KIEFERSA/Sophea-Titan-1

VISIONConcurrent Unit Cost:2Model Size:27BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 12, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

KIEFERSA/Sophea-Titan-1 is a 27 billion parameter multimodal chat model developed by Kiefer SA, fine-tuned from Qwen3.6-27B. It specializes in Greek conversational AI with register control and a fixed assistant identity, while retaining strong English language and vision capabilities. This model achieves a general Greek benchmark score of 0.7369 and an English retention score of 0.8783, making it suitable for general-purpose Greek chat and knowledge-based QA.

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Overview

Sophea-Titan-1 is a 27 billion parameter multimodal chat model developed by Kiefer SA, built upon the Qwen3.6-27B architecture. It is specifically fine-tuned for Greek conversational interactions, incorporating register control and a consistent assistant identity. Notably, it maintains strong English language proficiency and multimodal vision capabilities from its base model.

Key Capabilities

  • Primary Language: Optimized for Greek, offering general-purpose conversational assistance and knowledge-based QA.
  • Multimodal: Retains vision capabilities, allowing for image understanding and interaction.
  • Register Control: Supports formal and informal conversational registers in Greek.
  • Performance: Achieves a macro score of 0.7369 on general Greek benchmarks and 0.8783 for English retention, outperforming its base model and other comparable open-source Greek LLMs.
  • Non-Thinking Mode: Designed to operate optimally with enable_thinking=false in its chat template, which is crucial for maintaining Greek output quality.
  • Speculative Decoding: Includes a multi-token-prediction head for improved inference throughput with vLLM (version 0.23.0 or newer).

Good For

  • Applications requiring a robust Greek conversational AI.
  • Greek-language knowledge question-answering systems.
  • Multimodal applications where Greek language processing and image understanding are needed.
  • Developers looking for a performant Greek model that also retains strong English capabilities.