flywheel-ai/automotive

TEXT GENERATIONConcurrent Unit Cost:3Model Size:35.1BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 21, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The flywheel-ai/automotive model is a 35.1 billion parameter language model developed by Flywheel by OpSpot, fine-tuned from Qwen/Qwen3.6-35B-A3B. This model is specifically optimized as a vertical AI-employee for the automotive domain, excelling in tasks and knowledge related to this specialized industry. It features a 32768 token context length and is available in safetensors and GGUF formats for various deployment environments.

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Overview

The flywheel-ai/automotive model is a specialized 35.1 billion parameter language model developed by Flywheel by OpSpot. It is fine-tuned (LoRA) from the Qwen/Qwen3.6-35B-A3B base model, which is licensed under Apache-2.0. This model is designed as a "vertical AI-employee" specifically for the automotive domain, making it highly proficient in industry-specific tasks and knowledge.

Key Capabilities

  • Automotive Domain Expertise: Optimized for tasks and queries within the automotive industry.
  • Base Model Performance: On general prompts, it performs comparably to its Qwen3.6 base model.
  • Synthetic Data Training: Initial training utilized synthetic seed data generated by permissively-licensed local models (Apache/MIT teachers), avoiding distillation from closed models.
  • Flexible Formats: Available in safetensors for transformers and vLLM, and model-q4_k_m.gguf for llama.cpp and Ollama.

Good For

  • Applications requiring deep knowledge and processing within the automotive sector.
  • Developers looking for a specialized model with a strong base architecture.
  • Deployment with llama.cpp, Ollama, or vLLM due to provided format options.

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1 models