nomic-embed-text v1.5 on Apple M3 Pro (18GB Unified)
Yes — M3 Pro (18GB Unified) handles nomic-embed-text v1.5 well at Q8_0 — 600 tok/s. Solid daily-driver performance on 18 GB VRAM.
Model Size
137M
Device VRAM
18 GB
Bandwidth
150 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for nomic-embed-text v1.5 on Apple M3 Pro (18GB Unified) at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 600 tok/s | 50ms | ✓ Yes | Good | estimated |
Notes
Q8_0
Embedding throughput limited by 150 GB/s. Good for RAG pipelines.
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 Apple M3 Pro (18GB Unified)
Apple M3 Pro (18GB Unified) has 18 GB at 150 GB/s. Available in MacBook Pro 14", MacBook Pro 16".
See all models Apple M3 Pro (18GB Unified) can run →Estimate method: MLX performance estimates. 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.