Comprehensive side-by-side LLM comparison
Llama 3.1 70B Instruct leads with 1.2% higher average benchmark score. Llama 3.1 70B Instruct offers 224.0K more tokens in context window than Phi 4. Both models have similar pricing. Llama 3.1 70B Instruct is available on 9 providers. Both models have their strengths depending on your specific coding needs.
Meta
Llama 3.1 70B was created as a balanced open-source model, designed to provide strong performance with 70 billion parameters while remaining practical for many deployment scenarios. Built to serve as a versatile foundation for fine-tuning and application development, it combines capability with accessibility in the open-source ecosystem.
Microsoft
Phi-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
4 months newer

Llama 3.1 70B Instruct
Meta
2024-07-23

Phi 4
Microsoft
2024-12-12
Cost per million tokens (USD)

Llama 3.1 70B Instruct

Phi 4
Context window and performance specifications
Average performance across 6 common benchmarks

Llama 3.1 70B Instruct

Phi 4
Phi 4
2024-06-01
Available providers and their performance metrics

Llama 3.1 70B Instruct
Bedrock
Cerebras
DeepInfra
Fireworks
Groq

Llama 3.1 70B Instruct

Phi 4

Llama 3.1 70B Instruct

Phi 4
Hyperbolic
Lambda
Sambanova
Together

Phi 4
DeepInfra