What LLMs fit in 48GB VRAM? (Oct 2026)
34 models on our list fit in 48 GB of graphics memory. The largest by parameter count is Ornith-1.5-122B at UD-Q2_K_XL, 45.53 GB (measured weights; total is an estimate). We keep 0.6 GB free on one graphics card, so 47.4 GB is usable. Each total adds conversation memory for 8,192 tokens (or the model's own maximum, when that is shorter) and 0.8 GB for the software. The total is an estimate.
Updated
Own a 48 GB GPU? Get a 1-line alert when a new top model fits 47.4 GB usable VRAM
34 models on our catalog fit 48 GB today. Get our weekly 1-line alert when a new open-weight LLM lands inside 47.4 GB at Q4_K_M or when 48 GB+ GPU prices drop >10% — zero spam.
Models that fit
Ranked by parameter count, largest first. The best quant is the highest-quality option that fits in 47.4 GB. A measured download is used when we have one. Otherwise the figure is Q4, Q5, Q8 or FP16 from our estimate. The gigabytes are the weights plus conversation memory for 8,192 tokens, or the model's shorter maximum, plus 0.8 GB for the software. The total is an estimate.
| Rank | AI model | Parameters | Best quant | GB | Label |
|---|---|---|---|---|---|
| 1 | Can I run Ornith-1.5-122B? | 125.09B | UD-Q2_K_XL | 45.53 GB | measured weights; total is an estimate |
| 2 | Can I run NVIDIA Nemotron 3.5 Super VL? | 120B (estimate), 12B active | UD-IQ1_M | 47.01 GB | measured weights; total is an estimate |
| 3 | Can I run Laguna S 2.1? | 118B (estimate), 8B active | UD-IQ2_M | 38.55 GB | measured weights; total is an estimate |
| 4 | Can I run Llama 4 Scout? | 108.64B (estimate), 17B active | UD-Q2_K_XL | 44.79 GB | measured weights; total is an estimate |
| 5 | Can I run Kolibri-1? | 78.1B (estimate), 3.46B active | IQ4_XS | 44.64 GB | measured weights; total is an estimate |
| 6 | Can I run NVIDIA Nemotron 3.5 Bolt 74B-A9B? | 74B (estimate), 9B active | Q4_K_M | 45.27 GB | estimate |
| 7 | Can I run DeepSeek-R1-Distill 70B? | 70.6B (estimate) | Q4_K_M | 45.84 GB | estimate |
| 8 | Can I run Llama 3.3 70B? | 70.6B (estimate) | Q4_K_M | 46.00 GB | measured weights; total is an estimate |
| 9 | Can I run Recursive Flint? | 39.79B, 2.5B active | Q8_0 | 43.42 GB | measured weights; total is an estimate |
| 10 | Can I run Qwen3.6-35B-A3B? | 35.95B (estimate), 3B active | Q8_0 | 37.87 GB | measured weights; total is an estimate |
| 11 | Can I run Nanbeige4.3-33B? | 33.12B (estimate) | Q8_0 | 37.74 GB | measured weights; total is an estimate |
| 12 | Can I run Qwen2.5 32B? | 32.8B (estimate) | Q8 | 38.04 GB | estimate |
| 13 | Can I run Qwen3 32B? | 32.76B (estimate) | Q8_0 | 37.77 GB | measured weights; total is an estimate |
| 14 | Can I run Gemma 4 31B? | 31.27B (estimate) | Q8_0 | 34.95 GB | measured weights; total is an estimate |
| 15 | Can I run Qwen3 Coder 30B A3B? | 30.53B (estimate), 3.3B active | Q8_0 | 34.09 GB | measured weights; total is an estimate |
| 16 | Can I run NVIDIA Nemotron 3.5 Lightning? | 30B (estimate), 3B active | Q8_0 | 34.44 GB | measured weights; total is an estimate |
| 17 | Can I run Muse Glimmer 30B? | 29.6B | Q8 | 32.66 GB | estimate |
| 18 | Can I run Qwen3.8-27B? | 27.78B (estimate) | Q8_0 | 30.39 GB | measured weights; total is an estimate |
| 19 | Can I run Gemma 3 27B? | 27.43B (estimate) | Q8_0 | 30.62 GB | measured weights; total is an estimate |
| 20 | Can I run Gemma 2 27B? | 27.2B (estimate) | Q8 | 32.22 GB | estimate |
| 21 | Can I run OrcaCyber Nano 1.0? | 27B | Q8 | 30.23 GB | estimate |
| 22 | Can I run Gemma 4 26B A4B? | 25.2B (estimate), 3.8B active | Q8_0 | 28.04 GB | measured weights; total is an estimate |
| 23 | Can I run Mistral Small 3.2 24B? | 24.01B (estimate) | Q8_0 | 27.19 GB | measured weights; total is an estimate |
| 24 | Can I run gpt-oss-20b? | 21B (estimate), 3.6B active | F16 | 14.79 GB | measured weights; total is an estimate |
| 25 | Can I run DeepSeek R1 Distill Qwen 14B? | 14.77B | F16 | 31.96 GB | measured weights; total is an estimate |
| 26 | Can I run Phi-4 14B? | 14.7B (estimate) | FP16 | 31.88 GB | estimate |
| 27 | Can I run Qwen2.5 14B? | 14.7B (estimate) | FP16 | 31.81 GB | estimate |
| 28 | Can I run Gemma 2 9B? | 9.24B (estimate) | FP16 | 21.39 GB | estimate |
| 29 | Can I run Llama 3.1 8B? | 8.03B (estimate) | FP16 | 17.93 GB | estimate |
| 30 | Can I run NVIDIA Nemotron 3.5 Bolt E4B? | 8B (estimate) | BF16 | 16.12 GB | measured weights; total is an estimate |
| 31 | Can I run Mistral 7B v0.3? | 7.25B (estimate) | FP16 | 16.37 GB | estimate |
| 32 | Can I run Spark-X2.6-4B? | 4.11B (estimate) | BF16 | 9.39 GB | measured weights; total is an estimate |
| 33 | Can I run Llama 3.2 3B? | 3.21B (estimate) | FP16 | 8.16 GB | estimate |
| 34 | Can I run LFM3-1.7B? | 1.73B (estimate) | BF16 | 4.38 GB | measured weights; total is an estimate |
Cards and Macs with 48 GB
No graphics card or Mac on our list has 48 GB.
Memory totals are our estimate, including when the weight file was measured. Prices are the euro figures we store, with the date they were written down. How we calculate
Common questions
- What is the largest model that fits in 48 GB of VRAM?
- Ornith-1.5-122B is the largest by parameter count, at UD-Q2_K_XL, 45.53 GB (measured weights; total is an estimate). 34 models on our list fit.
- What does the best quant mean for 48 GB?
- The best quant is the highest-quality option that still fits. A measured download is used when we have one at that quality. Otherwise the figure is Q4, Q5, Q8 or FP16 from our estimate. A higher bit count wins. A file that runs only on a Mac is not counted. The gigabytes add conversation memory and the software overhead, so the total is an estimate even when the weight file was measured.
- Which cards and Macs have 48 GB, and what do they cost in the EU?
- No graphics card or Mac on our list has 48 GB. The model table is still for one graphics card of that size.
- How much of 48 GB can a model use?
- Our estimate keeps 0.6 GB free on one graphics card, so 47.4 GB is usable. A Mac with 48 GB of shared memory does not give the graphics all of it. The model table is for one graphics card.