What can you run on an 8GB graphics card?
With 8GB VRAM you can run 16 of the 66 open-source models we track, up to 9.7B parameters, using each model's Q4 file where one is published and otherwise the smallest file that is. The most downloaded that fits is MiniCPM5-2B, needing 2.3 GB.
Typical machines: RTX 5060 · RTX 4060 · RTX 3070 · RX 7600. We hold back up to 1.5GB of the card for the display, leaving 7.7 GB for a model.
8GB VRAM 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 8GB VRAM 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 GBTight | 87,218 |
| Ornith-1.5-9BDeepReinforce | 9.7B | 6.9 GBTight | 462,696 |
| MiMo-V2.6-Distill-Qwen-9BXiaomi | 9.4B | 7.0 GBTight | 19,920 |
Sorted by memory, smallest first. Click any column to change it.
Step up to 12GB VRAM and 1 more model come within reach
Including granite-switch-4.1-8b (8.8B).
See everything 12GB VRAM runs →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.