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 →

Meta: Llama 3.3 70B Instruct (free)

S-TIER

OpenRouter

Intelligence Score 94/100
Context Window 128k
Pricing Model Free / Open
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Meta: Llama 3.3 70B Instruct (free) Wins

With an intelligence score of 94/100 vs 91/100, Meta: Llama 3.3 70B Instruct (free) outperforms Llama 3.1 405B by 3 points.

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

Detailed Comparison

Feature
Llama 3.1 405B
Meta: Llama 3.3 70B Instruct (free)
Context Window
128K tokens 128k
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~85-87% ~88-91%
Release Date
Jul 2024 Dec 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) S-Tier (Elite)
Speed Estimate
🐢 Slower (Reasoning) ⚡ Fast
Primary Use Case
General Purpose General Purpose
Model Size
405B 70B
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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