Model comparison
DS-R1-Qwen3-8B-ArliAI-RpR-v4-Small vs HyperCLOVAX-SEED-Text-Instruct-1.5B
These two publish different quantization sets; the table below has the exact sizes.
From the file· summed bytes, KV per layer
Side by side
| DS-R1-Qwen3-8B-ArliAI-RpR-v4-Small | HyperCLOVAX-SEED-Text-Instruct-1.5B | |
|---|---|---|
| Parameters | 8.2B | 1.6B |
| Architecture | qwen3 | llama |
| Layers | 36 | — |
| Native context | 131,072 | — |
| Mixture of experts | no | no |
| Quantizations published | 26 | 1 |
| Smallest quantization | 1.97 GiB | 1.06 GiB |
| Q4_K_M | — | 1.06 GiB |
| Licence | apache-2.0 | other |
KV cache by context
the term that decides long-context viability
| Context | DS-R1-Qwen3-8B-ArliAI-RpR-v4-Small | HyperCLOVAX-SEED-Text-Instruct-1.5B | Ratio |
|---|---|---|---|
| 4,096 | 0.56 GiB | — | — |
| 8,192 | 1.13 GiB | — | — |
| 16,384 | 2.25 GiB | — | — |
| 32,768 | 4.50 GiB | — | — |
| 65,536 | 9.00 GiB | — | — |
| 131,072 | 18.00 GiB | — | — |