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staccs/Llama-3.3-70B-Instruct-lecore-GGUF overview

Llama 3.3 70B Instruct lecore GGUF GGUF builds of meta llama/Llama 3.3 70B Instruct https://huggingface.co/meta llama/Llama 3.3 70B Instruct for llama.cpp, Oll…

ggufllama.cppollamalm-studioquantizedlecoretext-generationbase_model:meta-llama/Llama-3.3-70B-Instructbase_model:quantized:meta-llama/Llama-3.3-70B-Instructendpoints_compatibleregion:usconversational

Runs locally from ~25.33 GB disk (32 GB+ VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation
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Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Llama-3.3-70B-Instruct-Q4_K_M.ggufGGUFQ4_K_M39.60 GBDownload
Llama-3.3-70B-Instruct-lecore-mix.ggufGGUFGGUF25.33 GBDownload

Model Details

Model IDstaccs/Llama-3.3-70B-Instruct-lecore-GGUF
Authorstaccs
Pipelinetext-generation
License—
Base modelmeta-llama/Llama-3.3-70B-Instruct
Last modified2026-10-15T14:26:23.000Z

Model README

---

base_model: meta-llama/Llama-3.3-70B-Instruct

library_name: gguf

pipeline_tag: text-generation

tags: [gguf, llama.cpp, ollama, lm-studio, quantized, lecore]

---

Llama-3.3-70B-Instruct-lecore-GGUF

GGUF builds of meta-llama/Llama-3.3-70B-Instruct for llama.cpp, Ollama and LM Studio.

These are companions to the MLX export staccs/Llama-3.3-70B-Instruct-lecore-mlx, which has the measured perplexity numbers.

| File | Size | What it is |

|---|---|---|

| Llama-3.3-70B-Instruct-Q4_K_M.gguf | 42.52 GB | stock llama.cpp Q4_K_M |

| Llama-3.3-70B-Instruct-lecore-mix.gguf | 27.20 GB | leCore per-tensor mix: each linear layer gets the GGUF K-quant matching the bits leCore measured for it (2→Q2_K, 3→Q3_K, 4→Q4_K, 8→Q8_0); embeddings and output follow the MLX export |

The lecore-mix file is quantized from the original bf16 weights with llama.cpp K-quants. The bit width of each tensor follows leCore's measured (KL-damage) allocation, so its numbers are close to, but not identical to, the MLX export.

Some tensor widths are not multiples of 256, so llama.cpp may fall back to a compatible type for those tensors.

Usage

Ollama: download a file, then

printf 'FROM ./Llama-3.3-70B-Instruct-Q4_K_M.gguf
' > Modelfile && ollama create llama-3.3-70b-instruct-lecore-gguf -f Modelfile && ollama run llama-3.3-70b-instruct-lecore-gguf

or pull straight from the Hub with ollama run hf.co/staccs/Llama-3.3-70B-Instruct-lecore-GGUF:Q4_K_M

LM Studio: search for staccs/Llama-3.3-70B-Instruct-lecore-GGUF in the model browser and pick a file. On a 36 GB Mac, the lecore-mix file is the one that fits.

llama.cpp

llama-cli -hf staccs/Llama-3.3-70B-Instruct-lecore-GGUF -p "Hello" -n 256

Benchmarks (lm-eval-harness 0.4.9, run on the shipped weights dequantized to bf16 on GPU)

MMLU 5-shot on the first 10 questions of each of the 57 subjects; GSM8K 5-shot on the first 100 test problems (greedy, 320 new tokens, no chat template). These are subsets, so expect about ±2–4 points of sampling noise.

| Model | MMLU (5-shot) | GSM8K strict | GSM8K flexible |

|---|---|---|---|

| leCore mix (this repo) | 72.6% | 82.0% | 84.0% |

| stock 3-bit affine, group 64 (simulated) | 24.2% | 0.0% | 0.0% |

License

Base model: meta-llama/Llama-3.3-70B-Instruct (weights taken from the identical public mirror unsloth/Llama-3.3-70B-Instruct). It is released by Meta under the Llama 3.3 Community License Agreement (https://www.llama.com/llama3_3/license/) and its Acceptable Use Policy (https://www.llama.com/llama3_3/use-policy/). This derivative is distributed under the same license. Built with Llama. Llama 3.3 is licensed under the Llama 3.3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. Only quantization was done here: no retraining.

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