Ornith-1.0-9B
2recorded runs
52.5best tok/s
2verified
What the Ornith-1.0-9B numbers mean
The fastest verified result on our board is 52.5 output tok/s on an RTX 3060 at Q4_K_M with a 32768-token context. That is about 19.1 ms per generated token — 500 tokens takes roughly 9.5 seconds. Prompt processing on the same record runs at 1457.6 tok/s, so a 2,000-token prompt is read in about 1.4 seconds. Peak VRAM was measured at 5.7 GB. Across the 2 records we hold for this model the range is 31.2–52.5 tok/s on 2 GPUs, because quantisation, context length and the engine build all move the number.
How much VRAM does Ornith-1.0-9B need?
Ornith-1.0-9B has 9.0B parameters. These estimates use the same formula as the VRAM calculator: weights, plus about 15% for a moderate-context KV cache and runtime overhead, plus a small engine floor.
| Quantisation | Estimated VRAM | Smallest card that fits |
|---|---|---|
| Q4_K_M (4-bit) | 6.6 GB | 8 GB |
| Q8_0 (8-bit) | 11.8 GB | 16 GB |
| FP16 (16-bit) | 21.5 GB | 32 GB |
Fastest GPUs for this model (best tok/s)
- RTX 306052.5
- Radeon AI Pro R9700 x331.2
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| Carnice-9b | 9B | 5.1 GB |
| DeepSeek-V4-Pro-Qwen3.5-9B-MTP | 9B | 5.1 GB |
| Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-i1 | 9B | 5.1 GB |
| NVIDIA-Nemotron-Nano-9B-v2 | 9B | 5.1 GB |
| Qwen3-VL-8B-Instruct | 9B | 5.1 GB |
| Qwen3.5-9B-MTP | 9B | 5.1 GB |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| RTX 3060 · 12 GB | Ornith-1.0-9B | Q4_K_M | llama.cpp b10443 | 32768 | 52.5 ✓ | 1457.6 | 5.7 | src |
| Radeon AI Pro R9700 x3 · 32 GB | Ornith-1.0-9B | BF16 | llama.cpp b10107 | 787 | 31.2 ✓ | 1631.6 | 25.8 | src |