Model comparison
gliner2-base-v1 vs SmolLM2-135M-Instruct
These two publish different quantization sets; the table below has the exact sizes.
From the file· summed bytes, KV per layer
Side by side
| gliner2-base-v1 | SmolLM2-135M-Instruct | |
|---|---|---|
| Parameters | 208M | 135M |
| Architecture | deberta | llama |
| Layers | — | 30 |
| Native context | — | 8,192 |
| Mixture of experts | no | no |
| Quantizations published | 1 | 41 |
| Smallest quantization | 0.13 GiB | 0.08 GiB |
| Q4_K_M | — | 0.10 GiB |
| Licence | — | apache-2.0 |
KV cache by context
the term that decides long-context viability
| Context | gliner2-base-v1 | SmolLM2-135M-Instruct | Ratio |
|---|---|---|---|
| 4,096 | — | 0.09 GiB | — |
| 8,192 | — | 0.18 GiB | — |
| 16,384 | — | 0.35 GiB | — |
| 32,768 | — | 0.70 GiB | — |
| 65,536 | — | 1.41 GiB | — |
| 131,072 | — | 2.81 GiB | — |