Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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meta/llama-3-70b-instruct

A-TIER

Replicate

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

Llama 3.1 405B Instruct

S-TIER

DeepInfra

Intelligence Score 92/100
Context Window 128K
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Llama 3.1 405B Instruct Wins

With an intelligence score of 92/100 vs 83/100, Llama 3.1 405B Instruct outperforms meta/llama-3-70b-instruct by 9 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
meta/llama-3-70b-instruct
Llama 3.1 405B Instruct
Context Window
8K tokens 128K
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~75-79% ~85-87%
Release Date
2024 Jul 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
Varies by model 60 RPM (varies by model)
Daily Limit
Credit-based Credit-based (no daily cap)
Capabilities
No specific data
Reasoning
Performance Tier
B-Tier (Strong) A-Tier (Excellent)
Speed Estimate
⚡ Fast 🐢 Slower (Reasoning)
Primary Use Case
General Purpose General Purpose
Model Size
70b 405B
Limitations
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
  • $5 credit is one-time only
  • Credits expire after 90 days
  • Rate limits vary by model
Key Strengths
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models
  • OpenAI-compatible API (drop-in replacement)
  • 40+ open-source models hosted
  • Fast inference with optimized serving

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