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Which language model works best for your prompt? What are the biases inherent in each? Compare the latest models from Google, Deepseek, OpenAI, Mistral, Meta, OpenAI and Anthropic with more LLMs being added each month. If you are looking for local language models we now also host Sarvam and SEA-LION!
Run
5d ago
Examples
API
Β product
product
string
Template variable
βοΈ Settings
Avoid Repetition
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 3.7 Sonnet (Anthropic) + 1Cr for DeepSeek R1 + 1Cr for Gemini 2 Flash (Google) + 1Cr for GPT-4o (openai) + 1Cr for Llama 3.2 90B + Vision (Meta AI) + 1Cr for Mistral Large 24/11 + 1Cr/run
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GPT-4.5 (openai)
GPT-4o (openai)
DeepSeek R1
Llama 3.3 70B
Mistral Large 24/11
Gemini 2 Flash (Google)
Claude 3.7 Sonnet (Anthropic)
Generated in 17.8s onΒ
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