What are the hardware requirements for Qwen2.5 32B Instruct CFT?

Qwen2.5 32B Instruct CFT requires approximately 65.8 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 32B Instruct CFT and how large is it?

Qwen2.5 32B Instruct CFT is developed by TIGER-Lab, a model with 32b 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 32B Instruct CFT?

Qwen2.5 32B Instruct CFT is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 32B Instruct CFT by TIGER-Lab — VRAM 65.8GB, 32K context

Name: Qwen2.5 32B Instruct CFT
Author: TIGER-Lab

Qwen2.5 32B Instruct CFT is an open-source language model by TIGER-Lab. Features: 32b LLM, VRAM: 65.8GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.16.

Arxiv:2501.17703 Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-32b-in... Cft Conversational Dataset:tiger-lab/webinstruct-... En Endpoints compatible Instruct Math Qwen2 Reasoning Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TIGER-Lab/Qwen2.5-32B-Instruct-CFT

Qwen2.5 32B Instruct CFT Parameters and Internals

LLM Name	Qwen2.5 32B Instruct CFT
Repository 🤗	https://huggingface.co/TIGER-Lab/Qwen2.5-32B-Instruct-CFT
Base Model(s)	Qwen/Qwen2.5-32B-Instruct Qwen/Qwen2.5-32B-Instruct
Model Size	32b
Required VRAM	65.8 GB
Updated	2026-07-21
Maintainer	TIGER-Lab
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-14 4.9 GB: 2-of-14 4.9 GB: 3-of-14 4.9 GB: 4-of-14 4.9 GB: 5-of-14 4.9 GB: 6-of-14 4.9 GB: 7-of-14 4.9 GB: 8-of-14 4.9 GB: 9-of-14 4.9 GB: 10-of-14 4.9 GB: 11-of-14 4.9 GB: 12-of-14 4.9 GB: 13-of-14 2.1 GB: 14-of-14
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 32B Instruct CFT 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 32B Instruct CFT

Best Alternatives	Context / RAM	Downloads	Likes
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	9	2
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	28	17
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	22	4
Franqwenstein 35B	128K / 69.8 GB	5	8
ELYZA Thinking 1.0 Qwen 32B	128K / 65.8 GB	23	10
Archaeo 32B KTO	128K / 65.8 GB	19	4
Hamanasu Magnum QwQ 32B	128K / 65.8 GB	295	9
Qwen2.5 32B Gokgok Step3	128K / 65.7 GB	6	0
Openthaigpt R1 32B Instruct	128K / 65.8 GB	33	8
Qwen2.5 32B Dark Days Stage2	128K / 65.8 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than TIGER-Lab/Qwen2.5-32B-Instruct-CFT.