GLM 5.3 Flash MXFP4 Mixed CT AutoRound — Hardware Requirements & GPU Compatibility
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GLM 5.3 Flash MXFP4 Mixed CT AutoRound is a 321.3B-parameter open language model from INCModel3 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.
224 downloads
2 likesSpecifications
- Publisher
- INCModel3
- Family
- GLM 5
- Parameters
- 321.3B
- Architecture
- Glm5NextForConditionalGeneration
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 154,880
- Release Date
- 2026-08-31
- License
- MIT
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How Much VRAM Does GLM 5.3 Flash MXFP4 Mixed CT AutoRound Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 138.4 GB | 910.0 GB | 136.56 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 158.4 GB | 930.0 GB | 156.64 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 194.6 GB | 966.2 GB | 192.79 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 230.8 GB | 1002.3 GB | 228.94 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 266.9 GB | 1038.5 GB | 265.09 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 323.1 GB | 1094.7 GB | 321.32 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 644.5 GB | 1416.0 GB | 642.65 GB | Brain floating point 16 — preferred for training |
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 MXFP4 Mixed CT AutoRound?
Q4_K_M · 194.6 GBGLM 5.3 Flash MXFP4 Mixed CT AutoRound (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 MXFP4 Mixed CT AutoRound?
Q4_K_M · 194.6 GB3 devices with unified memory can run GLM 5.3 Flash MXFP4 Mixed CT AutoRound, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does GLM 5.3 Flash MXFP4 Mixed CT AutoRound need?
GLM 5.3 Flash MXFP4 Mixed CT AutoRound 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
Q4_K_M194.6 GBQ4_K_M + full context966.2 GB- Can NVIDIA GeForce RTX 5090 run GLM 5.3 Flash MXFP4 Mixed CT AutoRound?
No — GLM 5.3 Flash MXFP4 Mixed CT AutoRound requires at least 138.4 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 Flash MXFP4 Mixed CT AutoRound?
For GLM 5.3 Flash MXFP4 Mixed CT AutoRound, 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 Q2_K at 138.4 GB.
VRAM requirement by quantization
Q2_K138.4 GBQ4_K_M ★194.6 GBQ5_K_M230.8 GBQ6_K266.9 GBQ8_0323.1 GBBF16644.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run GLM 5.3 Flash MXFP4 Mixed CT AutoRound on a Mac?
GLM 5.3 Flash MXFP4 Mixed CT AutoRound requires at least 138.4 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 Flash MXFP4 Mixed CT AutoRound locally?
Yes — GLM 5.3 Flash MXFP4 Mixed CT AutoRound 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 MXFP4 Mixed CT AutoRound?
At Q4_K_M, GLM 5.3 Flash MXFP4 Mixed CT AutoRound 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 B300 → 8000 ÷ 194.6 × 0.65 = ~27 tok/s
Estimated speed at Q4_K_M (194.6 GB)
~27 tok/s~25 tok/s~25 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of GLM 5.3 Flash MXFP4 Mixed CT AutoRound?
At Q4_K_M, the download is about 192.79 GB. The full-precision BF16 version is 642.65 GB. The smallest option (Q2_K) is 136.56 GB.
- Which GPUs can run GLM 5.3 Flash MXFP4 Mixed CT AutoRound?
No single consumer GPU has enough VRAM to run GLM 5.3 Flash MXFP4 Mixed CT AutoRound at Q4_K_M (194.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run GLM 5.3 Flash MXFP4 Mixed CT AutoRound?
4 devices with unified memory can run GLM 5.3 Flash MXFP4 Mixed CT AutoRound 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.