What are the hardware requirements for Internlm2 Math 20B AWQ?

Internlm2 Math 20B AWQ requires approximately 12.2 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Internlm2 Math 20B AWQ and how large is it?

Internlm2 Math 20B AWQ is developed by eabdullin, a model with 20b 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 Internlm2 Math 20B AWQ?

Internlm2 Math 20B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Internlm2 Math 20B AWQ by eabdullin — VRAM 12.2GB, 8K context

Name: Internlm2 Math 20B AWQ
Author: eabdullin

Internlm2 Math 20B AWQ is an open-source language model by eabdullin. Features: 20b LLM, VRAM: 12.2GB, Context: 8K, Quantized, LLM Explorer Score: 0.12.

4-bit Awq Custom code Feature-extraction Internlm2 Pytorch Quantized Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/eabdullin/internlm2-math-20b-awq

Internlm2 Math 20B AWQ Parameters and Internals

LLM Name	Internlm2 Math 20B AWQ
Repository 🤗	https://huggingface.co/eabdullin/internlm2-math-20b-awq
Base Model(s)	Internlm2 Math 20B internlm/internlm2-math-20b
Model Size	20b
Required VRAM	12.2 GB
Updated	2026-07-28
Maintainer	eabdullin
Model Type	internlm2
Model Files	2.0 GB: 1-of-7 1.9 GB: 2-of-7 2.0 GB: 3-of-7 2.0 GB: 4-of-7 2.0 GB: 5-of-7 1.2 GB: 6-of-7 1.1 GB: 7-of-7
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	InternLM2ForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.2
Is Biased	0
Tokenizer Class	InternLM2Tokenizer
Padding Token	</s>
Vocabulary Size	92544
Torch Data Type	float16

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Note: green Score (e.g. "73.2") means that the model is better than eabdullin/internlm2-math-20b-awq.