Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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No matches found

OpenLLM Generic

BentoML

Intelligence Score 65/100
Model Popularity 0 votes
Context Window Varies
Pricing Model Commercial / Paid

Llama 3.1 405B

S-TIER

Venice.ai

Intelligence Score 91/100
Context Window 128K tokens
Pricing Model Free / Open
Model Popularity 0 votes
FINAL VERDICT

Llama 3.1 405B Wins

With an intelligence score of 91/100 vs 65/100, Llama 3.1 405B outperforms OpenLLM Generic by 26 points.

Clear Winner: Significant performance advantage for Llama 3.1 405B.
HEAD-TO-HEAD

Detailed Comparison

Feature
OpenLLM Generic
Llama 3.1 405B
Context Window
Varies 128K tokens
Architecture
Transformer Transformer (Open Weight)
Est. MMLU Score
~60-64% ~85-87%
Release Date
2024 Jul 2024
Pricing Model
Paid / Commercial Free Tier
Rate Limit (RPM)
Hardware dependent 10 RPM (free tier)
Daily Limit
Unlimited Limited daily usage
Capabilities
No specific data
Reasoning
Performance Tier
C-Tier (Good) A-Tier (Excellent)
Speed Estimate
Medium 🐢 Slower (Reasoning)
Primary Use Case
General Purpose General Purpose
Model Size
Undisclosed 405B
Limitations
  • Learning curve for 'Bento' concept
  • Deployment requires cloud knowledge
  • Local serving is just step 1
  • Free tier has speed/rate limits
  • Pro subscription needed for 405B speed
  • Decentralized network variance
Key Strengths
  • Unified Model Store
  • Distributed Runner Architecture
  • Deployment Agnostic
  • Zero-Knowledge Proofs for privacy
  • Uncensored model options
  • Decentralized compute network

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