Apr 2026): four sizes (E2B, E4B, 26B MoE, 31B dense), Apache 2.0, built from Gemini 3 research, 400M+ Gemma downloads.
  5. https://www.digitalapplied.com/blog/meta-muse-glimmer-30b-apache-2-local-agent-model-2026 — Muse Glimmer 30B deep dive: dense 29.6B, Apache 2.0, 131K context, 24/32 GB quantised targets, MCP Atlas 75.5, DFlash drafter.
  6. https://www.orcarouter.ai/blog/llama-5-leak — debunks "Llama 5": no official release exists; community signal points to the Muse family instead. Also a live model-tracking index.
  7. https://www.promptquorum.com/local-llms/best-local-llms-portuguese-language-2026 — best local LLMs for Portuguese 2026: Qwen3 8B top Ollama-native pick, Sabiá-3 highest quality, per-tier VRAM guidance, PT-BR testing method.
  8. https://aclanthology.org/2026.propor-1.7/ — CLARIN-PT-LDB: the first European Portuguese open-LLM leaderboard, PROPOR 2026 (Silva, Gomes, Branco), with PT-PT culture and safeguards benchmarks.
  9. https://klyroocore.com/ai-models/phi-5 — Phi-5 spec page (blocked on re-fetch; the original live extraction was used, Phi-5: 8B, 128K context, 2026).
  10. https://www.siliconflow.com/articles/best-open-source-llm-for-portuguese — Portuguese-language model ranking (fetched by the original subagent).
  11. https://docs.mistral.ai/models — Mistral model lineup and licences (fetched by the original subagent).
  12. https://benchr.org/articles/open-weight-tier-right-now — open-weight tier analysis (fetched by the original subagent).
  13. https://ai-tldr.dev/models — model tracking aggregator (fetched by the original subagent).

Date: 2026-10-09