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Can the NVIDIA RTX 1000 Ada Generation Laptop GPU run Apertus v1.5 70B?

46Fair quality (C) · 46 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking.

No, it doesn’t fit

No. Apertus v1.5 70B needs about 32.4 GB even at Q2_K; the NVIDIA RTX 1000 Ada Generation Laptop GPU has 6.0 GB usable.

Download Apertus v1.5 70B

Original weights · Hugging Face

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

huggingface.co/swiss-ai/Apertus-v1.5-70B (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 46Fair quality (C) · 46 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 6/100 (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 1000 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.6.2 / 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 score6.2 / 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 RTX 1000 Ada Generation Laptop GPU

Quant Memory needed Available Speed Runs Quality Download
Q2_K 32.4 GB 6.0 GB — Won't run 46Fair quality (C) · 46 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 6/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q3_K_M 38.9 GB 6.0 GB — Won't run 55Good quality (B) · 55 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 7/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q4_K_M 47.5 GB 6.0 GB — Won't run 62Good quality (B) · 62 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q5_K_M 54.7 GB 6.0 GB — Won't run 64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q6_K 62.6 GB 6.0 GB — Won't run 65Good quality (B) · 65 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
Q8_0 79.9 GB 6.0 GB — Won't run 66Good quality (B) · 66 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 8/100 (quality, fit, speed and memory use) sets the ranking. All files (opens in a new tab)
F16 148 GB 6.0 GB — Won't run 66Good quality (B) · 66 of 100: how capable the model is at F16, whatever it runs on. Match score 8/100 (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 1000 Ada Generation Laptop GPU

Quick answers

How much memory does Apertus v1.5 70B need on the NVIDIA RTX 1000 Ada Generation Laptop GPU 6GB?

Even at Q2_K it needs about 32.4 GB; the NVIDIA RTX 1000 Ada Generation Laptop GPU 6GB has 6.0 GB usable.

What can the NVIDIA RTX 1000 Ada Generation Laptop GPU 6GB run instead?

Nemotron Labs Dory 1.0 4B, Spark-X2.6 4B and Nanbeige4.2 3B run best on it; the page lists more, each with its speed.

What hardware can run Apertus v1.5 70B?

NVIDIA RTX PRO 6000 Blackwell 96GB, M4 Max 64GB and M2 Ultra 192GB 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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