Battle of the Models

Compare specific LLM models, context windows, and capabilities.

No matches found
VS
No matches found

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 →

Qwen 2.5 72B Instruct

S-TIER

Chutes.ai

Intelligence Score 91/100
Context Window 32K
Pricing Model Free / Open
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Llama 3.1 405B Wins

Equal intelligence scores (91/100), but Llama 3.1 405B offers a significantly larger context window.

Close Match: The difference is minimal. Consider other factors like pricing and features.
HEAD-TO-HEAD

Detailed Comparison

Feature
Llama 3.1 405B
Qwen 2.5 72B Instruct
Context Window
128K tokens 32K
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~85-87% ~85-87%
Release Date
Jul 2024 Sep-Nov 2024
Pricing Model
Free Tier Free Tier
Rate Limit (RPM)
10 RPM (free tier) Varies (community capacity)
Daily Limit
Limited daily usage Subject to availability
Capabilities
Reasoning
No specific data
Performance Tier
A-Tier (Excellent) A-Tier (Excellent)
Speed Estimate
🐢 Slower (Reasoning) ⚡ Fast
Primary Use Case
General Purpose General Purpose
Model Size
405B 72B
Limitations
  • Free tier has speed/rate limits
  • Pro subscription needed for 405B speed
  • Decentralized network variance
  • Availability depends on community GPU donors
  • Speed varies with demand
  • Models may be temporarily unavailable
Key Strengths
  • Zero-Knowledge Proofs for privacy
  • Uncensored model options
  • Decentralized compute network
  • Community-powered GPU network
  • Free access to large open-source models
  • OpenAI-compatible API format

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