jina-reranker-v2 (300M) has 0.3 billion parameters. At standard 4-bit quantization with 8K context, it needs roughly 2.2 GB of VRAM — weights plus cache and runtime overhead.
VRAM by quantization
| Precision | Weights | Cache/Buffer | Total VRAM |
|---|---|---|---|
| 2-bit (IQ2_XXS) | 0.1 GB | 0.0 GB | 2.1 GB |
| 4-bit (Q4_K_M) | 0.2 GB | 0.0 GB | 2.2 GB |
| 8-bit (Q8_0) | 0.3 GB | 0.0 GB | 2.4 GB |
| 16-bit (FP16) | 0.6 GB | 0.0 GB | 2.6 GB |
Which GPU can run jina-reranker-v2 (300M) (at 4-bit)?
| GPU class | VRAM | jina-reranker-v2 (300M) (2.2 GB) |
|---|---|---|
| 8 GB · RTX 5060 / 4060 | 8 GB | Fits |
| 12 GB · RTX 5070 / 3060 | 12 GB | Fits |
| 16 GB · RTX 5070 Ti / 4080 | 16 GB | Fits |
| 24 GB · RTX 4090 / 3090 | 24 GB | Fits |
| 32 GB · RTX 5090 | 32 GB | Fits |
| 48 GB · 2×24 / RTX 6000 Ada | 48 GB | Fits |
| 128 GB · M-series / RTX Spark | 128 GB | Fits |
Next-gen cross-encoder for verifying semantic match order.
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VRAM figures are reproducible estimates (weights + KV cache + overhead) and vary by runtime and quant format. Data current as of 2026-06-15.