Which language model works best your prompt? Compare your text generations across multiple large language models (LLMs) like OpenAI's evolving and latest ChatGPT engines and others like Curie, Ada, Babbage.
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⚙️ Settings
Avoid Repetition
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The maximum number of tokens to generate in the completion. Increase to generate longer responses.
Higher values allow the LLM to take more risks. Try values larger than 1 for more creative applications or 0 to ensure that LLM gives the same answer when given the same user input.
How many answers should the copilot generate? Additional answer outputs increase the cost of each run.
Run cost = 7 credits
Breakdown: 1Cr for Claude 3.5 Sonnet (Anthropic) + 2Cr for Gemini 1.5 Pro (Google) + 1Cr for GPT-4o (openai) + 1Cr for Llama 3 70b (Meta AI) + 1Cr for Mixtral 8x7b Instruct v0.1 (Mistral) + 1Cr/run
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GPT-4o (openai)
Llama 3 70b (Meta AI)
Mixtral 8x7b Instruct v0.1 (Mistral)
Gemini 1.5 Pro (Google)
Claude 3.5 Sonnet (Anthropic)
Llama3 8B CPT SEA-LIONv2.1 Instruct (aisingapore)
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