Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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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 →

DeepSeek-V4 Pro

A-TIER

DeepSeek

Intelligence Score 80/100
Context Window 128K
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Llama 3.1 405B Wins

With an intelligence score of 91/100 vs 80/100, Llama 3.1 405B outperforms DeepSeek-V4 Pro by 11 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
Llama 3.1 405B
DeepSeek-V4 Pro
Context Window
128K tokens 128K
Architecture
Transformer (Open Weight) Dense Transformer
Est. MMLU Score
~85-87% ~75-79%
Release Date
Jul 2024 2024
Pricing Model
Free Tier Paid / Commercial
Rate Limit (RPM)
10 RPM (free tier) 60 RPM
Daily Limit
Limited daily usage Credit-based
Capabilities
Reasoning
No specific data
Performance Tier
A-Tier (Excellent) B-Tier (Strong)
Speed Estimate
🐢 Slower (Reasoning) Medium
Primary Use Case
General Purpose General Purpose
Model Size
405B Undisclosed
Limitations
  • Free tier has speed/rate limits
  • Pro subscription needed for 405B speed
  • Decentralized network variance
  • 10M tokens is one-time only
  • API can be slow during peak hours (Chinese business hours)
  • Rate limiting during high demand periods
Key Strengths
  • Zero-Knowledge Proofs for privacy
  • Uncensored model options
  • Decentralized compute network
  • DeepSeek-R1: OpenAI o1-level reasoning (open-source)
  • Mixture-of-Experts architecture for efficiency
  • OpenAI-compatible API (drop-in replacement)

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