Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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VS
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DeepSeek Coder 6.7B

A-TIER

Cloudflare Workers AI

Intelligence Score 83/100
Model Popularity 0 votes
Context Window 16K
Pricing Model Free / Open
View Provider Analysis →

meta/llama-3-70b-instruct

A-TIER

Replicate

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

DeepSeek Coder 6.7B Wins

Equal intelligence scores (83/100), but DeepSeek Coder 6.7B offers a significantly larger context window.

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

Detailed Comparison

Feature
DeepSeek Coder 6.7B
meta/llama-3-70b-instruct
Context Window
16K 8K tokens
Architecture
Dense Transformer Transformer (Open Weight)
Est. MMLU Score
~75-79% ~75-79%
Release Date
2024 2024
Pricing Model
Free Tier Paid / Commercial
Rate Limit (RPM)
Varies by model Varies by model
Daily Limit
10,000 neurons/day Credit-based
Capabilities
Code
No specific data
Performance Tier
B-Tier (Strong) B-Tier (Strong)
Speed Estimate
âš¡ Very Fast âš¡ Fast
Primary Use Case
💻 Code Generation General Purpose
Model Size
6.7B 70b
Limitations
  • 10,000 neurons/day cap (varies per model)
  • Larger models consume more neurons per request
  • No fine-tuning support
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
Key Strengths
  • Edge inference: runs closest to user
  • 50+ models: LLM, image gen, classification, speech
  • Workers integration for serverless apps
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models

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