Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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

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

Any HuggingFace Model

Cerebrium

Intelligence Score 65/100
Context Window Model-dependent
Pricing Model Commercial / Paid
Model Popularity 0 votes
FINAL VERDICT

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

With an intelligence score of 76/100 vs 65/100, mistralai/mistral-7b-instruct-v0.2 outperforms Any HuggingFace Model by 11 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
mistralai/mistral-7b-instruct-v0.2
Any HuggingFace Model
Context Window
32K tokens Model-dependent
Architecture
Transformer (Open Weight) Transformer
Est. MMLU Score
~70-74% ~60-64%
Release Date
2024 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
Varies by model Pay-per-second compute
Daily Limit
Credit-based Credit-based
Capabilities
No specific data
No specific data
Performance Tier
B-Tier (Strong) C-Tier (Good)
Speed Estimate
⚡ Very Fast Medium
Primary Use Case
General Purpose General Purpose
Model Size
7b Undisclosed
Limitations
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
  • $30 is one-time trial credits
  • Requires some DevOps knowledge
  • Cold starts for serverless models
Key Strengths
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models
  • Deploy any HuggingFace model
  • Serverless GPU infrastructure
  • Auto-scaling (scale to zero)

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