servantofares/Leanstral-1.5-119B-A6B-GGUF overview
Leanstral 1.5 models, quantized. I don't want to waste your time reading a 500 word LLM generated essay on what the model is, when Mistral themselves already p…
Runs locally from ~826.5 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | servantofares/Leanstral-1.5-119B-A6B-GGUF |
|---|---|
| Author | servantofares |
| Pipeline | — |
| License | apache-2.0 |
| Base model | mistralai/Leanstral-1.5-119B-A6B |
| Last modified | 2026-07-14T03:17:43.000Z |
Model README
---
license: apache-2.0
base_model:
- mistralai/Leanstral-1.5-119B-A6B
base_model_relation: quantized
tags:
- gguf
- llama-cpp
- mistral
- moe
- lean4
- math
- mistral4
- deepseek2
language:
- en
---
Leanstral 1.5 models, quantized.
I don't want to waste your time reading a 500-word LLM-generated essay on what the model is, when Mistral themselves already provide a good explanation in the original model's README. Go read that instead.
Instead, I'll focus on the important part: why should you use my quantization?
- Properly labeled as
mistral4architecture instead ofdeepseek2. This is a bug in upstreamllama.cpp's GGUF conversion code. PR incoming. - Chat template from Leanstral-2603 embedded inside GGUF, no need to specify a template by yourself.
- I run these models myself on my Strix Halo box.
- You can interrogate me on the Lean Zulip if you find these quants to be malicious, or if you just have suggestions for improvements.
Enjoy!
Run servantofares/Leanstral-1.5-119B-A6B-GGUF with guIDE
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Source: Hugging Face · Compare models