Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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Llama 3.1 405B

S-TIER

Venice.ai

Intelligence Score 91/100
Model Popularity 0 votes
Context Window 128K tokens
Pricing Model Free / Open
View Provider Analysis →

mistralai/mistral-7b-instruct-v0.2

Replicate

Intelligence Score 76/100
Context Window 32K tokens
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Llama 3.1 405B Wins

With an intelligence score of 91/100 vs 76/100, Llama 3.1 405B outperforms mistralai/mistral-7b-instruct-v0.2 by 15 points.

Clear Winner: Significant performance advantage for Llama 3.1 405B.
HEAD-TO-HEAD

Detailed Comparison

Feature
Llama 3.1 405B
mistralai/mistral-7b-instruct-v0.2
Context Window
128K tokens 32K tokens
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~85-87% ~70-74%
Release Date
Jul 2024 2024
Pricing Model
Free Tier Paid / Commercial
Rate Limit (RPM)
10 RPM (free tier) Varies by model
Daily Limit
Limited daily usage Credit-based
Capabilities
Reasoning
No specific data
Performance Tier
A-Tier (Excellent) B-Tier (Strong)
Speed Estimate
🐢 Slower (Reasoning) ⚡ Very Fast
Primary Use Case
General Purpose General Purpose
Model Size
405B 7b
Limitations
  • Free tier has speed/rate limits
  • Pro subscription needed for 405B speed
  • Decentralized network variance
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
Key Strengths
  • Zero-Knowledge Proofs for privacy
  • Uncensored model options
  • Decentralized compute network
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models

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