davidsyoung·GLM 5·GlmMoeDsaForCausalLM

GLM 5.3 EXL3 TR3 3.25bpw — Hardware Requirements & GPU Compatibility

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GLM 5.3 EXL3 TR3 3.25bpw is a 169.6B-parameter open language model from davidsyoung in the GLM 5 family. It supports a context window of up to 1,048,576 tokens. At Q4_K_M it needs about 106.00 GB of VRAM — see which GPUs and Macs can run it below.

1.1K downloads 7 likes1049K context
Based on GLM 5.3

Specifications

Publisher
davidsyoung
Family
GLM 5
Parameters
169.6B
Architecture
GlmMoeDsaForCausalLM
Context Length
1,048,576 tokens
Vocabulary Size
154,880
Release Date
2026-08-28
License
Other

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How Much VRAM Does GLM 5.3 EXL3 TR3 3.25bpw Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.4076.3 GB
Q3_K_Mest.3.9086.9 GB
Q4_K_Mest.4.80106 GB
Q5_K_Mest.5.70125.1 GB
Q6_Kest.6.60144.2 GB
Q8_0est.8.00173.8 GB
BF16est.16.00343.5 GB

est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.

Which GPUs Can Run GLM 5.3 EXL3 TR3 3.25bpw?

Q4_K_M · 106 GB

GLM 5.3 EXL3 TR3 3.25bpw (Q4_K_M) requires 106 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 138+ GB is recommended. Using the full 1049K context window can add up to 2006.1 GB, bringing total usage to 2112.1 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.

Which Devices Can Run GLM 5.3 EXL3 TR3 3.25bpw?

Q4_K_M · 106 GB

11 devices with unified memory can run GLM 5.3 EXL3 TR3 3.25bpw, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Pro 16" M5 Max (128 GB).

Related Models

Frequently Asked Questions

How much VRAM does GLM 5.3 EXL3 TR3 3.25bpw need?

GLM 5.3 EXL3 TR3 3.25bpw requires 106 GB of VRAM at Q4_K_M, or 343.5 GB at BF16. Full 1049K context adds up to 2006.1 GB (2112.1 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 169.6B × 4.8 bits ÷ 8 = 101.8 GB

KV Cache + Overhead 4.2 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 2010.3 GB (at full 1049K context)

VRAM usage by quantization

106.0 GB
2112.1 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 5090 run GLM 5.3 EXL3 TR3 3.25bpw?

No — GLM 5.3 EXL3 TR3 3.25bpw requires at least 76.3 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.

What's the best quantization for GLM 5.3 EXL3 TR3 3.25bpw?

For GLM 5.3 EXL3 TR3 3.25bpw, Q4_K_M (106 GB) offers the best balance of quality and VRAM usage. Q5_K_M (125.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 76.3 GB.

VRAM requirement by quantization

Q2_K
76.3 GB
Q4_K_M
106.0 GB
Q5_K_M
125.1 GB
Q6_K
144.2 GB
Q8_0
173.8 GB
BF16
343.5 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run GLM 5.3 EXL3 TR3 3.25bpw on a Mac?

GLM 5.3 EXL3 TR3 3.25bpw requires at least 76.3 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.

Can I run GLM 5.3 EXL3 TR3 3.25bpw locally?

Yes — GLM 5.3 EXL3 TR3 3.25bpw can run locally on consumer hardware. At Q4_K_M quantization it needs 106 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is GLM 5.3 EXL3 TR3 3.25bpw?

At Q4_K_M, GLM 5.3 EXL3 TR3 3.25bpw can reach ~45 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: NVIDIA B2008000 ÷ 106.0 × 0.65 = ~49 tok/s

Estimated speed at Q4_K_M (106 GB)

~49 tok/s
~49 tok/s
~45 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of GLM 5.3 EXL3 TR3 3.25bpw?

At Q4_K_M, the download is about 101.78 GB. The full-precision BF16 version is 339.26 GB. The smallest option (Q2_K) is 72.09 GB.

Which GPUs can run GLM 5.3 EXL3 TR3 3.25bpw?

No single consumer GPU has enough VRAM to run GLM 5.3 EXL3 TR3 3.25bpw at Q4_K_M (106 GB). Multi-GPU or professional hardware is required.

Which devices can run GLM 5.3 EXL3 TR3 3.25bpw?

18 devices with unified memory can run GLM 5.3 EXL3 TR3 3.25bpw at Q4_K_M (106 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.