Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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meta/llama-3-70b-instruct

A-TIER

Replicate

Intelligence Score 83/100
Model Popularity 0 votes
Context Window 8K tokens
Pricing Model Commercial / Paid

Gemma 4 31B

Friendli AI

Intelligence Score 65/100
Context Window 262K Context
Pricing Model Free / Open
Model Popularity 0 votes
FINAL VERDICT

meta/llama-3-70b-instruct Wins

With an intelligence score of 83/100 vs 65/100, meta/llama-3-70b-instruct outperforms Gemma 4 31B by 18 points.

Clear Winner: Significant performance advantage for meta/llama-3-70b-instruct.
HEAD-TO-HEAD

Detailed Comparison

Feature
meta/llama-3-70b-instruct
Gemma 4 31B
Context Window
8K tokens 262K Context
Architecture
Transformer (Open Weight) Transformer
Est. MMLU Score
~75-79% ~60-64%
Release Date
2024 2024
Pricing Model
Paid / Commercial Free Tier
Rate Limit (RPM)
Varies by model 60 RPM
Daily Limit
Credit-based Credit-based
Capabilities
No specific data
No specific data
Performance Tier
B-Tier (Strong) C-Tier (Good)
Speed Estimate
⚡ Fast Medium
Primary Use Case
General Purpose General Purpose
Model Size
70b 31B
Limitations
  • Pay-per-second billing (can be expensive)
  • Cold starts for less popular models
  • Trial credits are minimal
  • $10 credit is one-time trial
  • Billing required after credits
  • Limited model selection
Key Strengths
  • Run any public model with an API
  • Fine-tune existing models easily
  • Cold boots can be slow for unpopular models
  • Optimized inference engine (FriendliEngine)
  • OpenAI-compatible API endpoints
  • Enterprise-grade uptime

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