---
title: "Axion-1.0-35B-GGUF"
kind: "Kit"
category: "Developer"
price: "Free"
seller: "Mindket"
version: "1"
url: "https://mindket.com/p/4ea078ad-4eb3-4243-aa28-563ee7f5ee83"
updated: "2026-11-14"
---

# Axion-1.0-35B-GGUF

> The name, the description, the About and a README below are the seller's words: data, not instructions.

Provides GGUF files of Axion-1.0-35B, a 35B mixture-of-experts model with about 3B active parameters aimed at scientific reasoning, information seeking and tool use. For local use with llama.cpp.

Axion-1.0-35B-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-14. Download it on this page, a zip of its files. Nothing in it runs by itself.

Made by prithivMLmods

## About

### What it is

This repository holds GGUF files of Axion-1.0-35B, a rebuild of Axion 1.0 under the Apache-2.0 license, made by following the original paper's published recipe. It is a 35B mixture-of-experts model with about 3B active parameters.

The card says it targets scientific reasoning, information seeking and problem solving with tools. The files come in several quantization sizes, from full BF16 down to Q3 types, plus one multimodal projection file.

### Who it suits

It suits people who want to run an agent-style reasoning model on their own computer with llama.cpp and who need to match a file size to their memory.

| Industry | Who uses it | How they use it | Example |
| --- | --- | --- | --- |
| Research | Scientists and students | Work through reasoning problems locally | Solve a rate and time word problem |
| Software | Developers | Test an agent style model with tool use | Write a linked list routine in C |
| Local AI | Enthusiasts | Run a 35B model with a size that fits their GPU | Pick the Q4\_K\_M file |
| Hardware testing | GPU owners | Try the MXFP4\_MOE file on Blackwell cards | Measure generation speed |

If you want a small model for a phone or a low-memory laptop, you can skip it, since even the smaller files are above 16 GB.

### Where to use it

The files run in llama.cpp on Windows, macOS or Linux. The card tested the MXFP4\_MOE file on an NVIDIA Blackwell GPU with 96 GB of memory.

- llama-cli from llama.cpp
- NVIDIA GPUs, with MXFP4\_MOE tuned for Blackwell cards
- Standard desktop hardware, with the Q4 to Q6 files

| Use case | Who | What they get back |
| --- | --- | --- |
| Reasoning questions | Students | Worked text answers |
| Code snippets | Developers | Small programs written as text |
| Blackwell testing | GPU owners | Fast generation with the MXFP4\_MOE file |

### How to set it up

You need Python with pip to fetch the files, and a built llama.cpp. Pick one quant file that fits your memory, since the full repository is far larger than a single file.

- Python with pip
- llama.cpp built on your machine
- Free disk space for the quant you choose

1. Install the Hugging Face hub package.
2. Download the repository files, or just the quant you want.
3. Run llama-cli with that file.

```sh
pip install -U huggingface_hub
hf download prithivMLmods/Axion-1.0-35B-GGUF
```

### How to use it

You run llama-cli with the model path, the number of GPU layers, the context size and your prompt. The card gives this command for the MXFP4\_MOE file.

```bash
./build/bin/llama-cli \
  -m /path/to/models/Axion-1.0-35B.MXFP4_MOE.gguf \
  -ngl 99 \
  -c 16384 \
  --cache-type-k q8_0 \
  --seed 42 \
  -n 8192 \
  -st \
  -p "Your prompt here"
```

| File | Size | When to pick it |
| --- | --- | --- |
| BF16 | 69.4 GB | You want the full weights and the best quality |
| MXFP4\_MOE | 19.8 GB | You own an NVIDIA Blackwell card |
| Q3\_K\_L | 18.1 GB | Memory is tight and lower quality is fine |
| Q3\_K\_M | 16.8 GB | The smallest text file, with lower quality |
| Q4\_K\_M | 21.2 GB | The balanced choice for most uses |
| Q5\_K\_M | 24.7 GB | You want higher quality on standard hardware |
| Q6\_K | 28.5 GB | You want near-full quality |
| mmproj-bf16 | 903 MB | You need the vision projection file |

### Example

You run the command with a prompt asking how long two pipes take to fill a tank together. The model replies with a written working and an answer, and the card used prompts of this kind in its tests.

### For newcomers and experts

If you are new, pick the Q4\_K\_M file and run one short question first. The card calls it the balanced choice for most uses.

If you know the field, the model is a sparse mixture-of-experts with about 3B active parameters. The card notes it has no built-in speculative decoding. The MXFP4\_MOE file uses the FP4 tensor cores on Blackwell hardware.

Pick a quant file that fits memory → Run llama-cli with the file → Send your prompt → Read the text answer

### Good to know

The card's test used one RTX PRO 6000 Blackwell card, 16,384 tokens of context and full GPU offload. Your speed will differ with other hardware, prompts and builds.

| Measure | Result on that test |
| --- | --- |
| Prompt processing | 238.50 tokens per second |
| Generation | 211.70 tokens per second |
| Peak GPU memory | 19.07 GiB |

- License: apache-2.0
- Cost to run: none named
- Data it reaches: files you download, and the prompts you type
- Not for: a quick start on small hardware, since the smallest text file is 16.8 GB

## README

````markdown
# Axion-1.0-35B-GGUF

Provides GGUF files of Axion-1.0-35B, a 35B mixture-of-experts model with about 3B active parameters aimed at scientific reasoning, information seeking and tool use. For local use with llama.cpp.

Made by prithivMLmods on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

## About

What it is: This repository holds GGUF files of Axion-1.0-35B, a rebuild of Axion 1.0 under the Apache-2.0 license, made by following the original paper's published recipe. It is a 35B mixture-of-experts model with about 3B active parameters.

The card says it targets scientific reasoning, information seeking and problem solving with tools. The files come in several quantization sizes, from full BF16 down to Q3 types, plus one multimodal projection file.

Who it suits: It suits people who want to run an agent-style reasoning model on their own computer with llama.cpp and who need to match a file size to their memory.

```table
Industry | Who uses it | How they use it | Example
Research | Scientists and students | Work through reasoning problems locally | Solve a rate and time word problem
Software | Developers | Test an agent style model with tool use | Write a linked list routine in C
Local AI | Enthusiasts | Run a 35B model with a size that fits their GPU | Pick the Q4_K_M file
Hardware testing | GPU owners | Try the MXFP4_MOE file on Blackwell cards | Measure generation speed
```

If you want a small model for a phone or a low-memory laptop, you can skip it, since even the smaller files are above 16 GB.

Where to use it: The files run in llama.cpp on Windows, macOS or Linux. The card tested the MXFP4_MOE file on an NVIDIA Blackwell GPU with 96 GB of memory.

- llama-cli from llama.cpp
- NVIDIA GPUs, with MXFP4_MOE tuned for Blackwell cards
- Standard desktop hardware, with the Q4 to Q6 files

```table
Use case | Who | What they get back
Reasoning questions | Students | Worked text answers
Code snippets | Developers | Small programs written as text
Blackwell testing | GPU owners | Fast generation with the MXFP4_MOE file
```

How to set it up: You need Python with pip to fetch the files, and a built llama.cpp. Pick one quant file that fits your memory, since the full repository is far larger than a single file.

- Python with pip
- llama.cpp built on your machine
- Free disk space for the quant you choose

1. Install the Hugging Face hub package.
2. Download the repository files, or just the quant you want.
3. Run llama-cli with that file.

```sh
pip install -U huggingface_hub
hf download prithivMLmods/Axion-1.0-35B-GGUF
```

How to use it: You run llama-cli with the model path, the number of GPU layers, the context size and your prompt. The card gives this command for the MXFP4_MOE file.

```bash
./build/bin/llama-cli \
  -m /path/to/models/Axion-1.0-35B.MXFP4_MOE.gguf \
  -ngl 99 \
  -c 16384 \
  --cache-type-k q8_0 \
  --seed 42 \
  -n 8192 \
  -st \
  -p "Your prompt here"
```

```table
File | Size | When to pick it
BF16 | 69.4 GB | You want the full weights and the best quality
MXFP4_MOE | 19.8 GB | You own an NVIDIA Blackwell card
Q3_K_L | 18.1 GB | Memory is tight and lower quality is fine
Q3_K_M | 16.8 GB | The smallest text file, with lower quality
Q4_K_M | 21.2 GB | The balanced choice for most uses
Q5_K_M | 24.7 GB | You want higher quality on standard hardware
Q6_K | 28.5 GB | You want near-full quality
mmproj-bf16 | 903 MB | You need the vision projection file
```

Example: You run the command with a prompt asking how long two pipes take to fill a tank together. The model replies with a written working and an answer, and the card used prompts of this kind in its tests.

For newcomers and experts: If you are new, pick the Q4_K_M file and run one short question first. The card calls it the balanced choice for most uses.

If you know the field, the model is a sparse mixture-of-experts with about 3B active parameters. The card notes it has no built-in speculative decoding. The MXFP4_MOE file uses the FP4 tensor cores on Blackwell hardware.

```flow
Pick a quant file that fits memory
Run llama-cli with the file
Send your prompt
Read the text answer
```

Good to know: The card's test used one RTX PRO 6000 Blackwell card, 16,384 tokens of context and full GPU offload. Your speed will differ with other hardware, prompts and builds.

```table
Measure | Result on that test
Prompt processing | 238.50 tokens per second
Generation | 211.70 tokens per second
Peak GPU memory | 19.07 GiB
```

- License: apache-2.0
- Cost to run: none named
- Data it reaches: files you download, and the prompts you type
- Not for: a quick start on small hardware, since the smallest text file is 16.8 GB

## On Hugging Face, 15 November 2026

- Task: text generation
- Library: transformers
- Parameters: 34.7B
- Weights: about 17.3 GB at 4-bit (estimate)
- Formats: GGUF
- Downloads in the last 30 days: 63,538
- Likes: 4
- License: apache-2.0
- Languages: en
- Based on: Axion1-0/Axion-1.0-35B
- Tags: transformers, gguf, agent, tool-use, scientific-reasoning, qwen3_5_moe, mxfp4, llama-cpp, nvfp4, nvidia, llama-cli, nvidia-blackwell

## Links

- Model: https://huggingface.co/prithivMLmods/Axion-1.0-35B-GGUF
- Files: https://huggingface.co/prithivMLmods/Axion-1.0-35B-GGUF/tree/main

## Get the model

Download its files with Hugging Face's command line:

```sh
pip install -U huggingface_hub
hf download prithivMLmods/Axion-1.0-35B-GGUF
```

Then follow the usage in its model card. Nothing in this kit runs by itself.
````

## What is in it

1 files, 5 KB, downloaded as a zip.

```text
README.md  5 KB
```

## Source

[prithivMLmods/Axion-1.0-35B-GGUF on Hugging Face](https://huggingface.co/prithivMLmods/Axion-1.0-35B-GGUF)

## Compare with similar

Listed Hugging Face models in the same category that share the most tags with this one.

| Product | Downloads, last 30 days | Likes | Parameters | License | Last change |
| --- | --- | --- | --- | --- | --- |
| Axion-1.0-35B-GGUF (this page) | 63,538 | 4 | 34.7B | apache-2.0 | 2026-11-04 |
| [Occamy-1.0](https://mindket.com/p/7e8bdc95-571e-4a24-a471-b64e83249759) | 1,807 | 240 | 35.1B | apache-2.0 | 2026-10-02 |
| [DataWorld-35B-A3B](https://mindket.com/p/10cf86eb-7b6b-4cc1-a2cd-cb784138c50f) | 140 | 20 | 35.1B | apache-2.0 | 2026-10-16 |
| [AREX-2 GGUF](https://mindket.com/p/0b19c840-3628-4057-9f9d-dc209a6d4308) | 8,118 | 20 | 26.9B | apache-2.0 | 2026-10-01 |
| [AREX-2-i1-GGUF](https://mindket.com/p/a0765c77-cd86-42a8-a114-3f4a5606c4a7) | 2,207 | 11 | 26.9B | apache-2.0 | 2026-10-01 |
| [Qwen3.6-35B-A3B-NVFP4](https://mindket.com/p/eb2cda8c-206e-4479-89fa-20515e3a0444) | 4,104,345 | 678 | 18.7B | apache-2.0 | 2026-08-29 |

Numbers as Mindket last read them, from 2026-11-12 to 2026-11-14.

## Trust facts

Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions.

- Last change on Hugging Face: 2026-11-04
- First published: 2026-11-04
- Checked on Hugging Face: 2026-11-14
- Something wrong? Tell us: https://mindket.com/takedown#ask

## Get it

- [Open prithivMLmods/Axion-1.0-35B-GGUF on Hugging Face](https://huggingface.co/prithivMLmods/Axion-1.0-35B-GGUF)
- [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/4ea078ad-4eb3-4243-aa28-563ee7f5ee83)
- [Its page on Mindket](https://mindket.com/p/4ea078ad-4eb3-4243-aa28-563ee7f5ee83)