What can you run with 128GB of RAM?
With 128GB RAM you can run 37 of the 66 open-source models we track, up to 127B parameters, using each model's Q4 file where one is published and otherwise the smallest file that is. The most downloaded that fits is Qwen3.8-27B, needing 19 GB.
Typical machines: MacBook Pro M5 Max (128GB) · Mac Studio M5 Max (128GB) · Workstation desktops. We hold back 20% of RAM (2 to 4GB) for the operating system, leaving 133 GB for a model.
128GB RAM decides whether a model loads. How fast it answers depends on your machine's memory bandwidth, which differs between machines with the same amount of memory. Why bandwidth sets the speed →
Models that run on 128GB RAM in 2026
| Model↕ | Size↕ | Memory↑ | Downloads (30 days)↕ |
|---|---|---|---|
| MiniCPM-V-4.7-1BOpenBMB | 1.6B | 1.4 GBRuns well | 184,495 |
| K2-Horizon-0.9BMBZUAI Institute of Foundation Models | 1.1B | 1.4 GBRuns well | 13,425 |
| LFM3-1.7BLiquid AI | 1.7B | 1.8 GBRuns well | 15,885 |
| LFM3-VL-2BLiquid AI | 1.9B | 1.8 GBRuns well | 4,193 |
| MiniCPM5-2BOpenBMB | 2.5B | 2.3 GBRuns well | 1,180,516 |
| d1-3BLiquid AI | 3.1B | 2.5 GBRuns well | 31,374 |
| granite-4.2-3bIBM | 3.7B | 3.1 GBRuns well | 37,116 |
| Mage-VLMicrosoft | 4.7B | 3.9 GBRuns well | 7,645 |
| FrogNano-4B-2609Microsoft | 4.7B | 3.9 GBRuns well | 2,663 |
| K2-Horizon-3.7BMBZUAI Institute of Foundation Models | 5.1B | 4.3 GBRuns well | 24,267 |
| North-Micro-Vision-InstructCohere | 2.5B | 6.0 GBRuns well | 33,984 |
| Ling-3.0-tinyinclusionAI · MoE | 7.9B1.6B active | 6.2 GBRuns well | 13,391 |
| granite-4.2-8bIBM | 8.8B | 6.6 GBRuns well | 70,118 |
| K2-Horizon-7BMBZUAI Institute of Foundation Models | 9B | 6.8 GBRuns well | 87,218 |
| Ornith-1.5-9BDeepReinforce | 9.7B | 6.9 GBRuns well | 462,696 |
| MiMo-V2.6-Distill-Qwen-9BXiaomi | 9.4B | 7.0 GBRuns well | 19,920 |
| granite-switch-4.1-8bIBM | 8.8B | 7.8 GBRuns well | 3,734 |
| Qwen3.8-27BAlibaba / Qwen | 28B | 19 GBRuns well | 7,509,924 |
| Hy-Memory-30B-A3BTencent · MoE | 30B3B active | 20 GBRuns well | 5,468 |
| granite-4.2-30bIBM | 29B | 21 GBRuns well | 36,633 |
| Muse-Glimmer-30BMeta AI | 30B | 21 GBRuns well | 202,402 |
| Xing4.0-29B-A4BChina Telecom AI (TeleAI) · MoE | 31B4B active | 23 GBRuns well | 7,749 |
| MiniCPM-V-4.7-35B-A3BOpenBMB · MoE | 35B3B active | 24 GBRuns well | 334,870 |
| Nex-N2.5-miniNex-AGI · MoE | 35B7B active | 24 GBRuns well | 3,200 |
| Ornith-1.5-35B-A3BDeepReinforce · MoE | 36B3B active | 24 GBRuns well | 268,879 |
| granite-switch-4.1-30bIBM | 30B | 24 GBRuns well | 2,759 |
| K2-Horizon-32BMBZUAI Institute of Foundation Models | 35B | 25 GBRuns well | 6,150 |
| K2-Horizon-MoVA-36B-A4BMBZUAI Institute of Foundation Models · MoE | 37B4B active | 25 GBRuns well | 12,840 |
| NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16NVIDIA · MoE | 32B3B active | 28 GBRuns well | 1,117,157 |
| NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GBNVIDIA · MoE | 74B9B active | 29 GBRuns well | 12,123 |
| Bonsai-27B-unpackedPrismML | 27B | 59 GBRuns well | 13,075 |
| Ternary-Bonsai-27B-unpackedPrismML | 27B | 59 GBRuns well | 651 |
| Ornith-1.5-122BDeepReinforce · MoE | 125B25B active | 79 GBRuns well | 105,803 |
| Ling-3.0-flash-FininclusionAI · MoE | 127B25B active | 84 GBRuns well | 1,976 |
| Ling-3.0-flash-VLinclusionAI · MoE | 125B25B active | 85 GBRuns well | 11,564 |
| Laguna-S-2.1Poolside · MoE | 118B24B active | 100 GBRuns well | 619,054 |
| Ling-3.0-flash-SanteinclusionAI · MoE | 127B25B active | 117 GBTight | 1,075 |
Sorted by memory, smallest first. Click any column to change it.
All figures at Q4_K_M quantization and 4K context. “Memory” is the model's download size from Hugging Face, plus its context cache calculated from the model's configuration, plus a runtime allowance of 10% of the model (at least 0.5GB, at most 3GB). How this is calculated
Image generators that also fit
These make pictures rather than text. Their memory use scales with the resolution you generate at, not conversation length, so treat these figures as a floor rather than a ceiling.
What you'd need more memory for
The next models up, and what they ask for.