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 →

DeepSeek-R1

S-TIER

Chutes.ai

Intelligence Score 97/100
Context Window 64K
Pricing Model Free / Open
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

DeepSeek-R1 Wins

With an intelligence score of 97/100 vs 83/100, DeepSeek-R1 outperforms meta/llama-3-70b-instruct by 14 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
meta/llama-3-70b-instruct
DeepSeek-R1
Context Window
8K tokens 64K
Architecture
Transformer (Open Weight) Dense Transformer
Est. MMLU Score
~75-79% ~92-95%
Release Date
2024 Jan 2025
Pricing Model
Paid / Commercial Free Tier
Rate Limit (RPM)
Varies by model Varies (community capacity)
Daily Limit
Credit-based Subject to availability
Capabilities
No specific data
Reasoning
Performance Tier
B-Tier (Strong) S-Tier (Elite)
Speed Estimate
⚡ Fast 🐢 Slower (Reasoning)
Primary Use Case
General Purpose 🧠 Complex Reasoning
Model Size
70b Undisclosed
Limitations
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
  • Availability depends on community GPU donors
  • Speed varies with demand
  • Models may be temporarily unavailable
Key Strengths
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models
  • Community-powered GPU network
  • Free access to large open-source models
  • OpenAI-compatible API format

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