What are the hardware requirements for GLM 4.7 Flash AWQ?

GLM 4.7 Flash AWQ requires approximately 19.8 GB of VRAM and supports a context window of 198K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 4.7 Flash AWQ and how large is it?

GLM 4.7 Flash AWQ is developed by QuantTrio, a model with 31.2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does GLM 4.7 Flash AWQ perform on standard benchmarks?

GLM 4.7 Flash AWQ has the following published scores: LMSYS ELO 1365. Compare against reference models on this page or on the LLM Explorer leaderboards.

GLM 4.7 Flash AWQ by QuantTrio — VRAM 19.8GB, 198K context

Name: GLM 4.7 Flash AWQ
Author: QuantTrio

GLM 4.7 Flash AWQ is an open-source language model by QuantTrio. Features: 31.2b LLM, VRAM: 19.8GB, Context: 198K, License: mit, MoE, Quantized, LLM Explorer Score: 0.45, ELO: 1365.

Arxiv:2508.06471 4-bit Awq Base model:quantized:zai-org/g... Base model:zai-org/glm-4.7-fla... Conversational En Endpoints compatible Glm4 moe lite Moe Quantized Region:us Safetensors Sharded Tensorflow Vllm Zh

Model Card on HF 🤗: https://huggingface.co/QuantTrio/GLM-4.7-Flash-AWQ

GLM 4.7 Flash AWQ Benchmarks

LMSys ELO 1365 vs 1272 (so35) 7.3%

^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)

GLM 4.7 Flash AWQ Parameters and Internals

LLM Name	GLM 4.7 Flash AWQ
Repository 🤗	https://huggingface.co/QuantTrio/GLM-4.7-Flash-AWQ
Base Model(s)	zai-org/GLM-4.7-Flash zai-org/GLM-4.7-Flash
Model Size	31.2b
Required VRAM	19.8 GB
Updated	2026-10-14
Maintainer	QuantTrio
Model Type	glm4_moe_lite
Model Files	3.0 GB: 1-of-7 3.0 GB: 2-of-7 3.0 GB: 3-of-7 3.0 GB: 4-of-7 3.0 GB: 5-of-7 2.8 GB: 6-of-7 2.0 GB: 7-of-7
Supported Languages	en zh
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Glm4MoeLiteForCausalLM
License	mit
Context Length	202752
Model Max Length	202752
Transformers Version	5.0.0rc0
Tokenizer Class	PreTrainedTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	154880
Torch Data Type	float16

Rank the GLM 4.7 Flash AWQ 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 GLM 4.7 Flash AWQ

Best Alternatives	Context / RAM	Downloads	Likes
GLM 4.7 Flash	198K / 57.3 GB	2187874	1791
GLM 4.7 Flash	198K / 58.6 GB	295368	15
GLM 4.7 Flash Fable 5 Distill	198K / 58.6 GB	133	1
Mochi	198K / 58.6 GB	75	2
...ihui GLM 4.7 Flash Abliterated	198K / 58.6 GB	1196	84
GLM 4.7 Flash Derestricted	198K / 58.6 GB	156	34

Note: green Score (e.g. "73.2") means that the model is better than QuantTrio/GLM-4.7-Flash-AWQ.