Dolphin Mistral 24B Venice Edition on NVIDIA RTX A1000 Laptop GPU

Can the NVIDIA RTX A1000 Laptop GPU run Dolphin Mistral 24B Venice Edition?

No, it doesn’t fit

No. Dolphin Mistral 24B Venice Edition needs about 11.7 GB even at Q2_K; the NVIDIA RTX A1000 Laptop GPU has 4.0 GB usable.

Download Dolphin Mistral 24B Venice Edition

Recommended: Q2_K. 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 Q2_K file (opens in a new tab)

huggingface.co/mradermacher/Dolphin-Mistral-24B-Venice-Edition-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/Dolphin-Mistral-24B-Venice-Edition-i1-GGUF:Q2_K

Original weights · Hugging Face

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

huggingface.co/dphn/Dolphin-Mistral-24B-Venice-Edition (opens in a new tab)

No sign-in needed.

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

How it’s rated

Quality 43Fair quality (C) · 43 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 5/100 (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 A1000 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.	5.9 / 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	5.9 / 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 A1000 Laptop GPU

Quant	Memory needed	Available	Speed	Runs	Quality	Download
`Q2_K`	11.7 GB	4.0 GB	—	Won't run	43Fair quality (C) · 43 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 5/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q3_K_M`	13.9 GB	4.0 GB	—	Won't run	52Fair quality (C) · 52 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.	GGUF (opens in a new tab)
`Q4_K_M`	16.8 GB	4.0 GB	—	Won't run	58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 7/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q5_K_M`	19.2 GB	4.0 GB	—	Won't run	60Good quality (B) · 60 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.	GGUF (opens in a new tab)
`Q6_K`	21.8 GB	4.0 GB	—	Won't run	61Good quality (B) · 61 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.	GGUF (opens in a new tab)
`Q8_0`	27.6 GB	4.0 GB	—	Won't run	62Good quality (B) · 62 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.	GGUF files (opens in a new tab)
`F16`	50.2 GB	4.0 GB	—	Won't run	62Good quality (B) · 62 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

61Good quality (B) · 61 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5090 Q6_K · 63.6 tok/s · Runs great
60Good quality (B) · 60 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4090 Q5_K_M · 42.6 tok/s · Runs great
60Good quality (B) · 60 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 3090 Q5_K_M · 39.5 tok/s · Runs great
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 7900 XTX Q4_K_M · 42.3 tok/s · Runs great
52Fair quality (C) · 52 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4070 Ti SUPER Q3_K_M · 44.4 tok/s · Runs well (tight fit)
52Fair quality (C) · 52 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4080 SUPER Q3_K_M · 48.6 tok/s · Runs well (tight fit)

Models that do run on the NVIDIA RTX A1000 Laptop GPU

64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Nemotron Labs Dory 1.0 4B Q4_K_M · 69.1 tok/s
62Good quality (B) · 62 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4B Q4_K_M · 66.9 tok/s
59Good quality (B) · 59 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM5 2B Q6_K · 75.7 tok/s
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E2B Q4_K_M · 120 tok/s
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 4B Q4_K_M · 59.0 tok/s

Quick answers

How much memory does Dolphin Mistral 24B Venice Edition need on the NVIDIA RTX A1000 Laptop GPU 4GB?

Even at Q2_K it needs about 11.7 GB; the NVIDIA RTX A1000 Laptop GPU 4GB has 4.0 GB usable.

What can the NVIDIA RTX A1000 Laptop GPU 4GB run instead?

Nemotron Labs Dory 1.0 4B, Spark-X2.6 4B and MiniCPM5 2B run best on it; the page lists more, each with its speed.

What hardware can run Dolphin Mistral 24B Venice Edition?

RTX 5090 32GB, RTX 4090 24GB and RTX 3090 24GB 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.