Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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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 VL 72B Instruct (free)

A-TIER

OpenRouter

Intelligence Score 83/100
Context Window 32k
Pricing Model Free / Open
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Llama 3.1 405B Wins

With an intelligence score of 91/100 vs 83/100, Llama 3.1 405B outperforms Qwen 2.5 VL 72B Instruct (free) by 8 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
Llama 3.1 405B
Qwen 2.5 VL 72B Instruct (free)
Context Window
128K tokens 32k
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~85-87% ~75-79%
Release Date
Jul 2024 Sep-Nov 2024
Pricing Model
Free Tier Free Tier
Rate Limit (RPM)
10 RPM (free tier) 20 requests/minute
Daily Limit
Limited daily usage 50 requests/day (up to 1000 with $10 topup)
Capabilities
Reasoning
No specific data
Performance Tier
A-Tier (Excellent) B-Tier (Strong)
Speed Estimate
🐢 Slower (Reasoning) ⚡ Fast
Primary Use Case
General Purpose 👁️ Vision & Multimodal
Model Size
405B 72B
Limitations
  • Free tier has speed/rate limits
  • Pro subscription needed for 405B speed
  • Decentralized network variance
  • Limits depend on account history/topup
  • Community key models
  • Free models have lower priority during peak demand
Key Strengths
  • Zero-Knowledge Proofs for privacy
  • Uncensored model options
  • Decentralized compute network
  • Unified API for 100+ models from all providers
  • OpenAI-compatible endpoint (drop-in replacement)
  • Automatic model fallback and routing

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