migtissera/Synthia-4-27B

VISIONPricing:Input $1.6 / Cached $0.15 / Output $12Concurrent Unit Cost:2Model Size:27BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 16, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

Synthia-4-27B by migtissera is a 27 billion parameter personal AI model based on Qwen/Qwen3.8-27B, designed for expressive, conversational interaction and practical tool use. It is post-trained on long-form agent sessions up to 65,536 tokens, focusing on developing a working relationship across tasks. This model excels at maintaining a stable personality and assisting with coding, research, planning, and creative work, integrating conversation with task execution.

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Synthia-4-27B: A Personal AI for Conversational Agentic Work

Synthia-4-27B is a 27 billion parameter model developed by migtissera, built upon the Qwen/Qwen3.8-27B base. It is specifically fine-tuned for use as a personal AI agent, emphasizing expressive conversation, tool utilization, and persistence across long sessions. The model's training involved complete, long-form agent sessions up to 65,536 tokens, teaching it to manage complex tasks and maintain a consistent persona.

Key Capabilities

  • Stable Voice and Personality: Maintains a consistent character, including appropriate humor, across extended interactions.
  • Seamless Task Execution: Transitions smoothly between open conversation and executing tasks, including tool calls.
  • Agentic Workflow: Designed for multi-step tasks, preserving goals and constraints, and revising plans based on tool results.
  • Multimodal Support: Retains the base Qwen model's image and video input capabilities, along with a 262,144-token native context window.
  • Reasoning Control: Supports varying reasoning effort levels (xhigh, medium, low) through its bundled chat template.

Good For

  • Persistent Personal AI: Ideal for stateful agent runtimes requiring continuous interaction and memory.
  • Daily Assistance: Suitable for planning, decision support, writing, and creative collaboration.
  • Technical Work: Excels in long-running research, repository exploration, implementation, debugging, and verification.
  • Tool-Driven Workflows: Optimized for structured function definitions and tool-assisted problem-solving.
  • Image-Assisted Analysis: Capable of engaging in conversations and analysis with image inputs.

Finetunes
2 models