Nomic Embed Text v1.5 vs BGE Small EN v1.5
Side-by-side comparison of hardware requirements, quantization options, and specifications to help you choose the right model for your device.
Specifications Comparison
| Spec | Nomic Embed Text v1.5 | BGE Small EN v1.5 |
|---|---|---|
| Parameters | 0.137B | 0.033B |
| Architecture | nomic-bert | bert |
| License | Apache 2.0 | MIT |
| Context Length | 8K tokens | 1K tokens |
| Category | Embedding | Embedding |
| Author | Nomic AI | BAAI |
| HF Downloads | 10.9M | 17.0M |
| VRAM Range | 0.3 - 0.76 GB | 0.1 - 0.1 GB |
| Quantizations | 2 options | 1 options |
| Best Quality Score | 100% | 90% |
Quantization Options
Nomic Embed Text v1.5
Q8_0
0.1 GB0.3 GB VRAM98% quality
FP16
0.3 GB0.76 GB VRAM100% quality
BGE Small EN v1.5
Q8_0
0.0 GB0.1 GB VRAM90% quality
Which Should You Choose?
BGE Small EN v1.5 is more memory-efficient, starting at just 0.1GB VRAM compared to 0.3GB for Nomic Embed Text v1.5. Nomic Embed Text v1.5 offers more quantization options (2 vs 1), giving you more flexibility to balance quality and performance. Nomic Embed Text v1.5 is significantly larger at 0.137B parameters, which generally means better output quality but requires more hardware.