Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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Llama 3 8B Instruct

BentoML

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

Phi-4

A-TIER

GitHub Models

Intelligence Score 89/100
Context Window 128K
Pricing Model Free / Open
Model Popularity 0 votes
FINAL VERDICT

Phi-4 Wins

With an intelligence score of 89/100 vs 71/100, Phi-4 outperforms Llama 3 8B Instruct by 18 points.

Clear Winner: Significant performance advantage for Phi-4.
HEAD-TO-HEAD

Detailed Comparison

Feature
Llama 3 8B Instruct
Phi-4
Context Window
8K 128K
Architecture
Transformer (Open Weight) Transformer
Est. MMLU Score
~65-69% ~80-84%
Release Date
2024 Dec 2024
Pricing Model
Paid / Commercial Free Tier
Rate Limit (RPM)
Hardware dependent Varies by Copilot Tier
Daily Limit
Unlimited Low
Capabilities
No specific data
Reasoning
Performance Tier
C-Tier (Good) A-Tier (Excellent)
Speed Estimate
âš¡ Very Fast Medium
Primary Use Case
General Purpose General Purpose
Model Size
8B Undisclosed
Limitations
  • Learning curve for 'Bento' concept
  • Deployment requires cloud knowledge
  • Local serving is just step 1
  • Restrictive limits
  • Requires GitHub account
  • Rate limits vary by Copilot tier
Key Strengths
  • Unified Model Store
  • Distributed Runner Architecture
  • Deployment Agnostic
  • Prototyping

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