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

Mixtral 8x7B Instruct

A-TIER

Friendli AI

Intelligence Score 86/100
Context Window 32K
Pricing Model Commercial / Paid
Model Popularity 0 votes
FINAL VERDICT

Mixtral 8x7B Instruct Wins

With an intelligence score of 86/100 vs 71/100, Mixtral 8x7B Instruct outperforms Llama 3 8B Instruct by 15 points.

Clear Winner: Significant performance advantage for Mixtral 8x7B Instruct.
HEAD-TO-HEAD

Detailed Comparison

Feature
Llama 3 8B Instruct
Mixtral 8x7B Instruct
Context Window
8K 32K
Architecture
Transformer (Open Weight) Mixture of Experts (MoE)
Est. MMLU Score
~65-69% ~80-84%
Release Date
2024 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
Hardware dependent 60 RPM
Daily Limit
Unlimited Credit-based
Capabilities
No specific data
Multilingual
Performance Tier
C-Tier (Good) A-Tier (Excellent)
Speed Estimate
⚡ Very Fast ⚡ Very Fast
Primary Use Case
General Purpose General Purpose
Model Size
8B 7B
Limitations
  • Learning curve for 'Bento' concept
  • Deployment requires cloud knowledge
  • Local serving is just step 1
  • $10 credit is one-time trial
  • Billing required after credits
  • Limited model selection
Key Strengths
  • Unified Model Store
  • Distributed Runner Architecture
  • Deployment Agnostic
  • Optimized inference engine (FriendliEngine)
  • OpenAI-compatible API endpoints
  • Enterprise-grade uptime

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