bert-large-cased-finetuned-conll03-english
by dbmdz
334M params · token-classification · 95 likes · 1.4M downloads
bert-large-cased-finetuned-conll03-english is a 334M parameter model. At Q4 quantization it requires 0GB of VRAM. It runs comfortably on GeForce RTX 4090 (3935 tok/s), GeForce RTX 5090 (5902 tok/s), M4 Max 128GB (1440 tok/s).
Inference providers
| Provider | $/1M in | $/1M out | Throughput |
|---|---|---|---|
| HF Inference |
GPU compatibility
| GPU | VRAM | Q4 Decode | Verdict |
|---|---|---|---|
| GeForce RTX 4090 | 24GB | 3935 tok/s | comfortable |
| GeForce RTX 5090 | 32GB | 5902 tok/s | comfortable |
| M4 Max 128GB | 128GB | 1440 tok/s | comfortable |
| M4 Pro 48GB | 48GB | 720 tok/s | comfortable |
| M4 Pro 24GB | 24GB | 720 tok/s | comfortable |
| A100 PCIe 80 GB | 80GB | 7211 tok/s | comfortable |
| H100 SXM5 80 GB | 80GB | 14504 tok/s | comfortable |
| GeForce RTX 3090 | 24GB | 3480 tok/s | comfortable |
| Radeon RX 7900 XTX | 24GB | 2877 tok/s | comfortable |
| GeForce RTX 4080 | 16GB | 2793 tok/s | comfortable |