Tristepin/ue3ornith1
VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 21, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
Tristepin/ue3ornith1 is a 9 billion parameter Qwen3.5-based causal language model developed by Tristepin, fine-tuned from ornith-ai/Ornith-1.5-9B. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It offers a 32768 token context length, making it suitable for tasks requiring extensive contextual understanding.
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Model Overview
Tristepin/ue3ornith1 is a 9 billion parameter language model developed by Tristepin. It is a fine-tuned variant of the ornith-ai/Ornith-1.5-9B model, built upon the Qwen3.5 architecture. A key characteristic of this model is its optimized training process, which utilized Unsloth and Huggingface's TRL library to achieve a 2x speedup in training.
Key Capabilities
- Efficient Training: Benefits from accelerated training methods, indicating potential for rapid iteration and deployment.
- Qwen3.5 Architecture: Leverages the capabilities of the Qwen3.5 base model.
- Extended Context Window: Supports a context length of 32768 tokens, enabling processing of longer inputs and maintaining coherence over extended conversations or documents.
Good For
- Applications requiring a 9 billion parameter model with a substantial context window.
- Use cases where efficient fine-tuning is a priority, given its optimized training methodology.
- Tasks that can benefit from the underlying Qwen3.5 architecture's general language understanding and generation capabilities.