Falcon 180B Chat on Intel Core i5-1235U / i7-1255U NAS (96 GB)

Can the Intel Core i5-1235U / i7-1255U NAS (96 GB) run Falcon 180B Chat?

Barely: it runs very slowly (tight fit)

Very slow (tight fit). At Q2_K it needs about 79.4 GB of 83.5 GB usable, with an estimated speed of 0.4 tok/s.

Best quant: Q2_K
Generation speed: 0.4 tok/s
Prompt processing: 1.4 tok/s
First token (1K prompt): 750.3 s
Largest safe context: 2K

Best app to run it on the Intel Core i5-1235U / i7-1255U NAS (96 GB)

On Linux

Ollama

Command line + local API · runs on llama.cpp (ggml), MLX (Apple silicon, preview)

One command with Ollama’s own build of this model.
Serves an OpenAI-compatible API that other apps and coding tools can use.

ollama run falcon:180b

llama.cpp Usually the first to support new model architectures.
KoboldCpp

How we choose: the files published for this model, which apps run in a container on a NAS without a graphics card (models run on its processor), and whether the model fits fully in the memory models can use. Details.

Download Falcon 180B Chat

Recommended for the Intel Core i5-1235U / i7-1255U NAS (96 GB): Q2_K. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

ollama run falcon:180b

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q2_K (IQ2_XXS) file (opens in a new tab)

huggingface.co/mradermacher/falcon-180B-chat-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/falcon-180B-chat-i1-GGUF:IQ2_XXS

Original weights · Hugging Face

Full-precision files from TII, for fine-tuning, vLLM, Transformers.

huggingface.co/tiiuae/falcon-180B-chat (opens in a new tab)

Free Hugging Face account needed: accept the license on the model page and the download starts right away.

Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 23Basic quality (D) · 23 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at Q2_K, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Very slowtight fit: How well it runs on the Intel Core i5-1235U / i7-1255U NAS (96 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

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 qualityEditorial quality tier of the model, scaled by the quantization or precision used.	10.7 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.	24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	1.5 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Match score	51.2 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every quantization on the Intel Core i5-1235U / i7-1255U NAS (96 GB)

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q2_K`	79.4 GB	83.5 GB	0.4 tok/s	Very slowtight fit	23Basic quality (D) · 23 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (IQ2_XXS) (opens in a new tab)
`Q3_K_M`	95.6 GB	83.5 GB	—	Won't run	28Basic quality (D) · 28 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking.	GGUF files (opens in a new tab)
`Q4_K_M`	117 GB	83.5 GB	—	Won't run	32Basic quality (D) · 32 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking.	GGUF files (opens in a new tab)
`Q5_K_M`	135 GB	83.5 GB	—	Won't run	32Basic quality (D) · 32 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking.	GGUF files (opens in a new tab)
`Q6_K`	155 GB	83.5 GB	—	Won't run	33Basic quality (D) · 33 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking.	GGUF files (opens in a new tab)
`Q8_0`	198 GB	83.5 GB	—	Won't run	34Basic quality (D) · 34 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking.	GGUF files (opens in a new tab)
`F16`	367 GB	83.5 GB	—	Won't run	34Basic quality (D) · 34 of 100: how capable the model is at F16, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Memory figures assume 2K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

23Basic quality (D) · 23 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell Q2_K · 20.1 tok/s · Runs well
32Basic quality (D) · 32 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA B200 Q5_K_M · 45.2 tok/s · Runs great
32Basic quality (D) · 32 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H200 141GB SXM Q4_K_M · 32.8 tok/s · Runs great
32Basic quality (D) · 32 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H200 NVL Q4_K_M · 32.8 tok/s · Runs great
32Basic quality (D) · 32 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip Q5_K_M · 40.1 tok/s · Runs great
32Basic quality (D) · 32 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. AMD Instinct MI350X Q5_K_M · 38.9 tok/s · Runs great

Quick answers

How much memory does Falcon 180B Chat need on the Intel Core i5-1235U / i7-1255U NAS 96GB?

At Q2_K it needs about 79.4 GB. The Intel Core i5-1235U / i7-1255U NAS 96GB has 83.5 GB usable.

How fast is Falcon 180B Chat on the Intel Core i5-1235U / i7-1255U NAS 96GB?

About 0.4 tok/s at Q2_K, an estimate from the hardware’s memory bandwidth and the size of the model.

Which quantization of Falcon 180B Chat should I use on the Intel Core i5-1235U / i7-1255U NAS 96GB?

Q2_K. 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.