How much memory does GLM-5.3 need at 4-bit?

Unsloth's UD-Q4_K_XL GGUF is 467.29 GB, so our estimate is about 469.56 GB with 8,192 tokens of context and working space. Unsloth's own guide gives 372–475 GB for its 4-bit files.

What is the smallest GLM-5.3 file?

The smallest full-model files we found on 29 Oct 2026 are antirez/glm-5.3-gguf at 211.08 GB and Unsloth UD-IQ1_S at 216.72 GB. Pruned versions with experts removed are smaller but are not GLM-5.3 itself, so we do not score them.

Can GLM-5.3 run on 2× DGX Spark or a 256 GB Mac?

Unsloth says its UD-IQ2_M file (238.58 GB) works on 256 GB RAM devices such as 2× DGX Spark or a Mac Studio. That is a vendor claim we have not tested. On our rule a 256 GB Mac has about 192 GB usable, so we do not score it as a full fit.

Artificial Analysis gives GLM-5.3 (max) 32 on its Intelligence Index v5.0, checked 29 Oct 2026. Thinking is always on, with low, high and max settings.

Is GLM-5.3 free for commercial use?

The GLM-5.3 License is permissive and MIT-style. It adds one condition: Model-as-a-Service businesses with more than US$10 billion in revenue over the past 12 months need Z.ai's security review before commercial use. Read the licence before you ship.

Can I run GLM-5.3 locally?

Key facts

Not on one machine we list. GLM-5.3 has about 753B parameters with 40B active per token; its 4-bit GGUF needs about 469.56 GB, and even the smallest full-model file (211.08 GB) is larger than the 192 GB usable on a 256 GB Mac Studio M5 Ultra.

About 469.6 GB at UD-Q4_K_XL, our estimate. Checked 29 Oct 2026. Unsloth UD-Q4_K_XL GGUF.

Artificial Analysis scores GLM-5.3 (max) 32 on its Intelligence Index v5.0 (checked 29 Oct 2026). If you want a model that fits a 24 GB card, see what fits 24 GB, or work out your own setup in the VRAM calculator. The same pattern, a file bigger than one box, is MiniMax M3.1 Flash and DeepSeek V4.1 Flash. The closest machines on our list are the Mac Studio M5 Ultra 256GB and the DGX Spark 128GB. Every model is on the model list.

None of the 43 graphics cards, PCs and Macs on our list holds the whole model at the standard quality in its graphics memory.

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Which graphics cards run it

Seven popular graphics cards and two PCs with two cards each, at the standard quality (Q4). Click one for the full answer: memory, speed and price.

Doesn't fit10

Not enough graphics memory: it needs about 469.6 GB.

RTX 3060 12GBhas 12 GB
RTX 4060 Ti 16GBhas 16 GB
RTX 3090has 24 GB
RTX 4090has 24 GB
RTX 5080has 16 GB
RX 9060 XT 16GBhas 16 GB
RTX 5090has 32 GB
RX 7900 XTXhas 24 GB
Dual RTX 3090has 48 GB
Dual RTX 4090has 48 GB

Every model on every card

GLM-5.3 needs 469.6 GB at Q4. When a new open model would fit 128 GB, or the cards and Macs that run it change price, The Fit List tells you, with the memory it needs and dated EU/US prices. Plus a free GPU buying cheat sheet (PDF) now.

Which Macs and mini PCs run it

Macs and mini PCs from the picker, at the standard quality (Q4). A Mac shares its memory with the rest of the computer. Each name opens that machine's page.

Doesn't fit14

Not enough shared memory: it needs about 469.6 GB.

Mac mini M4 16GBhas 16 GB
Mac mini M6 32GBhas 32 GB
Mac Studio M5 Max 36GBhas 36 GB
Mac mini M4 Pro 64GBhas 64 GB
Mac mini M5 Pro 64GBhas 64 GB
GMKtec EVO-X2 (Ryzen AI Max+ 395) 64GBhas 64 GB
NVIDIA DGX Spark 64GBhas 64 GB
Mac Studio M5 Ultra 96GBhas 96 GB
GMKtec EVO-X2 (Ryzen AI Max+ 395) 128GBhas 128 GB
NVIDIA DGX Spark 128GBhas 128 GB
GEEKOM A9 Mega (Ryzen AI Max+ 395) 128GBhas 128 GB
Beelink GTR9 Pro (Ryzen AI Max+ 395) 128GBhas 128 GB
Mac Studio M5 Max 128GBhas 128 GB
Mac Studio M5 Ultra 256GBhas 256 GB

Cheapest hardware for each size

From all 43 graphics cards, PCs and Macs on our list. "Runs slowly" means part of the model runs from normal memory: cheaper, but much slower. A smaller download needs less memory and answers a little less well.

Standard quality (UD-Q4_K_XL)No machine on our list runs this size.
Standard quality (UD-Q4_K_XL), runs slowlyNo machine on our list runs this size.
Smallest download (IQ2_XXS)No machine on our list runs this size.
Smallest download (IQ2_XXS), runs slowlyNo machine on our list runs this size.

Prices excl. shipping unless marked. Euro prices incl. VAT where the seller charges it. Dollar prices are converted from our euro prices without the 21% EU VAT, before US sales tax.

Prices moved: see Building a local LLM rig in the RAMageddon.

About GLM-5.3

753.33B total, 40B active. Parameter count is an estimate. More parameters usually means a smarter model that needs more memory.

Licence:: GLM-5.3 License source
Longest conversation:: about 1573 pages of text (1,048,576 tokens)
Input:: text
Released:: 18 Aug 2026 source

Sources and method

Z.ai's open-weight sparse mixture of experts (GLM-5.3 License: MIT-style and permissive, plus a Model-as-a-Service clause: MaaS businesses with more than US$10 billion revenue in the past 12 months need Z.AI's security review before commercial use). Hugging Face safetensors metadata lists 753,329,940,480 parameters (F8_E4M3 751.23B, BF16 2.10B), stored here as 753.33B, so our count is an estimate. About 40B are active per token (Artificial Analysis lists 753B total / 40B active; Unsloth's guide says 744B). Config: GlmMoeDsaForCausalLM, 78 layers (first 3 dense), hidden size 6144, 64 attention heads, 256 routed experts plus 1 shared, 8 routed per token, 1 MTP layer, text only, max_position_embeddings 1,048,576. Attention is MLA (kv_lora_rank 512 + qk_rope_head_dim 64 = 576 cached values per token per layer) with a DeepSeek-style sparse indexer (32 index heads x 128, top-k 2048). We store kvHeads 1 and headDim 576, so our K+V formula gives 1.47 GB at 8,192 tokens. A runtime that caches only the 576-wide latent needs about half (0.74 GB in BF16); the indexer key cache is not counted. Our figure is a conservative estimate. Q4 uses the measured Unsloth UD-Q4_K_XL file, 467.29 GB (467,289,116,837 bytes). Q5, Q8 and FP16 are our bytes-per-parameter estimates (0.71 / 1.07 / 2.0 x 753.33B). Unsloth GGUF sizes, shards summed from the Hugging Face tree, decimal GB, checked 29 Oct 2026 (https://huggingface.co/unsloth/GLM-5.3-GGUF): UD-IQ1_S 216.72, UD-IQ1_M 228.49, UD-IQ2_M 238.58, UD-Q2_K_XL 253.88, UD-IQ3_XXS 281.69, UD-Q3_K_XL 342.97, UD-IQ4_XS 365.31, UD-Q4_K_XL 467.29, UD-Q5_K_XL 562.47, UD-Q6_K_XL 684.37, Q8_0 801.36, BF16 1,507.99. Smallest full-model file we found: antirez/glm-5.3-gguf IQ2_XXS mix, 211.08 GB (https://huggingface.co/antirez/glm-5.3-gguf). MLX: mlx-community/GLM-5.3-4bit 418.32 GB; pipenetwork/GLM-5.3-MLX-mixed-3_6bit 332.58 GB. NVIDIA NVFP4 checkpoint 464.14 GB (https://huggingface.co/nvidia/GLM-5.3-NVFP4). Official FP8 weights are 755.63 GB; BF16 repo zai-org/GLM-5.3-BF16 is 1,506.67 GB. Pruned derivatives with experts removed are not GLM-5.3 and are not scored. Runs in mainline llama.cpp per Unsloth's guide (https://unsloth.ai/docs/models/glm-5.3). Unsloth says UD-IQ2_M works on 256 GB RAM devices such as 2x DGX Spark or a Mac Studio; that is a vendor claim, not tested by us, and it relies on RAM offload. With 192 GB usable on a 256 GB Mac Studio M5 Ultra, even the 211.08 GB file does not fit, so no machine on our list runs GLM-5.3 fully in fast memory. Released by Z.ai on 18 August 2026 (API; docs.z.ai release notes and Artificial Analysis), with the Hugging Face repo created 25 August 2026. Artificial Analysis Intelligence Index v5.0: 32 for GLM-5.3 (max), checked 29 Oct 2026 (https://artificialanalysis.ai/models/glm-5-3). Thinking is always on (low / high / max). Ollama tag: not checked.

Parameter source · Architecture source · Model page

Memory at each quality level

Each download of GLM-5.3 is a different size. The total adds the file, the memory a conversation of about 12 pages of text (8,192 tokens) takes, and 0.8 GB of working space. A measured file size is labelled; the rest is our estimate. The last column is the cheapest machine that holds the total.

Swipe the table sideways to see every column, up to the cheapest machine.

Memory per quant for GLM-5.3
Quality (file)	File size	Conversation	Working space	Total	Cheapest machine that holds it
BF16	1507.99 GBmeasured GGUF	1.5 GB	0.8 GB	1,510.3 GB	No machine on our list runs this size.
Q8_0	801.36 GBmeasured GGUF	1.5 GB	0.8 GB	803.6 GB	No machine on our list runs this size.
UD-Q6_K_XL	684.37 GBmeasured GGUF	1.5 GB	0.8 GB	686.6 GB	No machine on our list runs this size.
UD-Q5_K_XL	562.47 GBmeasured GGUF	1.5 GB	0.8 GB	564.7 GB	No machine on our list runs this size.
UD-Q4_K_XL	467.29 GBmeasured GGUF	1.5 GB	0.8 GB	469.6 GB	No machine on our list runs this size.
UD-IQ4_XS	365.31 GBmeasured GGUF	1.5 GB	0.8 GB	367.6 GB	No machine on our list runs this size.
UD-Q3_K_XL	342.97 GBmeasured GGUF	1.5 GB	0.8 GB	345.2 GB	No machine on our list runs this size.
UD-IQ3_XXS	281.69 GBmeasured GGUF	1.5 GB	0.8 GB	284.0 GB	No machine on our list runs this size.
UD-Q2_K_XL	253.88 GBmeasured GGUF	1.5 GB	0.8 GB	256.2 GB	No machine on our list runs this size.
UD-IQ2_M	238.58 GBmeasured GGUF	1.5 GB	0.8 GB	240.9 GB	No machine on our list runs this size.
UD-IQ1_M	228.49 GBmeasured GGUF	1.5 GB	0.8 GB	230.8 GB	No machine on our list runs this size.
UD-IQ1_S	216.72 GBmeasured GGUF	1.5 GB	0.8 GB	219.0 GB	No machine on our list runs this size.
IQ2_XXS	211.08 GBmeasured GGUF	1.5 GB	0.8 GB	213.4 GB	No machine on our list runs this size.

speed: not estimated for MoE yet.

Speeds and memory are our estimate from the hardware specs, not a measured test. Prices are dated and may change. How we calculate

Questions

Can I run GLM-5.3 locally?: Not fully in fast memory on any machine we list. GLM-5.3 has about 753B parameters (40B active), and the smallest full-model file we found is 211.08 GB (a community IQ2_XXS GGUF). With 8,192 tokens of context that needs about 213 GB, more than the 192 GB usable on a 256 GB Mac Studio M5 Ultra.
How much memory does GLM-5.3 need at 4-bit?: Unsloth's UD-Q4_K_XL GGUF is 467.29 GB, so our estimate is about 469.56 GB with 8,192 tokens of context and working space. Unsloth's own guide gives 372–475 GB for its 4-bit files.
What is the smallest GLM-5.3 file?: The smallest full-model files we found on 29 Oct 2026 are antirez/glm-5.3-gguf at 211.08 GB and Unsloth UD-IQ1_S at 216.72 GB. Pruned versions with experts removed are smaller but are not GLM-5.3 itself, so we do not score them.
Can GLM-5.3 run on 2× DGX Spark or a 256 GB Mac?: Unsloth says its UD-IQ2_M file (238.58 GB) works on 256 GB RAM devices such as 2× DGX Spark or a Mac Studio. That is a vendor claim we have not tested. On our rule a 256 GB Mac has about 192 GB usable, so we do not score it as a full fit.
How good is GLM-5.3?: Artificial Analysis gives GLM-5.3 (max) 32 on its Intelligence Index v5.0, checked 29 Oct 2026. Thinking is always on, with low, high and max settings.
Is GLM-5.3 free for commercial use?: The GLM-5.3 License is permissive and MIT-style. It adds one condition: Model-as-a-Service businesses with more than US$10 billion in revenue over the past 12 months need Z.ai's security review before commercial use. Read the licence before you ship.