Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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

Replicate

Intelligence Score 76/100
Model Popularity 0 votes
Context Window 32K tokens
Pricing Model Commercial / Paid

Llama 3.1 405B

S-TIER

Venice.ai

Intelligence Score 91/100
Context Window 128K tokens
Pricing Model Free / Open
Model Popularity 0 votes
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
mistralai/mistral-7b-instruct-v0.2
Llama 3.1 405B
Context Window
32K tokens 128K tokens
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~70-74% ~85-87%
Release Date
2024 Jul 2024
Pricing Model
Paid / Commercial Free Tier
Rate Limit (RPM)
Varies by model 10 RPM (free tier)
Daily Limit
Credit-based Limited daily usage
Capabilities
No specific data
Reasoning
Performance Tier
B-Tier (Strong) A-Tier (Excellent)
Speed Estimate
⚡ Very Fast 🐢 Slower (Reasoning)
Primary Use Case
General Purpose General Purpose
Model Size
7b 405B
Limitations
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
  • Free tier has speed/rate limits
  • Pro subscription needed for 405B speed
  • Decentralized network variance
Key Strengths
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models
  • Zero-Knowledge Proofs for privacy
  • Uncensored model options
  • Decentralized compute network

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