LongCat 2.5 (1.6T-A48B) on NVIDIA GeForce RTX 4090

Can the NVIDIA GeForce RTX 4090 run LongCat 2.5 (1.6T-A48B)?

No, it doesn’t fit

No. LongCat 2.5 (1.6T-A48B) needs about 714 GB even at Q2_K; the NVIDIA GeForce RTX 4090 has 24.0 GB usable.

Download LongCat 2.5 (1.6T-A48B)

Original weights · Hugging Face

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

huggingface.co/meituan-longcat/LongCat-2.5 (opens in a new tab)

No sign-in needed.

Links checked 4 hours ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 68Good quality (B) · 68 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 9/100 (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 Won't run: How well it runs on the NVIDIA GeForce RTX 4090: 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.	9.2 / 45
Memory fitFull marks when everything sits in GPU memory; fewer when part spills to system RAM.	0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	0.0 / 15
Match score	9.2 / 100

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

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

Every quantization on the NVIDIA GeForce RTX 4090

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q2_K`	714 GB	24.0 GB	—	Won't run	68Good quality (B) · 68 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q3_K_M`	874 GB	24.0 GB	—	Won't run	82Great quality (A) · 82 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q4_K_M`	1,088 GB	24.0 GB	—	Won't run	92Excellent quality (A+) · 92 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q5_K_M`	1,266 GB	24.0 GB	—	Won't run	94Excellent quality (A+) · 94 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q6_K`	1,462 GB	24.0 GB	—	Won't run	96Excellent quality (A+) · 96 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 13/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`Q8_0`	1,889 GB	24.0 GB	—	Won't run	97Excellent quality (A+) · 97 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 13/100 (quality, fit, speed and memory use) sets the ranking.	All files (opens in a new tab)
`F16`	3,562 GB	24.0 GB	—	Won't run	97Excellent quality (A+) · 97 of 100: how capable the model is at F16, whatever it runs on. Match score 13/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Hardware that can run it

None. No single GPU or device in our catalog runs this model on its own; it needs several GPUs working together.

Models that do run on the NVIDIA GeForce RTX 4090

90Excellent quality (A+) · 90 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.8 27B Q4_K_M · 44.5 tok/s
91Excellent quality (A+) · 91 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4B Q6_K · 124 tok/s
89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 27B Q4_K_M · 44.5 tok/s
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 27B Q4_K_M · 44.5 tok/s
90Excellent quality (A+) · 90 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking. Nanbeige4.3 33B Q4_K_M · 37.4 tok/s

Quick answers

How much memory does LongCat 2.5 (1.6T-A48B) need on the RTX 4090 24GB?

Even at Q2_K it needs about 714 GB; the RTX 4090 24GB has 24.0 GB usable.

What can the RTX 4090 24GB run instead?

Qwen3.8 27B, Gemma 4 26B-A4B and Qwen3.6 27B run best on it; the page lists more, each with its speed.

What hardware can run LongCat 2.5 (1.6T-A48B)?

No single GPU or device in our catalog runs it on its own; it needs several GPUs working together.

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.