What are the hardware requirements for Qwen1.5 32B Chat?

Qwen1.5 32B Chat requires approximately 65.5 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 Qwen1.5 32B Chat and how large is it?

Qwen1.5 32B Chat is developed by Qwen, a model with 32b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Qwen1.5 32B Chat perform on standard benchmarks?

Qwen1.5 32B Chat has the following published scores: MMLU 74.99, LMSYS ELO 1203. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen1.5 32B Chat by Qwen — VRAM 65.5GB, 32K context

Name: Qwen1.5 32B Chat
Author: Qwen

Qwen1.5 32B Chat is an open-source language model by Qwen. Features: 32b LLM, VRAM: 65.5GB, Context: 32K, License: other, HF Score: 63, LLM Explorer Score: 0.39, ELO: 1203, Arc: 66, HellaSwag: 85.5, MMLU: 75, TruthfulQA: 67, WinoGrande: 77.2, GSM8K: 7.1.

Arxiv:2309.16609 Chat Conversational Deploy:azure En Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen1.5-32B-Chat

Qwen1.5 32B Chat Benchmarks

LMSys ELO: 1203 vs 1272 (so35)^-5.4%

IFEval: 55.32 vs 88 (so35)^-37.1%

ARC: 66.04 vs 96.7 (so35)^-31.7%

HellaSwag: 85.49 vs 95.3 (gpt4)^-10.3%

MMLU: 74.99 vs 88.3 (so35)^-15.1%

TruthfulQA: 66.95 vs 59 (gpt4)^13.5%

WinoGrande: 77.19 vs 87.5 (gpt4)^-11.8%

GSM8K: 7.05 vs 96.4 (so35)^-92.7%

MATH Lvl 5: 19.56

LLME Score: 0.39095

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen1.5 32B Chat (Qwen/Qwen1.5-32B-Chat)

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Qwen1.5 32B Chat Parameters and Internals

Model Type

text-generation, chat

Additional Notes

Stable support of 32K context length for models of all sizes. No need of 'trust_remote_code'.

Supported Languages

multilingual ()

Training Details

Methodology:

supervised finetuning and direct preference optimization

Context Length:

32000

Model Architecture:

Transformer architecture with SwiGLU activation, attention QKV bias, group query attention, mixture of sliding window attention and full attention.

Input Output

Input Format:

tokenized input using the tokenizer

Accepted Modalities:

text

Output Format:

text response generation

Performance Tips:

If you encounter code switching or other undesirable results, use provided hyper-parameters in 'generation_config.json'.

LLM Name	Qwen1.5 32B Chat
Repository 🤗	https://huggingface.co/Qwen/Qwen1.5-32B-Chat
Model Size	32b
Required VRAM	65.5 GB
Updated	2026-04-15
Maintainer	Qwen
Model Type	qwen2
Model Files	3.9 GB: 1-of-17 3.9 GB: 2-of-17 3.9 GB: 3-of-17 3.9 GB: 4-of-17 3.9 GB: 5-of-17 3.9 GB: 6-of-17 3.9 GB: 7-of-17 3.9 GB: 8-of-17 3.9 GB: 9-of-17 3.9 GB: 10-of-17 3.9 GB: 11-of-17 3.9 GB: 12-of-17 3.9 GB: 13-of-17 3.9 GB: 14-of-17 3.9 GB: 15-of-17 3.9 GB: 16-of-17 3.1 GB: 17-of-17
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Quantized Models of the Qwen1.5 32B Chat

Model	Likes	Downloads	VRAM
Qwen1.5 32B Chat AWQ	18	2088	21 GB
Qwen1.5 32B Chat 4bit	3	23	54 GB
Qwen1.5 32B Chat 8bit	1	15	54 GB

Best Alternatives to Qwen1.5 32B Chat

Best Alternatives	Context / RAM	Downloads	Likes
Openbuddy Qwq 32B V24.2 200K	195K / 65.8 GB	24	3
Openbuddy Qwq 32B V24.1 200K	195K / 65.8 GB	12	3
Openbuddy Qwq 32B V25.2q 200K	195K / 65.8 GB	9	4
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	8	2
DeepSeek R1 Distill Qwen 32B	128K / 65.7 GB	1059570	1546
Qwen2.5 32B	128K / 65.5 GB	239028	174
Baichuan M2 32B	128K / 65.8 GB	110798	120
RomboUltima 32B	128K / 20.7 GB	28	6
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	65	17
OpenReasoning Nemotron 32B	128K / 65.8 GB	104686	123

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen1.5-32B-Chat.

Rank the Qwen1.5 32B Chat Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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

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Qwen1.5 32B Chat by Qwen