GLM-4 9B Chat 1M on Intel Core i5-1235U / i7-1255U NAS (64 GB)
Can the Intel Core i5-1235U / i7-1255U NAS (64 GB) run GLM-4 9B Chat 1M?
Yes, but slowly
Slow. At Q4_K_M it needs about 11.4 GB of 54.4 GB usable, with an estimated speed of 4.8 tok/s.
- Best quant
Q4_K_M- Generation speed
- 4.8 tok/s
- Prompt processing
- 25.8 tok/s
- First token (1K prompt)
- 39.6 s
- Largest safe context
- 520K
Best app to run it on the Intel Core i5-1235U / i7-1255U NAS (64 GB)
Download GLM-4 9B Chat 1M
Recommended for the Intel Core i5-1235U / i7-1255U NAS (64 GB): Q4_K_M. Every other quantization has its own download link in the table below.
Quantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q4_K_M file (opens in a new tab)
huggingface.co/bartowski/glm-4-9b-chat-1m-GGUF (opens in a new tab)
ollama run hf.co/bartowski/glm-4-9b-chat-1m-GGUF:Q4_K_MOriginal weights · Hugging Face
Full-precision files from Zhipu AI, for fine-tuning, vLLM, Transformers.
huggingface.co/zai-org/glm-4-9b-chat-1m (opens in a new tab)
How it’s rated
Match score
To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.
| Model quality | 20.5 / 45 | |
|---|---|---|
| Memory fit | 25.0 / 25 | |
| Speed | 5.2 / 15 | |
| Memory use | 4.8 / 15 | |
| Match score | 55.6 / 100 |
Every quantization on the Intel Core i5-1235U / i7-1255U NAS (64 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 9.4 GB | 54.4 GB | 7.9 tok/s | Slow | 33Basic quality (D) · 33 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q3_K_M | 10.3 GB | 54.4 GB | 6.2 tok/s | Slow | 40Fair quality (C) · 40 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4_K_M | 11.4 GB | 54.4 GB | 4.8 tok/s | Slow | 45Fair quality (C) · 45 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 12.4 GB | 54.4 GB | 4.0 tok/s | Slow | 46Fair quality (C) · 46 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 13.4 GB | 54.4 GB | 3.4 tok/s | Slow | 47Fair quality (C) · 47 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 15.7 GB | 54.4 GB | 2.5 tok/s | Very slow | 48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 24.6 GB | 54.4 GB | 1.1 tok/s | Very slow | 48Fair quality (C) · 48 of 100: how capable the model is at F16, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Other hardware that runs it
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4080 SUPER
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5070 Ti
-
48Fair quality (C) · 48 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5080
-
48Fair quality (C) · 48 of 100: how capable the model is at F16, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5090
-
47Fair quality (C) · 47 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 SUPER
Quick answers
How much memory does GLM-4 9B Chat 1M need on the Intel Core i5-1235U / i7-1255U NAS 64GB?
At Q4_K_M it needs about 11.4 GB. The Intel Core i5-1235U / i7-1255U NAS 64GB has 54.4 GB usable.
How fast is GLM-4 9B Chat 1M on the Intel Core i5-1235U / i7-1255U NAS 64GB?
About 4.8 tok/s at Q4_K_M, an estimate from the hardware’s memory bandwidth and the size of the model.
Which quantization of GLM-4 9B Chat 1M should I use on the Intel Core i5-1235U / i7-1255U NAS 64GB?
Q4_K_M. Of the versions that fit, it is the one that runs best; when two run equally well, the check prefers the higher-rated one.
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.