Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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Llama 3.1 (Deployable)

Cerebrium

Intelligence Score 65/100
Model Popularity 0 votes
Context Window 128K
Pricing Model Commercial / Paid
View Provider Analysis →

meta/llama-3-70b-instruct

A-TIER

Replicate

Intelligence Score 83/100
Context Window 8K tokens
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

meta/llama-3-70b-instruct Wins

With an intelligence score of 83/100 vs 65/100, meta/llama-3-70b-instruct outperforms Llama 3.1 (Deployable) by 18 points.

Clear Winner: Significant performance advantage for meta/llama-3-70b-instruct.
HEAD-TO-HEAD

Detailed Comparison

Feature
Llama 3.1 (Deployable)
meta/llama-3-70b-instruct
Context Window
128K 8K tokens
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~60-64% ~75-79%
Release Date
Jul 2024 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
Pay-per-second compute Varies by model
Daily Limit
Credit-based Credit-based
Capabilities
No specific data
No specific data
Performance Tier
C-Tier (Good) B-Tier (Strong)
Speed Estimate
Medium ⚡ Fast
Primary Use Case
General Purpose General Purpose
Model Size
Undisclosed 70b
Limitations
  • $30 is one-time trial credits
  • Requires some DevOps knowledge
  • Cold starts for serverless models
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
Key Strengths
  • Deploy any HuggingFace model
  • Serverless GPU infrastructure
  • Auto-scaling (scale to zero)
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models

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