What are the hardware requirements for GLM 5.3 Flash MLX Q9?

GLM 5.3 Flash MLX Q9 requires approximately 352.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 5.3 Flash MLX Q9 and how large is it?

GLM 5.3 Flash MLX Q9 is developed by inferencerlabs. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does GLM 5.3 Flash MLX Q9 perform on standard benchmarks?

GLM 5.3 Flash MLX Q9 has the following published scores: LMSYS ELO 1259. Compare against reference models on this page or on the LLM Explorer leaderboards.

GLM 5.3 Flash MLX Q9 by inferencerlabs — VRAM 352.2GB

Name: GLM 5.3 Flash MLX Q9
Author: inferencerlabs

GLM 5.3 Flash MLX Q9 is an open-source language model by inferencerlabs. Features: LLM, VRAM: 352.2GB, Quantized, LLM Explorer Score: 0.41, ELO: 1259.

Base model:quantized:zai-org/g... Base model:zai-org/glm-5.3-fla... Conversational En Glm5 next Image-text-to-text Mlx Q9 Quantized Region:us Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/inferencerlabs/GLM-5.3-Flash-MLX-Q9

GLM 5.3 Flash MLX Q9 Benchmarks

LMSys ELO 1259 vs 1272 (so35) -1%

^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 5.3 Flash MLX Q9 Parameters and Internals

LLM Name	GLM 5.3 Flash MLX Q9
Repository 🤗	https://huggingface.co/inferencerlabs/GLM-5.3-Flash-MLX-Q9
Base Model(s)	zai-org/GLM-5.3-Flash-BF16 zai-org/GLM-5.3-Flash-BF16
Required VRAM	352.2 GB
Updated	2026-08-30
Maintainer	inferencerlabs
Model Type	glm5_next
Model Files	10.2 GB: 1-of-42 8.3 GB: 2-of-42 8.3 GB: 3-of-42 8.3 GB: 4-of-42 8.3 GB: 5-of-42 8.3 GB: 6-of-42 8.3 GB: 7-of-42 8.3 GB: 8-of-42 8.3 GB: 9-of-42 8.3 GB: 10-of-42 8.3 GB: 11-of-42 8.3 GB: 12-of-42 8.3 GB: 13-of-42 8.3 GB: 14-of-42 8.3 GB: 15-of-42 8.3 GB: 16-of-42 8.3 GB: 17-of-42 8.3 GB: 18-of-42 8.3 GB: 19-of-42 8.3 GB: 20-of-42 8.3 GB: 21-of-42 8.3 GB: 22-of-42 8.3 GB: 23-of-42 8.3 GB: 24-of-42 8.3 GB: 25-of-42 8.3 GB: 26-of-42 8.3 GB: 27-of-42 8.3 GB: 28-of-42 8.3 GB: 29-of-42 8.3 GB: 30-of-42 8.3 GB: 31-of-42 8.3 GB: 32-of-42 8.3 GB: 33-of-42 8.3 GB: 34-of-42 8.3 GB: 35-of-42 8.3 GB: 36-of-42 8.3 GB: 37-of-42 8.3 GB: 38-of-42 8.3 GB: 39-of-42 8.3 GB: 40-of-42 8.3 GB: 41-of-42 10.0 GB: 42-of-42
Supported Languages	en
Quantization Type	q9
Model Architecture	Glm5NextForConditionalGeneration
Transformers Version	5.16.0

Rank the GLM 5.3 Flash MLX Q9 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

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