Verified lossless (this FP8 build)
Measured on this checkpoint through the vLLM decode path (greedy, non-thinking), vs the bf16 base:
Every axis is within measurement noise of bf16 → lossless. FP8 also loads in HF transformers.
Per-benchmark detail (measured on this FP8 build)
General Greek benchmarks (9, accuracy)
English retention — 5 benchmarks (accuracy)
greekmmlu — per-subject (accuracy)
Usage
Serve with vLLM (compressed-tensors FP8 auto-detected; Cutlass FP8 kernels on Blackwell/Hopper):
vllm serve KIEFERSA/Sophea-Titan-1-FP8 --served-model-name sophea-titan-1-fp8 --trust-remote-code \
--enable-auto-tool-choice --tool-call-parser qwen3_coder \
--reasoning-parser qwen3
Recommended sampling (instruct / non-thinking): temperature=0.7, top_p=0.80, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0.
from openai import OpenAI
client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
resp = client.chat.completions.create(
model="sophea-titan-1-fp8",
messages=[{"role": "user", "content": "Ποια είναι η πρωτεύουσα της Ελλάδας;"}],
temperature=0,
extra_body={"chat_template_kwargs": {"enable_thinking": False}},
)
print(resp.choices[0].message.content)
License
Inherits the Qwen3.6-27B base-model license. Verify base-model terms before use.