Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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Mixtral 8x22B Instruct

A-TIER

DeepInfra

Intelligence Score 89/100
Model Popularity 0 votes
Context Window 64K
Pricing Model Commercial / Paid
View Provider Analysis →

Llama 3 8B Instruct

BentoML

Intelligence Score 71/100
Context Window 8K
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Mixtral 8x22B Instruct Wins

With an intelligence score of 89/100 vs 71/100, Mixtral 8x22B Instruct outperforms Llama 3 8B Instruct by 18 points.

Clear Winner: Significant performance advantage for Mixtral 8x22B Instruct.
HEAD-TO-HEAD

Detailed Comparison

Feature
Mixtral 8x22B Instruct
Llama 3 8B Instruct
Context Window
64K 8K
Architecture
Mixture of Experts (MoE) Transformer (Open Weight)
Est. MMLU Score
~80-84% ~65-69%
Release Date
2024 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
60 RPM (varies by model) Hardware dependent
Daily Limit
Credit-based (no daily cap) Unlimited
Capabilities
Reasoning Multilingual
No specific data
Performance Tier
A-Tier (Excellent) C-Tier (Good)
Speed Estimate
Medium ⚡ Very Fast
Primary Use Case
General Purpose General Purpose
Model Size
22B 8B
Limitations
  • $5 credit is one-time only
  • Credits expire after 90 days
  • Rate limits vary by model
  • Learning curve for 'Bento' concept
  • Deployment requires cloud knowledge
  • Local serving is just step 1
Key Strengths
  • OpenAI-compatible API (drop-in replacement)
  • 40+ open-source models hosted
  • Fast inference with optimized serving
  • Unified Model Store
  • Distributed Runner Architecture
  • Deployment Agnostic

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meta/llama-3-70b-instruct