Model comparison
SmolLM2-135M vs ced-base
These two publish different quantization sets; the table below has the exact sizes.
From the file· summed bytes, KV per layer
Side by side
| SmolLM2-135M | ced-base | |
|---|---|---|
| Parameters | 135M | 86M |
| Architecture | llama | ced |
| Layers | 30 | — |
| Native context | 8,192 | — |
| Mixture of experts | no | no |
| Quantizations published | 4 | 3 |
| Smallest quantization | 0.10 GiB | 0.12 GiB |
| Q4_K_M | 0.10 GiB | — |
| Licence | creativeml-openrail-m | apache-2.0 |
KV cache by context
the term that decides long-context viability
| Context | SmolLM2-135M | ced-base | 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 | — | — |