Best AI Models for 16 GB VRAM
The sweet spot — 14B at Q8, smaller models at full precision. Here are all 59 models you can run locally with 16 GB of memory.
Hardware with 16 GB Memory
AMD Radeon RX 6800 XTAMD Radeon RX 6900 XTAMD Radeon RX 7800 XTAMD Radeon RX 9060 XT 16GBAMD Radeon RX 9070AMD Radeon RX 9070 XTIntel Arc A770NVIDIA GeForce RTX 4060 Ti 16GBNVIDIA GeForce RTX 4070 Ti SuperNVIDIA GeForce RTX 4080NVIDIA GeForce RTX 4080 SuperNVIDIA GeForce RTX 5060 Ti 16GBNVIDIA GeForce RTX 5070 TiNVIDIA GeForce RTX 5080NVIDIA RTX A4000iMac M1 16GBiMac M4 16GBMac mini M1 16GBMac mini M4 16GBMacBook Air M2 16GBMacBook Air M3 16GBMacBook Air M4 16GBMacBook Air M5 16GBMacBook Pro M1 16GBMacBook Pro M2 Pro 16GBMacBook Pro M5 16GB
Runs Comfortably (55)
These models fit with room to spare for context window and OS overhead.
| Model | Params | Quantization | VRAM | Quality |
|---|---|---|---|---|
| Qwen 3.5 35B A3B | 35B | Q4_K_M | 12 GB | 4 |
| InternLM 2.5 20B | 20B | Q4_K_M | 12 GB | 4 |
| StarCoder2 15B | 15B | Q5_K_M | 12 GB | 4 |
| DeepSeek R1 14B | 14B | Q5_K_M | 11.3 GB | 4 |
| Phi-4 14B | 14B | Q5_K_M | 11.3 GB | 4 |
| Phi-4 Reasoning 14B | 14B | Q4_K_M | 11 GB | 4 |
| Qwen 2.5 14B | 14B | Q5_K_M | 11.3 GB | 4 |
| Qwen 2.5 Coder 14B | 14B | Q4_K_M | 12 GB | 4 |
| Qwen 3 14B | 14B | Q4_K_M | 12 GB | 4 |
| Gemma 3 12B | 12B | Q4_K_M | 10.5 GB | 4 |
| Mistral Nemo 12B | 12B | Q4_K_M | 9.5 GB | 4 |
| Falcon 3 10B | 10B | Q8_0 | 13 GB | 4 |
| Gemma 2 9B | 9B | Q8_0 | 11 GB | 4 |
| Qwen 3.5 9B | 9B | Q8_0 | 11.5 GB | 5 |
| Yi 1.5 9B | 9B | Q8_0 | 11 GB | 5 |
| Yi Coder 9B | 9B | Q8_0 | 12 GB | 5 |
| Aya Expanse 8B | 8B | Q8_0 | 10.5 GB | 5 |
| Cogito 8B | 8B | Q8_0 | 11 GB | 4 |
| DeepSeek R1 8B | 8B | Q8_0 | 11.5 GB | 4 |
| Dolphin 3 8B | 8B | Q8_0 | 10 GB | 5 |
| Granite 3.3 8B | 8B | Q8_0 | 10 GB | 4 |
| Llama 3.1 8B | 8B | Q8_0 | 10 GB | 4 |
| Nemotron 3 Nano 8B | 8B | Q8_0 | 11 GB | 4 |
| Nous Hermes 2 8B | 8B | Q8_0 | 10 GB | 5 |
| Qwen 3 8B | 8B | Q8_0 | 11.5 GB | 4 |
| Codestral Mamba 7B | 7B | Q8_0 | 9.9 GB | 5 |
| DeepSeek R1 7B | 7B | Q8_0 | 9 GB | 4 |
| Falcon 3 7B | 7B | Q8_0 | 10 GB | 4 |
| InternLM 2.5 7B | 7B | Q8_0 | 9 GB | 5 |
| Mistral 7B | 7B | Q8_0 | 9 GB | 4 |
| OpenChat 3.5 7B | 7B | Q8_0 | 9.9 GB | 5 |
| Qwen 2.5 7B | 7B | Q8_0 | 9 GB | 4 |
| Qwen 2.5 Coder 7B | 7B | Q8_0 | 9 GB | 4 |
| Qwen 2.5 VL 7B | 7B | Q8_0 | 10.5 GB | 4 |
| StarCoder2 7B | 7B | Q8_0 | 9 GB | 5 |
| WizardLM 2 7B | 7B | Q8_0 | 9.9 GB | 5 |
| Gemma 3 4B | 4B | F16 | 11.5 GB | 5 |
| Gemma 3n E4B | 4B | F16 | 11 GB | 5 |
| Gemma 4 E4B | 4B | Q8_0 | 10 GB | 5 |
| Qwen 3 4B | 4B | F16 | 11 GB | 5 |
| Qwen 3.5 4B | 4B | Q8_0 | 6.5 GB | 4 |
| Phi-3 Mini 3.8B | 3.8B | F16 | 9.6 GB | 5 |
| Phi-4 Mini 3.8B | 3.8B | F16 | 10.5 GB | 5 |
| Llama 3.2 3B | 3B | F16 | 8 GB | 5 |
| StarCoder2 3B | 3B | F16 | 8 GB | 5 |
| Gemma 2 2B | 2B | F16 | 6 GB | 5 |
| Gemma 3n E2B | 2B | F16 | 6.5 GB | 5 |
| Gemma 4 E2B | 2B | Q8_0 | 6 GB | 5 |
| Qwen 3.5 2B | 2B | Q8_0 | 4.5 GB | 4 |
| SmolLM2 1.7B | 1.7B | F16 | 4.4 GB | 5 |
| DeepSeek R1 1.5B | 1.5B | F16 | 5 GB | 5 |
| Gemma 3 1B | 1B | F16 | 3.5 GB | 5 |
| Llama 3.2 1B | 1B | F16 | 4 GB | 5 |
| Qwen 3.5 0.8B | 0.8B | Q8_0 | 2 GB | 4 |
| Qwen 3 0.6B | 0.6B | F16 | 3.3 GB | 5 |
Tight Fit (4)
These models run but with limited context window. Close other apps to free memory.
| Model | Params | Quantization | VRAM | Quality |
|---|---|---|---|---|
| Codestral 22B | 22B | Q4_K_M | 14.7 GB | 4 |
| gpt-oss 20B | 21B | MXFP4 | 15 GB | 4 |
| Llama 3.2 Vision 11B | 11B | Q8_0 | 14 GB | 4 |
| Yi 1.5 6B | 6B | F16 | 14 GB | 5 |
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