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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OpenRouter

Intelligence Score 79/100

Context Window 32k

Pricing Model Free / Open

Model Popularity 0 votes

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FINAL VERDICT

With an intelligence score of 83/100 vs 79/100, meta/llama-3-70b-instruct outperforms Qwen 2.5 7B Instruct (free) by 4 points.

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

HEAD-TO-HEAD

Feature	meta/llama-3-70b-instruct	Qwen 2.5 7B Instruct (free)
Context Window	8K tokens	32k
Architecture	Transformer (Open Weight)	Transformer (Open Weight)
Est. MMLU Score	~75-79%	~70-74%
Release Date	2024	Sep-Nov 2024
Pricing Model	Paid / Commercial	Free Tier
Rate Limit (RPM)	Varies by model	20 requests/minute
Daily Limit	Credit-based	50 requests/day (up to 1000 with $10 topup)
Capabilities	No specific data	No specific data
Performance Tier	B-Tier (Strong)	B-Tier (Strong)
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	Limits depend on account history/topup Community key models Free models have lower priority during peak demand
Key Strengths	Run any public model with an API Fine-tune existing models easily Cold boots can be slow for unpopular models	Unified API for 100+ models from all providers OpenAI-compatible endpoint (drop-in replacement) Automatic model fallback and routing