GLM 4.6 — Hardware Requirements & GPU Compatibility
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GLM 4.6 is a 356.8B-parameter open language model from zai-org in the GLM family. It supports a context window of up to 202,752 tokens. At Q4_K_M it needs about 214.69 GB of VRAM — see which GPUs and Macs can run it below.
15.0K downloads
1.2K likesSpecifications
- Publisher
- zai-org
- Family
- GLM
- Parameters
- 356.8B
- Architecture
- Glm4MoeForCausalLM
- Context Length
- 202,752 tokens
- Vocabulary Size
- 151,552
- Release Date
- 2025-09-30
- License
- MIT
Get Started
HuggingFace
How Much VRAM Does GLM 4.6 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 152.3 GB | 183.8 GB | 151.63 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 156.7 GB | 188.2 GB | 156.09 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 174.6 GB | 206.1 GB | 173.93 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 179.0 GB | 210.5 GB | 178.39 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 214.7 GB | 246.2 GB | 214.07 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 254.8 GB | 286.3 GB | 254.21 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 295.0 GB | 326.5 GB | 294.35 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 357.4 GB | 388.9 GB | 356.79 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run GLM 4.6?
Q4_K_M · 214.7 GBGLM 4.6 (Q4_K_M) requires 214.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 280+ GB is recommended. Using the full 203K context window can add up to 31.5 GB, bringing total usage to 246.2 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run GLM 4.6?
Q4_K_M · 214.7 GB2 devices with unified memory can run GLM 4.6, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomBenchmarks
View all 1 →Related Models
Frequently Asked Questions
- How much VRAM does GLM 4.6 need?
GLM 4.6 requires 214.7 GB of VRAM at Q4_K_M, or 357.4 GB at Q8_0. Full 203K context adds up to 31.5 GB (246.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 356.8B × 4.8 bits ÷ 8 = 214.1 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 32.1 GB (at full 203K context)
VRAM usage by quantization
Q4_K_M214.7 GBQ4_K_M + full context246.2 GB- Can NVIDIA GeForce RTX 5090 run GLM 4.6?
No — GLM 4.6 requires at least 98.7 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for GLM 4.6?
For GLM 4.6, Q4_K_M (214.7 GB) offers the best balance of quality and VRAM usage. Q5_K_S (245.9 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 98.7 GB.
VRAM requirement by quantization
IQ2_XXS98.7 GBIQ3_XS147.8 GBQ4_0179.0 GBIQ4_NL201.3 GBQ4_K_M ★214.7 GBQ8_0357.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run GLM 4.6 on a Mac?
GLM 4.6 requires at least 98.7 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 4.6 locally?
Yes — GLM 4.6 can run locally on consumer hardware. At Q4_K_M quantization it needs 214.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of GLM 4.6?
At Q4_K_M, the download is about 214.07 GB. The full-precision Q8_0 version is 356.79 GB. The smallest option (IQ2_XXS) is 98.12 GB.
- Which GPUs can run GLM 4.6?
No single consumer GPU has enough VRAM to run GLM 4.6 at Q4_K_M (214.7 GB). Multi-GPU or professional hardware is required.
- Which devices can run GLM 4.6?
2 devices with unified memory can run GLM 4.6 at Q4_K_M (214.7 GB), including 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.