What are the hardware requirements for OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2?

OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 requires approximately 6.9 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 OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 and how large is it?

OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 is developed by LoneStriker, a model with 6.7b 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 OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2?

OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 by LoneStriker — VRAM 6.9GB, 16K context

Name: OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2
Author: LoneStriker

OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 is an open-source language model by LoneStriker. Features: 6.7b LLM, VRAM: 6.9GB, Context: 16K, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.11.

Arxiv:2402.14658 Code Codegen Conversational En Endpoints compatible Exl2 Instruct Llama Pytorch Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/LoneStriker/OpenCodeInterpreter-DS-6.7B-8.0bpw-h8-exl2

OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 Parameters and Internals

Model Type

text generation, code generation

LLM Name	OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2
Repository 🤗	https://huggingface.co/LoneStriker/OpenCodeInterpreter-DS-6.7B-8.0bpw-h8-exl2
Model Size	6.7b
Required VRAM	6.9 GB
Updated	2026-08-07
Maintainer	LoneStriker
Model Type	llama
Instruction-Based	Yes
Model Files	6.9 GB
Supported Languages	en
Quantization Type	exl2
Generates Code	Yes
Model Architecture	LlamaForCausalLM
Context Length	16384
Model Max Length	16384
Transformers Version	4.34.1
Tokenizer Class	LlamaTokenizer
Padding Token	<｜end▁of▁sentence｜>
Vocabulary Size	32256
Torch Data Type	bfloat16

Rank the OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2 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 OpenCodeInterpreter DS 6.7B 8.0bpw H8 EXL2

Best Alternatives	Context / RAM	Downloads	Likes
...rpreter DS 6.7B 6.0bpw H6 EXL2	16K / 5.2 GB	5	2
...rpreter DS 6.7B 4.0bpw H6 EXL2	16K / 3.6 GB	1	1
...epseek Coder 6.7B Instruct AWQ	16K / 3.9 GB	291702	19
Speechless Coder Ds 6.7B	16K / 13.5 GB	459	7
...s Coder6.7b Reflct Adamw Iter1	16K / 13.5 GB	475	0
...Coder6.7b Reflct Rmsprop Iter1	16K / 13.5 GB	95	0
...Coder6.7b Reflct Rmsprop Iter1	16K / 13.5 GB	110	0
...r6.7b Pos Reflct Rmsprop Iter1	16K / 13.5 GB	87	0
...ir4 Ds Coder6.7b Rmsprop Iter1	16K / 13.5 GB	43	0
Code 290K 6.7B Instruct	16K / 13.5 GB	87	6

Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/OpenCodeInterpreter-DS-6.7B-8.0bpw-h8-exl2.