What are the hardware requirements for Qwen2.5 Coder 7B Instruct OBLITERATED?

Qwen2.5 Coder 7B Instruct OBLITERATED requires approximately 15.5 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 Coder 7B Instruct OBLITERATED and how large is it?

Qwen2.5 Coder 7B Instruct OBLITERATED is developed by OBLITERATUS, a model with 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 Qwen2.5 Coder 7B Instruct OBLITERATED?

Qwen2.5 Coder 7B Instruct OBLITERATED is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 Coder 7B Instruct OBLITERATED by OBLITERATUS — VRAM 15.5GB, 32K context

Name: Qwen2.5 Coder 7B Instruct OBLITERATED
Author: OBLITERATUS

Qwen2.5 Coder 7B Instruct OBLITERATED is an open-source language model by OBLITERATUS. Features: 7b LLM, VRAM: 15.5GB, Context: 32K, Instruction-Based, Code Generating, LLM Explorer Score: 0.27.

Abliteration Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-... Codegen En Instruct Obliterate Obliteratus Qwen2 Region:us Safetensors Sharded Tensorflow Uncensored

Model Card on HF 🤗: https://huggingface.co/OBLITERATUS/Qwen2.5-Coder-7B-Instruct-OBLITERATED

Qwen2.5 Coder 7B Instruct OBLITERATED Parameters and Internals

LLM Name	Qwen2.5 Coder 7B Instruct OBLITERATED
Repository 🤗	https://huggingface.co/OBLITERATUS/Qwen2.5-Coder-7B-Instruct-OBLITERATED
Base Model(s)	Qwen/Qwen2.5-Coder-7B-Instruct Qwen/Qwen2.5-Coder-7B-Instruct
Model Size	7b
Required VRAM	15.5 GB
Updated	2026-09-25
Maintainer	OBLITERATUS
Model Type	qwen2
Instruction-Based	Yes
Model Files	1.9 GB: 1-of-9 1.9 GB: 2-of-9 1.9 GB: 3-of-9 1.9 GB: 4-of-9 1.9 GB: 5-of-9 1.9 GB: 6-of-9 1.9 GB: 7-of-9 1.1 GB: 8-of-9 1.1 GB: 9-of-9
Supported Languages	en
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	5.3.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Errors	replace

Rank the Qwen2.5 Coder 7B Instruct OBLITERATED 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 Qwen2.5 Coder 7B Instruct OBLITERATED

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Rebase	986K / 15.2 GB	73	2
Qwen2.5 7B Rebase	986K / 15.2 GB	33	2
StockQwen 2.5 7B	128K / 15.2 GB	69	6
DareQwen 2.5 7B	128K / 15.2 GB	11	1
Tessa T1 7B	117K / 15.2 GB	14	10
UIGEN T1.5 7B	117K / 15.2 GB	12	6
Qwen2.5 Coder 7B Instruct	32K / 15.2 GB	2019400	765
VeriLadder QwenCoder 7B	32K / 15.2 GB	947	1
DroidSenior 7B	32K / 15.2 GB	210	1
FinoCode 7B	32K / 15.2 GB	125	0

Note: green Score (e.g. "73.2") means that the model is better than OBLITERATUS/Qwen2.5-Coder-7B-Instruct-OBLITERATED.