nomic-embed-text v1.5 on NVIDIA GeForce RTX 4060 8GB
Yes — RTX 4060 8GB runs nomic-embed-text v1.5 excellently at Q8_0 — 4200 tok/s. 8 GB VRAM with plenty of headroom.
Model Size
137M
Device VRAM
8 GB
Bandwidth
272 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for nomic-embed-text v1.5 on NVIDIA GeForce RTX 4060 8GB at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 4200 tok/s | 8ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
137M embedding model. Q8_0 0.4GB. Can run concurrently with any LLM.
About nomic-embed-text v1.5
nomic-embed-text v1.5 (137M) is a embeddings, ai building model. High-quality text embedding model for RAG pipelines. 137M params, negligible VRAM. Competitive with OpenAI's ada-002 on MTEB benchmarks. Essential for builders running local RAG with Cursor or similar tools. Can run concurrently with coding models without meaningful VRAM impact.
View all nomic-embed-text v1.5 hardware options →About NVIDIA GeForce RTX 4060 8GB
NVIDIA GeForce RTX 4060 8GB has 8 GB at 272 GB/s. Street price: $289.
See all models NVIDIA GeForce RTX 4060 8GB can run →Estimate method: Performance estimates based on model size and device bandwidth. Reference hardware source: github.com (2026-03-15)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.