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Choose up to 4 models to see their file size, memory, license and third-party evaluations side by side.
Comparison table
| Item | Ornith-1.5-9B ornith-ai ✕ Remove | Huihui-Qwen3.6-35B-A3B-abliterated-MTP huihui-ai ✕ Remove |
|---|---|---|
| Parameters | 9.2B | 35.5B |
| Architecture | qwen35 | qwen35moe |
| Max context length | 262,144 | 262,144 |
| Representative quantization and size Measured | Q4_K_M · 5.78 GB | Q2_K · 13.2 GB |
| Memory at 8K Estimated | 7.17 GB | 14.5 GB |
| Memory at 32K Estimated | 7.98 GB | 15.0 GB |
| VRAM it fits (8K) Estimated | VRAM 8 GB+ | VRAM 16 GB+ |
| Smallest quantization (8K) Estimated | Q4_K_M · 5.78 GB → 7.17 GB | Q2_K · 13.2 GB → 14.5 GB |
| License | MIT License Commercial OK | Apache License 2.0 Commercial OK |
| llama.cpp support | llama.cpp b7990 and later | llama.cpp b7990 and later |
| Downloads (30 days, total) | 5,824,840 | 4,969,070 |
| Human preference (LMArena) | - | - |
| Capabilities (Epoch AI) | - | - |
| Hard science (GPQA) | - | - |
- The representative quantization is Q4_K_M (or the smallest one if missing) from the source with the most downloads. Memory is estimated with an f16 KV cache.
- Third-party evaluations are other organizations' values for the original model before quantization, not this site's rating (sources are on the ranking page).
- This site does not judge which model is better or give an overall score.