davidsyoung·GLM 5·GlmMoeDsaForCausalLM

GLM 5.3 EXL3 TR3 3.42bpw — Hardware Requirements & GPU Compatibility

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GLM 5.3 EXL3 TR3 3.42bpw is a 177.5B-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 110.74 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
177.5B
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 3.42bpw Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.4079.7 GB
Q3_K_Mest.3.9090.8 GB
Q4_K_Mest.4.80110.7 GB
Q5_K_Mest.5.70130.7 GB
Q6_Kest.6.60150.7 GB
Q8_0est.8.00181.7 GB
BF16est.16.00359.3 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 3.42bpw?

Q4_K_M · 110.7 GB

GLM 5.3 EXL3 TR3 3.42bpw (Q4_K_M) requires 110.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 144+ GB is recommended. Using the full 1049K context window can add up to 2006.1 GB, bringing total usage to 2116.8 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.

Which Devices Can Run GLM 5.3 EXL3 TR3 3.42bpw?

Q4_K_M · 110.7 GB

11 devices with unified memory can run GLM 5.3 EXL3 TR3 3.42bpw, 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 3.42bpw need?

GLM 5.3 EXL3 TR3 3.42bpw requires 110.7 GB of VRAM at Q4_K_M, or 359.3 GB at BF16. Full 1049K context adds up to 2006.1 GB (2116.8 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 177.5B × 4.8 bits ÷ 8 = 106.5 GB

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

KV Cache + Overhead 2010.4 GB (at full 1049K context)

VRAM usage by quantization

110.7 GB
2116.8 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 5090 run GLM 5.3 EXL3 TR3 3.42bpw?

No — GLM 5.3 EXL3 TR3 3.42bpw requires at least 79.7 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 3.42bpw?

For GLM 5.3 EXL3 TR3 3.42bpw, Q4_K_M (110.7 GB) offers the best balance of quality and VRAM usage. Q5_K_M (130.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 79.7 GB.

VRAM requirement by quantization

Q2_K
79.7 GB
Q4_K_M
110.7 GB
Q5_K_M
130.7 GB
Q6_K
150.7 GB
Q8_0
181.7 GB
BF16
359.3 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run GLM 5.3 EXL3 TR3 3.42bpw on a Mac?

GLM 5.3 EXL3 TR3 3.42bpw requires at least 79.7 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 3.42bpw locally?

Yes — GLM 5.3 EXL3 TR3 3.42bpw can run locally on consumer hardware. At Q4_K_M quantization it needs 110.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is GLM 5.3 EXL3 TR3 3.42bpw?

At Q4_K_M, GLM 5.3 EXL3 TR3 3.42bpw can reach ~43 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 ÷ 110.7 × 0.65 = ~47 tok/s

Estimated speed at Q4_K_M (110.7 GB)

~47 tok/s
~47 tok/s
~43 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 3.42bpw?

At Q4_K_M, the download is about 106.51 GB. The full-precision BF16 version is 355.03 GB. The smallest option (Q2_K) is 75.44 GB.

Which GPUs can run GLM 5.3 EXL3 TR3 3.42bpw?

No single consumer GPU has enough VRAM to run GLM 5.3 EXL3 TR3 3.42bpw at Q4_K_M (110.7 GB). Multi-GPU or professional hardware is required.

Which devices can run GLM 5.3 EXL3 TR3 3.42bpw?

18 devices with unified memory can run GLM 5.3 EXL3 TR3 3.42bpw at Q4_K_M (110.7 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.