What are the hardware requirements for Stable Code 3B GPTQ?

Stable Code 3B GPTQ requires approximately 1.8 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Stable Code 3B GPTQ and how large is it?

Stable Code 3B GPTQ is developed by TechxGenus, a model with 3b parameters. 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 Stable Code 3B GPTQ?

Stable Code 3B GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Stable Code 3B GPTQ by TechxGenus — VRAM 1.8GB, 16K context

Name: Stable Code 3B GPTQ
Author: TechxGenus

Stable Code 3B GPTQ is an open-source language model by TechxGenus. Features: 3b LLM, VRAM: 1.8GB, Context: 16K, License: other, Quantized, LLM Explorer Score: 0.12.

Arxiv:1910.02054 Arxiv:2104.09864 Arxiv:2204.06745 Arxiv:2305.06161 Arxiv:2307.09288 Arxiv:2309.12284 Arxiv:2310.10631 4-bit Code Dataset:bigcode/commitpackft Dataset:bigcode/starcoderdata Dataset:bigcode/the-stack-gith... Dataset:eleutherai/proof-pile-... Dataset:meta-math/metamathqa Dataset:tiiuae/falcon-refinedw... En Endpoints compatible Gptq Model-index Quantized Region:us Safetensors Stablelm

Model Card on HF 🤗: https://huggingface.co/TechxGenus/stable-code-3b-GPTQ

Stable Code 3B GPTQ Parameters and Internals

Model Type

text generation, code

Use Cases

Areas:

research, commercial applications

Limitations:

Potentially unreliable, unsafe, or undesirable behaviors without further fine-tuning.

Considerations:

Evaluate and fine-tune for safe performance in downstream applications.

Additional Notes

Demo example code snippets to get started with the model are provided.

Supported Languages

English (fluent), Code (multi-language)

Training Details

Data Sources:

tiiuae/falcon-refinedweb, bigcode/the-stack-github-issues, bigcode/commitpackft, bigcode/starcoderdata, meta-math/MetaMathQA

Data Volume:

1.3 trillion tokens

Methodology:

decoder-only transformer, similar to LLaMA with modifications

Context Length:

16384

Hardware Used:

256 NVIDIA A100 40GB GPUs (AWS P4d instances)

Model Architecture:

decoder-only transformer architecture with rotary position embeddings and SwiGLU with flash-attention.

Input Output

Accepted Modalities:

text, code

LLM Name	Stable Code 3B GPTQ
Repository 🤗	https://huggingface.co/TechxGenus/stable-code-3b-GPTQ
Model Size	3b
Required VRAM	1.8 GB
Updated	2026-06-28
Maintainer	TechxGenus
Model Type	stablelm
Model Files	1.8 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	StableLmForCausalLM
License	other
Context Length	16384
Model Max Length	16384
Transformers Version	4.39.3
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50304
Torch Data Type	float16

Rank the Stable Code 3B GPTQ 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 Stable Code 3B GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Stable Code Instruct 3B 4bit	16K / 1.8 GB	52	5
Stable Code 3B 4bit	16K / 1.8 GB	17	1
Stable Code 3B	16K / 5.6 GB	5507	666
Stable Cypher Instruct 3B	16K / 1.7 GB	864	34
Stable Code Instruct 3B	16K / 5.6 GB	2134	189
Stable Cypher Instruct 3B	16K / 1.7 GB	263	26
...t 3B Mix Spider Bird 200 Steps	16K / 5.6 GB	9	0
...struct 3B Spider 1500 Steps Q4	16K / 1.7 GB	36	0
... Instruct 3B Spider 3500 Steps	16K / 11.2 GB	5	0
Stable Code Instruct 3B AWQ	16K / 1.8 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than TechxGenus/stable-code-3b-GPTQ.