Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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VS
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DeepSeek-R1

S-TIER

NVIDIA NIM

Intelligence Score 97/100
Model Popularity 0 votes
Context Window 128K
Pricing Model Commercial / Paid
View Provider Analysis →

DeepSeek-V4 Flash

A-TIER

DeepSeek

Intelligence Score 83/100
Context Window 1M
Pricing Model Commercial / Paid
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

DeepSeek-R1 Wins

With an intelligence score of 97/100 vs 83/100, DeepSeek-R1 outperforms DeepSeek-V4 Flash by 14 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
DeepSeek-R1
DeepSeek-V4 Flash
Context Window
128K 1M
Architecture
Dense Transformer Dense Transformer
Est. MMLU Score
~92-95% ~75-79%
Release Date
Jan 2025 2024
Pricing Model
Paid / Commercial Paid / Commercial
Rate Limit (RPM)
40 requests/minute 60 RPM
Daily Limit
- Credit-based
Capabilities
No specific data
No specific data
Performance Tier
S-Tier (Elite) B-Tier (Strong)
Speed Estimate
🐢 Slower (Reasoning) ⚡ Very Fast
Primary Use Case
🧠 Complex Reasoning ⚡ Fast Chat & Apps
Model Size
Undisclosed Undisclosed
Limitations
  • Phone number verification required
  • Free credits are limited
  • Rate limits on free tier
  • 10M tokens is one-time only
  • API can be slow during peak hours (Chinese business hours)
  • Rate limiting during high demand periods
Key Strengths
  • High performance models
  • DeepSeek-R1: OpenAI o1-level reasoning (open-source)
  • Mixture-of-Experts architecture for efficiency
  • OpenAI-compatible API (drop-in replacement)

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