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thox-pro-8b

THOX configuration of Ministral-3-8B-Instruct-2512 β€” a THOX configuration and distribution of Ministral 3 8B for professional work on a single device: text and image input for documents, charts, and diagrams, within the base model's abiliti

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Run it: [Ollama β€” Thox-ai/thox-pro-8b](https://ollama.com/Thox-ai/thox-pro-8b) Β· Find your model: THOX Model Factory Β· Collection: Open & Pro β€” Laptop and Desktop Models

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Status: MODEL CARD PAGE β€” RUNNABLE BUILD ON OLLAMA. This Hugging Face repository is the model's public model card page and THOX packaging record; the runnable build is served from Ollama (see How to Use). THOX did not train these weights; THOX's work is the configuration, clustering layer, and documentation.

Summary

A THOX configuration and distribution of Ministral 3 8B for professional work on a single device: text and image input for documents, charts, and diagrams, within the base model's abilities, with all inference local. Multilingual, per the base model record (32+ languages). Configuration-derived: THOX did not train these weights.

Correction notice. This card previously presented HIPAA, SOC 2, and FERPA compliance as product properties; a locally run model can be one component of a compliant deployment, but THOX claims no certification for this model, and those checklists have been removed. It also described the build as "full precision"; the served build is Q4_K_M, per the manifest config. No benchmark, throughput, latency, concurrency, uptime, cost-saving, or compliance figure is claimed for this release. Earlier versions also stated a blanket MIT license for the model; that was incorrect for the weights (see License Terms).

Model ID: Thox-ai/thox-pro-8b Base model: Ministral-3 8B by Mistral AI Runnable build: Ollama - ollama run Thox-ai/thox-pro-8b License: Apache License 2.0 (weights; see License Terms)

Highlights

  • A THOX configuration and distribution of Ministral 3 8B for professional work on a single device: text and image input for documents, charts, and diagrams, within the base model's abilities, with all inference local.

Files

File Size Purpose
.gitattributes 1,519 B Repository file

MeshStack Origin

This model is part of the professional model family released alongside the MeshStack Cluster family. MeshStack, THOX's device-to-device clustering technology, was built for the flagship ThoxNova devices: hardware designed to magnetically connect and interact, using custom-developed magnetic pogo pins (MagStack) to distribute models and share resources device to device. The Pro family is the single-device professional line from the same program, and the foundation the Cluster family builds on.

That physical stack is the foundation of the MeshStack app and the patent-pending over-air mesh technology THOX ships today. MeshStack is included in the THOX Kickstarter campaign (thox.ai).

What THOX Did and Did Not Do

These are THOX-configured model distributions, and the THOX work lives in the MeshStack clustering layer, configuration, documentation, and the origin program, never in the weights. The weight layers in this model's Ollama distribution are byte-identical to the upstream provider's Ollama distribution (SHA-256 verified in the 2026-10-31 release review), and the weights remain governed by the upstream license terms recorded on this card. What THOX built is the layer around them: the MagStack and MeshStack clustering design these configurations were made for, the runtime configuration, and this documentation.

This distribution's weight layer is the same artifact as thox-cluster-swift's (identical SHA-256 digest). The two differ in configuration and presentation: Pro 8B is packaged for single-device use, Cluster Swift for multi-device team serving.

Specifications

Specification Details
Base model Ministral-3 8B (Mistral AI)
Parameters 8B
Size 6.0 GB (Ollama listing)
Context window 256,000 tokens
Quantization Q4_K_M (GGUF)
Modalities Text and image; up to 5 images per request
Languages 32+
Deployment Local inference via Ollama; distributed orchestration via MeshStack (separate from this download)

Intended Use

  • Professional document and image analysis on local hardware
  • Multilingual assistance for distributed teams
  • Privacy-sensitive workflows where data must stay on the device, subject to your own compliance obligations

How to Use

ollama pull Thox-ai/thox-pro-8b
ollama run Thox-ai/thox-pro-8b

This Hugging Face repository is the model's public model card page. The runnable build is served from Ollama at https://ollama.com/Thox-ai/thox-pro-8b - the original card this page is based on lives there in full.

Platforms

Platform / device Run path
Ollama (laptop / desktop) `ollama run Thox-ai/thox-pro-8b``
Hugging Face Download the builds listed under Files from this repo (see Run it)

Training Data and Procedure

This is a THOX distribution of the base model named above, packaged and documented by THOX.ai for local and MeshStack/MagStack deployment. The original THOX release materials for this model claim no separate THOX fine-tuning run, training dataset, or training procedure, and none is claimed here. Base-model training data and procedure are those of the base model's provider; see the base model card for that record.

Datasets added by THOX for this release: none.

Evaluation

Benchmark and performance figures quoted in this card were reported by Mistral for the base model and are reproduced from the model's original Ollama model card (catalog-reported at original publication). They were not re-run for this Hugging Face publication.

Independent THOX evaluation of this model on this page: pending. This section will be updated with method and results when a THOX-run evaluation lands; until then, treat quoted figures as the original catalog's claims, not as independently verified measurements.

Catalog notes for this model: The original card reports qualitative performance without published benchmark scores, and THOX claims no figure for this release.

Limitations

  • Vision is optimized for documents, charts, and professional imagery, not general photography

  • Maximum 5 images per request

  • The operator is responsible for meeting any regulatory obligations that apply to their deployment

  • Professional outputs (medical, legal, financial) require licensed professional verification

  • All processing is local by design; the model has no access to online information or external services unless the operator wires them in.

  • Outputs can be wrong. Professional, medical, legal, financial, and security-relevant outputs require qualified human review.

Hardware Reference (from the original card)

Minimum 16 GB RAM, 8 GB storage, NVIDIA Jetson Orin NX class GPU (8GB VRAM). Recommended 32 GB RAM, 16 GB SSD, Jetson Orin AGX class GPU.

License Terms

The base model weights in this distribution are governed by the Apache License 2.0, as recorded in the Ollama manifest license layer for this model. THOX claims no license over the weights beyond the upstream terms. Where a THOX copyright notice appears on a page for this family, it applies to THOX's own material (configuration and documentation) only, not to the weights. The Ollama manifest for this model also carries a THOX MIT layer, which covers THOX's own packaging material only.

Provenance

  • First listed on Ollama under Thox-ai in 2025 and held private.
  • Publicly released 2026-10-31 by order of Tommy Xaypanya, CTO and Co-Founder of THOX.ai, as part of the MeshStack model family release.
  • Runnable build: Ollama, ollama run Thox-ai/thox-pro-8b and https://ollama.com/Thox-ai/thox-pro-8b
  • This Hugging Face repository was created 2026-10-31 as the model's public model card page. It contains this card; the runnable model build is served from Ollama.
  • Announcement: the MeshStack model family public release announcement (thox.ai).

Citation

@software{thoxai_thox_pro_8b_2025,
  title = {Thox.ai Pro 8B - Privacy-First Professional AI with Vision},
  author = {Thox.ai LLC},
  year = {2025},
  url = {https://huggingface.co/Thox-ai/thox-pro-8b},
  note = {Runnable build: https://ollama.com/Thox-ai/thox-pro-8b}
}

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