Battle of the Models

Compare specific LLM models, context windows, and capabilities.

meta/llama-3-70b-instruct

A-TIER

Replicate

Intelligence Score 83/100

Model Popularity 0 votes

Context Window 8K tokens

Pricing Model Commercial / Paid

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Venice.ai

Intelligence Score 65/100

Context Window 32K tokens

Pricing Model Free / Open

Model Popularity 0 votes

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FINAL VERDICT

With an intelligence score of 83/100 vs 65/100, meta/llama-3-70b-instruct outperforms Dolphin Mixtral by 18 points.

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

HEAD-TO-HEAD

Feature	meta/llama-3-70b-instruct	Dolphin Mixtral
Context Window	8K tokens	32K tokens
Architecture	Transformer (Open Weight)	Mixture of Experts (MoE)
Est. MMLU Score	~75-79%	~60-64%
Release Date	2024	2024
Pricing Model	Paid / Commercial	Free Tier
Rate Limit (RPM)	Varies by model	10 RPM (free tier)
Daily Limit	Credit-based	Limited daily usage
Capabilities	No specific data	No specific data
Performance Tier	B-Tier (Strong)	C-Tier (Good)
Speed Estimate	⚡ Fast	Medium
Primary Use Case	General Purpose	General Purpose
Model Size	70b	Undisclosed
Limitations	Pay-per-second billing (can be expensive) Cold starts for less popular models Trial credits are minimal	Free tier has speed/rate limits Pro subscription needed for 405B speed Decentralized network variance
Key Strengths	Run any public model with an API Fine-tune existing models easily Cold boots can be slow for unpopular models	Zero-Knowledge Proofs for privacy Uncensored model options Decentralized compute network