Comprehensive side-by-side LLM comparison
Llama 3.1 8B Instruct leads with 2.0% higher average benchmark score. Llama 3.1 8B Instruct offers 6.1K more tokens in context window than Phi-3.5-mini-instruct. Both models have similar pricing. Llama 3.1 8B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
Meta
Llama 3.1 8B was developed as an efficient open-source model, designed to bring capable instruction-following to applications with limited computational resources. Built with 8 billion parameters, it provides a lightweight option for developers seeking reliable performance without the overhead of larger models.
Microsoft
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
1 month newer

Llama 3.1 8B Instruct
Meta
2024-07-23

Phi-3.5-mini-instruct
Microsoft
2024-08-23
Cost per million tokens (USD)

Llama 3.1 8B Instruct

Phi-3.5-mini-instruct
Context window and performance specifications
Average performance across 5 common benchmarks

Llama 3.1 8B Instruct

Phi-3.5-mini-instruct
Llama 3.1 8B Instruct
2023-12-31
Available providers and their performance metrics

Llama 3.1 8B Instruct
Bedrock
Cerebras
DeepInfra
Fireworks
Groq

Llama 3.1 8B Instruct

Phi-3.5-mini-instruct

Llama 3.1 8B Instruct

Phi-3.5-mini-instruct
Hyperbolic
Lambda
Sambanova
Together

Phi-3.5-mini-instruct
Azure