Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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VS
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DeepSeek-V4 Pro

A-TIER

DeepSeek

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

Llama 3.1 70B (via routing)

A-TIER

Requesty

Intelligence Score 87/100
Context Window 128K
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

Llama 3.1 70B (via routing) Wins

With an intelligence score of 87/100 vs 80/100, Llama 3.1 70B (via routing) outperforms DeepSeek-V4 Pro by 7 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
DeepSeek-V4 Pro
Llama 3.1 70B (via routing)
Context Window
128K 128K
Architecture
Dense Transformer Transformer (Open Weight)
Est. MMLU Score
~75-79% ~80-84%
Release Date
2024 Jul 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
60 RPM 60 RPM
Daily Limit
Credit-based Credit-based
Capabilities
No specific data
No specific data
Performance Tier
B-Tier (Strong) A-Tier (Excellent)
Speed Estimate
Medium ⚡ Fast
Primary Use Case
General Purpose General Purpose
Model Size
Undisclosed 70B
Limitations
  • 10M tokens is one-time only
  • API can be slow during peak hours (Chinese business hours)
  • Rate limiting during high demand periods
  • Requires underlying provider API keys
  • Free credit amount is limited
  • Routing adds minimal latency
Key Strengths
  • DeepSeek-R1: OpenAI o1-level reasoning (open-source)
  • Mixture-of-Experts architecture for efficiency
  • OpenAI-compatible API (drop-in replacement)
  • AI Router: automatic provider failover
  • Prompt caching for cost savings
  • Multi-provider load balancing

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