Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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Phi-3.5 Mini

Ollama

Intelligence Score 65/100
Model Popularity 0 votes
Context Window 128K tokens
Pricing Model Free / Open

Llama 3 8B Instruct

BentoML

Intelligence Score 71/100
Context Window 8K
Pricing Model Commercial / Paid
Model Popularity 0 votes
FINAL VERDICT

Llama 3 8B Instruct Wins

With an intelligence score of 71/100 vs 65/100, Llama 3 8B Instruct outperforms Phi-3.5 Mini by 6 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
Phi-3.5 Mini
Llama 3 8B Instruct
Context Window
128K tokens 8K
Architecture
Transformer Transformer (Open Weight)
Est. MMLU Score
~60-64% ~65-69%
Release Date
2024 2024
Pricing Model
Free Tier Paid / Commercial
Rate Limit (RPM)
Hardware limited Hardware dependent
Daily Limit
Unlimited Unlimited
Capabilities
Reasoning
No specific data
Performance Tier
C-Tier (Good) C-Tier (Good)
Speed Estimate
âš¡ Very Fast âš¡ Very Fast
Primary Use Case
âš¡ Fast Chat & Apps General Purpose
Model Size
Undisclosed 8B
Limitations
  • Depends on your RAM/GPU
  • Laptop fans will spin up
  • Large models (70B+) need heavy hardware
  • Learning curve for 'Bento' concept
  • Deployment requires cloud knowledge
  • Local serving is just step 1
Key Strengths
  • Local Inference: Data never leaves your device
  • Modelfiles: Script your own system prompts
  • API: Local REST API for app integration
  • Unified Model Store
  • Distributed Runner Architecture
  • Deployment Agnostic

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