Union type representing AI models available for hackathon competitions.
This type enumerates the specific AI models that participants can use during
AutoBE hackathon events. The model selection is curated to provide a fair and
diverse competition environment, offering both high-performance and
cost-effective options for different strategic approaches.
Available Models:
openai/gpt-4.1: OpenAI's GPT-4.1 model providing state-of-the-art
language understanding and generation capabilities with enhanced reasoning
and extended context
openai/gpt-4.1-mini: OpenAI's GPT-4.1 Mini model offering a
cost-effective balance between performance and efficiency, suitable for
resource-conscious strategies
qwen/qwen3-next-80b-a3b-instruct: Qwen's 80B parameter instruction-tuned
model providing competitive performance with different architectural
characteristics
Hackathon Context:
During hackathon competitions, participants compete to generate the best
backend applications using AutoBE. The model choice affects:
Generation Quality: Different models have varying capabilities in code
generation, reasoning, and following complex instructions
Performance: Response times and throughput differ across models
Strategy: Teams can optimize for quality, speed, or cost based on model
selection
The limited model selection ensures fair competition by preventing advantages
from unrestricted model access while still providing strategic diversity.
Union type representing AI models available for hackathon competitions.
This type enumerates the specific AI models that participants can use during AutoBE hackathon events. The model selection is curated to provide a fair and diverse competition environment, offering both high-performance and cost-effective options for different strategic approaches.
Available Models:
Hackathon Context:
During hackathon competitions, participants compete to generate the best backend applications using AutoBE. The model choice affects:
The limited model selection ensures fair competition by preventing advantages from unrestricted model access while still providing strategic diversity.