Extended Catalogs 6 Families 55 Models Free to Download

Specialty Model Catalogs

The default NotesXML catalog ships 10 Pareto-optimised models. These extended family catalogs let you explore the full breadth of each model lineage — from sub-1 GB ultra-lights to 400B datacenter giants.

How to load a specialty catalog

  1. Easiest (NotesXML 5.182.0 and later): open the AI Models window in NotesXML and tap Check for catalog updates. The app fetches the default catalog directly from this site, verifies its digital signature, and shows you what changed before applying anything.
  2. To load a specialty catalog instead: download a catalog JSON file from the cards below.
  3. In NotesXML, open Settings → AI → Model Catalog → Import Catalog.
  4. Select the downloaded file. NotesXML will load the new model list immediately.
  5. To return to defaults, tap Reset to Default Catalog in the same menu.

⚠️ Specialty catalogs include models that are significantly larger than the defaults. Check the RAM and storage requirements for each model before downloading it inside the app. Large models (20 GB+) are intended for desktop hardware with 32 GB+ RAM.

Choose a model family

Each catalog focuses on one model lineage. Models that already ship in the default catalog are included here too — the full family gives you context about where the defaults sit within their lineage.

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Gemma Family

Google · Apache 2.0 / Gemma ToU

↓ Download
11
Models
8
Vision-capable
0.8–19 GB
Model size

The complete Gemma lineage: Gemma 3 (1B–27B, vision from 4B up), Gemma 3n (E2B/E4B text-only), and Gemma 4 (E2B/E4B/12B/26B/31B, all vision-capable). Includes the Gemma 4 26B-A4B MoE and 31B dense models for high-RAM desktop systems. NotesXML is GPU-first on every platform: Intel integrated graphics run through Vulkan, or through SYCL where the Intel oneAPI runtime is available, exactly as dedicated NVIDIA, AMD and Intel Arc GPUs do. If you would rather run on the processor, Force CPU Only is a setting you choose in AI Settings → Advanced — it is never applied automatically. Requires NotesXML Beta 5.141.84 or later.

Gemma 3 Gemma 3n Gemma 4 3 Desktop-only Apache 2.0 & Gemma ToU
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Mistral Family

Mistral AI · Apache 2.0

↓ Download
14
Models
7
Vision-capable
2.1–80 GB
Model size

The broadest family catalog: Ministral 3/8/14B, Mistral 7B, Nemo 12B, Pixtral 12B (vision), Codestral 25.01, Mistral Small 3.1 & 3.2, Devstral Small, Mixtral 8x7B & 8x22B, Magistral Small 24B, and the new Mistral Small 4 119B MoE.

Ministral Mistral Small Mixtral MoE Pixtral 8 Desktop-only
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Llama Family

Meta · Llama Community License

↓ Download
10
Models
4
Vision-capable
0.8–243 GB
Model size

From Llama 3.2 1B through Llama 4 Maverick 402B MoE: Llama 3.1 (8B/70B/405B), Llama 3.2 (1B/3B/11B/90B vision), Llama 3.3 70B, Llama 4 Scout 109B-16E, and Llama 4 Maverick 402B-128E. Warning: the 400B+ entries require 250+ GB RAM.

Llama 3.1 Llama 3.2 Llama 3.3 Llama 4 6 Desktop-only
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Phi Family

Microsoft · MIT License

↓ Download
9
Models
1
Vision-capable
2.2–24 GB
Model size

Microsoft's Phi line: Phi-3.5 Mini & MoE 42B, Phi-4 14B, Phi-4 Mini, Phi-4 Multimodal 5.6B (vision), Phi-4 Reasoning, Phi-4 Reasoning Plus, Phi-4 Mini Reasoning, and Phi-4 Reasoning Vision 15B (text backbone only). All MIT licensed. Note: all Phi-4 models use hybrid Mamba1/SWA — flash-attn is disabled.

Phi-3.5 Phi-4 Reasoning 5 Desktop-only MIT
🪨

Granite Family

IBM · Apache 2.0

↓ Download
9
Models
0
Vision-capable
0.2–20 GB
Model size

IBM's enterprise-grade Granite stack: 3.0 (1B-A400M MoE, 2B, 8B), 3.2 8B with thinking, 4.0 350M (ultra-compact dense), 4.0 H-Small 32B MoE, and the full 4.1 generation (3B, 8B, 30B). All Apache 2.0. Text-only across the board — GGUF vision support not yet available.

Granite 3.0 Granite 3.2 Granite 4.0 Granite 4.1 Text-only Apache 2.0

GPT-OSS Family

OpenAI · Apache 2.0

↓ Download
2
Models
0
Vision-capable
14–63 GB
Model size

OpenAI's first open-weight releases (Aug 2025): GPT-OSS 20B (21B total / 3.6B active MoE) and GPT-OSS 120B (117B total / 5.1B active MoE). Both are reasoning models using the 'harmony' response format. Desktop-only. Minimum 16 GB RAM for 20B; 80+ GB RAM for 120B.

GPT-OSS 20B GPT-OSS 120B Reasoning MoE Desktop-only Apache 2.0

Why the default catalog has 16 models

The default NotesXML catalog is constructed using Pareto-frontier curation: given the trade-off between inference speed (tokens per second) and benchmark quality (AvgScore), only models that are undominated on that frontier ship by default. If model A is both faster and higher quality than model B, model B is removed — no user would choose it.

The specialty catalogs here include every model that was evaluated but fell off the Pareto frontier. They are perfectly functional — they just aren't the optimal choice when faster or higher-quality alternatives exist at similar sizes. You may prefer them for architecture familiarity, licensing requirements, or specific use-cases not captured in the benchmarks.

Benchmark data and the full methodology are published in the AI Benchmarks article.

Ready to experiment?

Download NotesXML, import a specialty catalog, and run any of these models entirely on your own hardware.