§01·spec · /gpus
RTX 4060 Ti 8GB
nvidia40 series8GB VRAM
13 open-weights AI models run on the RTX 4060 Ti 8GB — see which fit, how fast they go, and the VRAM each needs.
§02·models that run on this GPU
13 totalLLM · 3
| Model | Best speed | Min VRAM | Works | Evidence | |
|---|---|---|---|---|---|
| Nanbeige4.2 3B | 8GB | ✓ | recipe | check ↗ | |
| Ornith 1.0 9B | 8GB | ✓ | recipe | check ↗ | |
| Qwen3-4B | 4GB | ✓ | recipe | check ↗ |
Multimodal · 3
| Model | Best speed | Min VRAM | Works | Evidence | |
|---|---|---|---|---|---|
| Fara1.5-4B | 8GB | ✓ | recipe | check ↗ | |
| Gemma 4 E4B-IT | 6GB | ✓ | recipe | check ↗ | |
| MiniMind-O | 4GB | ✓ | recipe | check ↗ |
Image · 1
| Model | Best speed | Min VRAM | Works | Evidence | |
|---|---|---|---|---|---|
| Qwen-Image-2.1 | 8GB | ✓ | recipe | check ↗ |
TTS · 4
Music · 1
| Model | Best speed | Min VRAM | Works | Evidence | |
|---|---|---|---|---|---|
| Foundation-1 | 8GB | ✓ | recipe | check ↗ |
§03·tested recipes
showing 6 of 13- imageintermediate8GB+recipe
Qwen-Image-2.1 on RTX 4060 Ti 8GB: What Fits, What Streams per Step, Which 4-Bit DiTs Run
- llmintermediate8GB+recipe
Nanbeige4.2-3B on RTX 4060 Ti 8GB: an 8 GB Budget for 65,536 New Tokens
- multimodaladvanced8GB+recipe
Fara1.5-4B on RTX 4060 Ti 8GB: Local Browser Computer-Use Agent with llama.cpp
- llmintermediate8GB+recipe
Ornith 1.0 9B on RTX 4060 Ti 8GB: Local Agentic Coding at the Fit Boundary via llama.cpp + OpenHands
- multimodalbeginner6GB+recipe
Gemma 4 E4B on RTX 4060 Ti 8GB: Multimodal Inference via Q4_K_M GGUF (llama.cpp or Ollama)
- specializedbeginner4GB+recipe
SAM 3 on RTX 4060 Ti 8GB: Promptable Image and Video Segmentation