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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A-TIER

Friendli AI

Intelligence Score 86/100

Context Window 32K

Pricing Model Commercial / Paid

Model Popularity 0 votes

View Provider Analysis →

FINAL VERDICT

With an intelligence score of 86/100 vs 83/100, Mixtral 8x7B Instruct outperforms meta/llama-3-70b-instruct by 3 points.

Close Match: The difference is minimal. Consider other factors like pricing and features.

HEAD-TO-HEAD

Feature	meta/llama-3-70b-instruct	Mixtral 8x7B Instruct
Context Window	8K tokens	32K
Architecture	Transformer (Open Weight)	Mixture of Experts (MoE)
Est. MMLU Score	~75-79%	~80-84%
Release Date	2024	2024
Pricing Model	Paid / Commercial	Paid / Commercial
Rate Limit (RPM)	Varies by model	60 RPM
Daily Limit	Credit-based	Credit-based
Capabilities	No specific data	Multilingual
Performance Tier	B-Tier (Strong)	A-Tier (Excellent)
Speed Estimate	⚡ Fast	⚡ Very Fast
Primary Use Case	General Purpose	General Purpose
Model Size	70b	7B
Limitations	Pay-per-second billing (can be expensive) Cold starts for less popular models Trial credits are minimal	$10 credit is one-time trial Billing required after credits Limited model selection
Key Strengths	Run any public model with an API Fine-tune existing models easily Cold boots can be slow for unpopular models	Optimized inference engine (FriendliEngine) OpenAI-compatible API endpoints Enterprise-grade uptime