What are the hardware requirements for Octocoder GGML?

Octocoder GGML requires approximately 10.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Octocoder GGML and how large is it?

Octocoder GGML is developed by TheBloke. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Octocoder GGML?

Octocoder GGML is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Octocoder GGML by TheBloke — VRAM 10.7GB

Name: Octocoder GGML
Author: TheBloke

Octocoder GGML is an open-source language model by TheBloke. Features: LLM, VRAM: 10.7GB, License: bigcode-openrail-m, Quantized, LLM Explorer Score: 0.08.

Arxiv:2308.07124 Base model:bigcode/octocoder Base model:finetune:bigcode/oc... Code Dataset:bigcode/commitpackft Dataset:bigcode/oasst-octopack Ggml Model-index Quantized Region:us Starcoder

Model Card on HF 🤗: https://huggingface.co/TheBloke/Octocoder-GGML

Octocoder GGML Parameters and Internals

Model Type

text-generation

Additional Notes

OctoCoder is an instruction tuned model created by fine-tuning StarCoder on CommitPackFT & OASST.

Supported Languages

80+ Programming languages ()

Training Details

Data Sources:

CommitPackFT, OASST

Data Volume:

1 trillion pretraining & 2M instruction tuning tokens

Methodology:

Instruction tuning

Training Time:

24 days pretraining, 4 hours instruction tuning

Hardware Used:

512 Tesla A100 GPUs for pretraining, 8 Tesla A100 GPUs for instruction tuning

Model Architecture:

GPT-2 model with multi-query attention and Fill-in-the-Middle objective

LLM Name	Octocoder GGML
Repository 🤗	https://huggingface.co/TheBloke/Octocoder-GGML
Model Creator	BigCode
Base Model(s)	Octocoder bigcode/octocoder
Required VRAM	10.7 GB
Updated	2026-07-21
Maintainer	TheBloke
Model Type	starcoder
Model Files	10.7 GB 11.9 GB 13.1 GB 14.3 GB 20.1 GB
GGML Quantization	Yes
Quantization Type	ggml
Model Architecture	AutoModel
License	bigcode-openrail-m

Rank the Octocoder GGML capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Octocoder GGML

Best Alternatives	Context / RAM	Downloads	Likes
Athena V1 GGML	0K / 5.5 GB	6	1
MythoMax Kimiko Mix GGML	0K / 5.7 GB	3	3
...ax22b Instruct Falseblock GGML	0K / 9.2 GB	7	6
PULI GPT 3SX GGML	0K / 3.9 GB	7	5
NewHope GGML	0K / 5.7 GB	6	38
Spring Dragon GGML	0K / 5.5 GB	3	3
QCammel 13 GGML	0K / 5.5 GB	11	8
QCammel 70 X GGML	0K / 28.6 GB	10	3
OpenChat V3.2 GGML	0K / 5.7 GB	5	14
Replit Openorca GGML	0K / 1.5 GB	6	6

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Octocoder-GGML.