What are the hardware requirements for Qwopus3.5 27B V3 FP8 Vllm Ready?

Qwopus3.5 27B V3 FP8 Vllm Ready requires approximately 29.4 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwopus3.5 27B V3 FP8 Vllm Ready and how large is it?

Qwopus3.5 27B V3 FP8 Vllm Ready is developed by Jackrong, a model with 27b 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 Qwopus3.5 27B V3 FP8 Vllm Ready?

Qwopus3.5 27B V3 FP8 Vllm Ready is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwopus3.5 27B V3 FP8 Vllm Ready by Jackrong — VRAM 29.4GB, 256K context

Name: Qwopus3.5 27B V3 FP8 Vllm Ready
Author: Jackrong

Qwopus3.5 27B V3 FP8 Vllm Ready is an open-source language model by Jackrong. Features: 27b LLM, VRAM: 29.4GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.23.

Base model:quantized:unsloth/q... Base model:unsloth/qwen3.5-27b Chain-of-thought Competitive-programming Compressed-tensors Conversational En Fixed-metadata Fp8 Ko Lora Qwen Qwen3.5 Qwen3 5 text Reasoning Region:us Safetensors Sglang Unsloth Vllm Zh

Model Card on HF 🤗: https://huggingface.co/Jackrong/Qwopus3.5-27B-v3-FP8-vllm-ready

Qwopus3.5 27B V3 FP8 Vllm Ready Parameters and Internals

LLM Name	Qwopus3.5 27B V3 FP8 Vllm Ready
Repository 🤗	https://huggingface.co/Jackrong/Qwopus3.5-27B-v3-FP8-vllm-ready
Base Model(s)	Jackrong/Qwopus3.5-27B-v3-FP8 unsloth/Qwen3.5-27B Jackrong/Qwopus3.5-27B-v3-FP8 unsloth/Qwen3.5-27B
Model Size	27b
Required VRAM	29.4 GB
Updated	2026-07-19
Maintainer	Jackrong
Model Type	qwen3_5_text
Model Files	29.4 GB
Supported Languages	en zh ko
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.5.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|vision_pad\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwopus3.5 27B V3 FP8 Vllm Ready 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 Qwopus3.5 27B V3 FP8 Vllm Ready

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.6 27B OBLITERATED	256K / 53.6 GB	15137	184
Qwen3.8 27B Obliterated E03	256K / 53.6 GB	708	1
Sharona Q27B R CodeSecurity V2	256K / 53.8 GB	574	1
Barcenas Qwen3.8 27B Fable	256K / 54.1 GB	869	5
...maAQUA Gridbook 13GB 5080 Vllm	256K / 13 GB	731	4
...wen3.8 P44w75 16.8B Unrepaired	256K / 2.4 GB	929	1
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	6727	14
...n3.8 27B PrismaScout AQUA 20GB	256K / 20.2 GB	266	3
Qwen3.8 27B Abliteratex	256K / 53.9 GB	321	6
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	5919	14

Note: green Score (e.g. "73.2") means that the model is better than Jackrong/Qwopus3.5-27B-v3-FP8-vllm-ready.