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Can the NVIDIA RTX 3000 Ada Generation Laptop GPU run LongCat Flash Chat (560B)?

61Good quality (B) · 61 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking.

No, it doesn’t fit

No. LongCat Flash Chat (560B) needs about 226 GB even at Q2_K; the NVIDIA RTX 3000 Ada Generation Laptop GPU has 8.0 GB usable.

Download LongCat Flash Chat (560B)

Quantized files · GGUF

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

huggingface.co/ggml-org/LongCat-Flash-Chat-GGUF (opens in a new tab)

ollama run hf.co/ggml-org/LongCat-Flash-Chat-GGUF

Original weights · Hugging Face

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

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

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Meituan. The weights themselves download from Hugging Face.

github.com/meituan-longcat/LongCat-Flash-Chat (opens in a new tab)

git clone https://github.com/meituan-longcat/LongCat-Flash-Chat

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

How it’s rated

Quality 61Good quality (B) · 61 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 8/100 (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 RTX 3000 Ada Generation Laptop GPU: 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.8.3 / 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 score8.3 / 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 RTX 3000 Ada Generation Laptop GPU

Quant Memory needed Available Speed Runs Quality Download
Q2_K 226 GB 8.0 GB — Won't run 61Good quality (B) · 61 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q3_K_M 277 GB 8.0 GB — Won't run 73Great quality (A) · 73 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 9/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q4_K_M 344 GB 8.0 GB — Won't run 83Great quality (A) · 83 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q5_K_M 400 GB 8.0 GB — Won't run 85Excellent quality (A+) · 85 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q6_K 462 GB 8.0 GB — Won't run 87Excellent quality (A+) · 87 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
Q8_0 597 GB 8.0 GB — Won't run 88Excellent quality (A+) · 88 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 11/100 (quality, fit, speed and memory use) sets the ranking. GGUF files (opens in a new tab)
F16 1,125 GB 8.0 GB — Won't run 88Excellent quality (A+) · 88 of 100: how capable the model is at F16, whatever it runs on. Match score 11/100 (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

Models that do run on the NVIDIA RTX 3000 Ada Generation Laptop GPU

Quick answers

How much memory does LongCat Flash Chat (560B) need on the NVIDIA RTX 3000 Ada Generation Laptop GPU 8GB?

Even at Q2_K it needs about 226 GB; the NVIDIA RTX 3000 Ada Generation Laptop GPU 8GB has 8.0 GB usable.

What can the NVIDIA RTX 3000 Ada Generation Laptop GPU 8GB run instead?

K2 Horizon 7B, MiMo V2.6 Distill Qwen 9B and SenseNova Loop 9B Preview run best on it; the page lists more, each with its speed.

What hardware can run LongCat Flash Chat (560B)?

M3 Ultra 512GB, M5 Ultra 512GB and AMD Instinct MI350X 288GB run it; the page lists more, each with its speed.

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.

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