GLM 5.3 Flash EXL3 K2 — Hardware Requirements & GPU Compatibility
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GLM 5.3 Flash EXL3 K2 is a 48.9B-parameter open language model from vcruz305 in the GLM 5 family. It supports a context window of up to 1,048,576 tokens. At Q4_K_M it needs about 31.12 GB of VRAM — see which GPUs and Macs can run it below.
Doesn't fit a 24 GB GPU
Smallest consumer fit → RTX 5090 · Q4_K_M · 41.7 GB · ~37 tok/s
Macs from 36 GB (Q4_K_M · ~10 tok/s)
MIT
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run GLM 5.3 Flash EXL3 K2
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve vcruz305/GLM-5.3-Flash-EXL3-K2 --max-model-len 16384vLLM repo with its own quantisation
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Fits on A100 80GB (38 GB headroom) · Q4_K_M
- Generation speed
- ~43 tok/s
- generation speed
- Cost per 1M output tokens
- $9.06
- per 1M output tokens
How Much VRAM Does GLM 5.3 Flash EXL3 K2 Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | On RTX 4090 (reference) | |
|---|---|---|---|---|
| 22.6 GB | 45.2 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Fits: 2K context · ~29 tok/s | |
| 25.6 GB | 48.3 GB | 3-bit medium — 3-bit medium quantization | Does not fit: needs 36.2 GB | |
| 31.1 GB | 53.8 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Does not fit: needs 41.7 GB | |
| 36.6 GB | 59.3 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Does not fit: needs 47.2 GB | |
| 42.1 GB | 64.8 GB | 6-bit, very good — 6-bit quantization, very good quality | Does not fit: needs 52.7 GB | |
| 50.7 GB | 73.3 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Does not fit: needs 61.2 GB | |
| 99.5 GB | 122.2 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Does not fit: needs 110.1 GB |
Selected Q4_K_M
4-bit medium quantization41.7GBat 16K context
- Weights
- 29.3 GB
- KV cache
- 12.1 GB
- Overhead
- 0.3 GB
Doesn't fit RTX 4090 (reference) · needs 17.7 GB more
Which Hardware Can Run GLM 5.3 Flash EXL3 K2?
Q4_K_M · 31.1 GBGLM 5.3 Flash EXL3 K2 (Q4_K_M) requires 31.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 41+ GB is recommended. Using the full 1049K context window can add up to 771.6 GB, bringing total usage to 802.7 GB. 1 GPU can run it, including NVIDIA GeForce RTX 5090. 78 devices with unified memory can run GLM 5.3 Flash EXL3 K2, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Studio M5 Max (48 GB).
32–40 GB
tight · up to 2K ctx
1 GPU · 2 Mac classes · 1 device family
RTX 5090~37Simulate output on RTX 5090M5 Max36 GB~10Simulate output on Mac Studio M5 Max (36 GB)M3 Pro*36 GB~3Simulate output on MacBook Pro 14" M3 Pro (36 GB)Orin~4Simulate output on NVIDIA Jetson AGX Orin 32GB48 GB
48 GB tier →fits · 6.3 GB free · up to 16K ctx
2 Mac classes · 1 device family
M5 Max48 GB~14Simulate output on Mac Studio M5 Max (48 GB)M5 Pro48 GB~7Simulate output on Mac Mini M5 Pro (48 GB)Snapdragon X2 Elite Extreme (X2E-96-100)~5Simulate output on Snapdragon X2 Elite Extreme Copilot+ PC
By VRAM tier · typical GPUs and Macs at Q4_K_M
Alternatives to GLM 5.3 Flash EXL3 K2
GLM 5 family · 6 models →Similar models
5| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| Mixtral 8x7B Instruct v0.1Mistral AI | 65.1 | 23.5 GB | ~92 | same size |
| Kimi Linear 48B A3B BaseMoonshot AI | — | 23.4 GB | ~275 | same size |
| Llama 3 3 Nemotron Super 49B V1 5NVIDIA | — | 22.8 GB | ~35 | same size |
| Nemotron H 47B Reasoning 128KNVIDIA | — | 107.2 GB | —needs > 24 GB | same size |
| AI21 Jamba Mini 1.5AI21 Labs | — | 117.8 GB | —needs > 24 GB | same size |
Specifications
- Publisher
- vcruz305
- Family
- GLM 5
- Parameters
- 48.9B
- Architecture
- Glm5NextForConditionalGeneration
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 154,880
- Release Date
- 2026-08-28
- License
- MIT
Frequently Asked Questions
How much VRAM does GLM 5.3 Flash EXL3 K2 need?
GLM 5.3 Flash EXL3 K2 requires 31.1 GB of VRAM at Q4_K_M, or 99.5 GB at BF16. Full 1049K context adds up to 771.6 GB (802.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 48.9B × 4.8 bits ÷ 8 = 29.3 GB
KV Cache + Overhead ≈ 1.8 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 773.4 GB (at full 1049K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 4090 run GLM 5.3 Flash EXL3 K2?
Yes, at Q2_K (22.6 GB) or lower. Higher quantizations like Q3_K_M (25.6 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
What's the best quantization for GLM 5.3 Flash EXL3 K2?
For GLM 5.3 Flash EXL3 K2, Q4_K_M (31.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (36.6 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 22.6 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run GLM 5.3 Flash EXL3 K2 on a Mac?
Yes — Mac Studio M5 Max (36 GB) and 65 other Macs can run GLM 5.3 Flash EXL3 K2. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 31.1 GB of usable unified memory (RAM minus macOS overhead).
Can I run GLM 5.3 Flash EXL3 K2 locally?
Yes — GLM 5.3 Flash EXL3 K2 can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is GLM 5.3 Flash EXL3 K2?
At Q4_K_M, GLM 5.3 Flash EXL3 K2 can reach ~154 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 B200 → 8000 ÷ 31.1 × 0.65 = ~167 tok/s
Estimated speed at Q4_K_M (31.1 GB)
Real-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 EXL3 K2?
At Q4_K_M, the download is about 29.31 GB. The full-precision BF16 version is 97.71 GB. The smallest option (Q2_K) is 20.76 GB.
Which GPUs can run GLM 5.3 Flash EXL3 K2?
1 consumer GPU can run GLM 5.3 Flash EXL3 K2 at Q4_K_M. Top options include NVIDIA GeForce RTX 5090.
Which devices can run GLM 5.3 Flash EXL3 K2?
78 devices with unified memory can run GLM 5.3 Flash EXL3 K2 at Q4_K_M (31.1 GB), including ASUS Ascent GX10, Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB), GMKtec EVO-X2 (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.