empero-ai
Qwythos 9B Claude Mythos 5 1M
Qwythos 9B Claude Mythos 5 1M is a 8.95B dense qwen35 model from empero-ai. Configured context length is 1,048,576 tokens. License: apache-2.0. Quant sizes are the GGUF file bytes published on Hugging Face when a file exists.
Parameters9.0B
Context1024K
Attentionhybrid
Licenseapache-2.0
32 layers · 4 KV heads · head dim 256 · 24 linear-attention layers · GGUF repo · config
Quant file sizes
| Quant | File size | Source |
|---|---|---|
| BF16 | 16.7 GB | Hugging Face file bytes |
| Q8_0 | 8.87 GB | Hugging Face file bytes |
| Q6_K | 6.85 GB | Hugging Face file bytes |
| Q5_K_M | 6.02 GB | Hugging Face file bytes |
| Q4_K_M | 5.24 GB | Hugging Face file bytes |
On common machines
| Device | Verdict | Quant | Speed |
|---|---|---|---|
| GeForce RTX 4060 Ti 8GB | Tight fit | Q5_K_M | 24–32 |
| GeForce RTX 3060 12GB | Tight fit | Q8_0 | 20–28 |
| GeForce RTX 4060 Ti 16GB | Runs | Q8_0 | 16–22 |
| GeForce RTX 4090 | Runs | BF16 | 30–42 |
| GeForce RTX 5090 | Runs great | BF16 | 54–74 |
| Apple M4 Pro | Tight fit | BF16 | 8.3–11 |
| Apple M5 | Tight fit | Q8_0 | 8.6–12 |
| CPU only · DDR5-5600 | Runs on CPU | BF16 | 2.7–3.7 |
Smallest devices that fit it fully
- GeForce RTX 5060 Ti 8GB — Tight fit, Q5_K_M, 37–50 tok/s
- GeForce RTX 5060 — Tight fit, Q5_K_M, 37–50 tok/s
- GeForce RTX 5050 — Tight fit, Q5_K_M, 26–36 tok/s
- GeForce RTX 4060 Ti 8GB — Tight fit, Q5_K_M, 24–32 tok/s
- GeForce RTX 4060 — Tight fit, Q5_K_M, 22–30 tok/s
- GeForce RTX 3070 Ti — Tight fit, Q5_K_M, 50–68 tok/s
Run it
Commands for the GeForce RTX 4060 Ti 16GB estimate (Q8_0).
llama.cpp
llama-server -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q8_0 -c 8192 -ngl 32
No matching name in the Ollama library snapshot.
LM Studio
lms get empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF # Then load quant Q8_0