Resources 🧰
Available Models
Learn about the available models in Prem.
Here’s a list of the available models:
Name | Description |
---|---|
claude-3.5-haiku | Fast, efficient Anthropic model for everyday tasks. Good at concise responses and basic reasoning. |
claude-3.5-sonnet | Balanced Anthropic model with strong reasoning and creative capabilities. |
claude-3.7-sonnet | Advanced Anthropic model with superior reasoning and instruction-following abilities. |
deepseek-r1 | Code-specialized model with strong programming and technical reasoning capabilities. |
gemma3-1b | Compact Google model for efficient, lightweight applications. |
gemma3-4b | Balanced Google model offering good performance for general tasks at moderate size. |
gpt-4o | OpenAI’s multimodal model with strong reasoning and creative capabilities. |
gpt-4o-mini | Smaller, faster version of GPT-4o for everyday tasks and applications. |
llama3.1-8b | Mid-sized Meta model balancing performance and resource efficiency. |
llama3.2-1b | Compact Meta model for lightweight applications with minimal resource needs. |
llama3.2-3b | Balanced Meta model for general-purpose tasks with reasonable resource requirements. |
llama3.2-3b Exp2 | Experimental version of llama3.2-3b with optimized performance. |
llama3.3-70b-instruct | Large instruction-tuned Meta model with advanced reasoning capabilities. |
nova-lite | Lighter version of Anthropic’s Nova model for everyday tasks. |
nova-micro | Most compact Nova model optimized for speed and efficiency. |
nova-pro | Premium Anthropic Nova model with advanced capabilities for complex tasks. |
qwen2.5-0.5b | Ultra-compact Alibaba model for extremely lightweight applications. |
qwen2.5-1.5b | Compact Alibaba model balancing efficiency and basic capabilities. |
qwen2.5-3b | Mid-sized Alibaba model with good performance for everyday tasks. |
qwen2.5-3b Exp1 | Experimental version of qwen2.5-3b with performance enhancements. |
qwen2.5-7b | Larger Alibaba model with enhanced reasoning and generation capabilities. |
qwen2.5-7b Exp4 | Experimental version of qwen2.5-7b with advanced optimizations. |
smollm-1.7b | Efficient small model optimized for resource-constrained environments. |
smollm-135m | Tiny model for basic tasks with minimal computational requirements. |
smollm-360m | Very small model balancing capability and extreme efficiency. |