Z.ai·GLM 5·Glm5NextForConditionalGeneration

GLM 5.3 Flash — Hardware Requirements & GPU Compatibility

Vision

GLM 5.3 Flash is a 321.3B-parameter open language model from Z.ai in the GLM 5 family. It supports a context window of up to 1,048,576 tokens. At Q4_K_M it needs about 194.60 GB of VRAM — see which GPUs and Macs can run it below.

727.6K downloads 2.1K likes 101.0K quant downloads1049K context

Specifications

Publisher
Z.ai
Family
GLM 5
Parameters
321.3B
Architecture
Glm5NextForConditionalGeneration
Context Length
1,048,576 tokens
Vocabulary Size
154,880
Release Date
2026-08-25
License
MIT

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How Much VRAM Does GLM 5.3 Flash Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
IQ2_XXS2.2090.2 GB
IQ3_XXS3.10126.3 GB
Q2_K3.40138.4 GB
Q3_K_Mest.3.90158.4 GB
IQ4_XS4.30174.5 GB
Q4_K_Mest.4.80194.6 GB
Q5_K_Mest.5.70230.8 GB
Q6_K6.60266.9 GB
Q8_08.00323.1 GB
BF1616.00644.5 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 Flash?

Q4_K_M · 194.6 GB

GLM 5.3 Flash (Q4_K_M) requires 194.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 253+ GB is recommended. Using the full 1049K context window can add up to 771.6 GB, bringing total usage to 966.2 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.

Which Devices Can Run GLM 5.3 Flash?

Q4_K_M · 194.6 GB

3 devices with unified memory can run GLM 5.3 Flash, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.

Where to Download GLM 5.3 Flash

Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.

Related Models

Frequently Asked Questions

How much VRAM does GLM 5.3 Flash need?

GLM 5.3 Flash requires 194.6 GB of VRAM at Q4_K_M, or 644.5 GB at BF16. Full 1049K context adds up to 771.6 GB (966.2 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 321.3B × 4.8 bits ÷ 8 = 192.8 GB

KV Cache + Overhead 1.8 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 773.4 GB (at full 1049K context)

VRAM usage by quantization

194.6 GB
966.2 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 5090 run GLM 5.3 Flash?

No — GLM 5.3 Flash requires at least 90.2 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.

What's the best quantization for GLM 5.3 Flash?

For GLM 5.3 Flash, Q4_K_M (194.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (230.8 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 90.2 GB.

VRAM requirement by quantization

IQ2_XXS
90.2 GB
Q2_K
138.4 GB
Q4_K_M
194.6 GB
Q5_K_M
230.8 GB
Q6_K
266.9 GB
BF16
644.5 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run GLM 5.3 Flash on a Mac?

GLM 5.3 Flash requires at least 90.2 GB at IQ2_XXS, 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 Flash locally?

Yes — GLM 5.3 Flash can run locally on consumer hardware. At Q4_K_M quantization it needs 194.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is GLM 5.3 Flash?

At Q4_K_M, GLM 5.3 Flash can reach ~25 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 B3008000 ÷ 194.6 × 0.65 = ~27 tok/s

Estimated speed at Q4_K_M (194.6 GB)

~27 tok/s
~25 tok/s
~25 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 Flash?

At Q4_K_M, the download is about 192.79 GB. The full-precision BF16 version is 642.65 GB. The smallest option (IQ2_XXS) is 88.36 GB.

Which GPUs can run GLM 5.3 Flash?

No single consumer GPU has enough VRAM to run GLM 5.3 Flash at Q4_K_M (194.6 GB). Multi-GPU or professional hardware is required.

Which devices can run GLM 5.3 Flash?

4 devices with unified memory can run GLM 5.3 Flash at Q4_K_M (194.6 GB), including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.