Battle of the Models

Compare specific LLM models, context windows, and capabilities.

DeepSeek-V4 Pro

A-TIER

DeepSeek

Intelligence Score 80/100

Model Popularity 0 votes

Context Window 128K

Pricing Model Commercial / Paid

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A-TIER

Groq

Intelligence Score 85/100

Context Window 1k RPD, 10k TPM

Pricing Model Free / Open

Model Popularity 0 votes

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FINAL VERDICT

With an intelligence score of 85/100 vs 80/100, Moonshot Kimi K2 outperforms DeepSeek-V4 Pro by 5 points.

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

HEAD-TO-HEAD

Feature	DeepSeek-V4 Pro	Moonshot Kimi K2
Context Window	128K	1k RPD, 10k TPM
Architecture	Dense Transformer	Transformer
Est. MMLU Score	~75-79%	~80-84%
Release Date	2024	2024
Pricing Model	Paid / Commercial	Free Tier
Rate Limit (RPM)	60 RPM	30 RPM, 14.4k RPD
Daily Limit	Credit-based	14,400 Requests/Day
Capabilities	No specific data	No specific data
Performance Tier	B-Tier (Strong)	A-Tier (Excellent)
Speed Estimate	Medium	Medium
Primary Use Case	General Purpose	General Purpose
Model Size	Undisclosed	Undisclosed
Limitations	10M tokens is one-time only API can be slow during peak hours (Chinese business hours) Rate limiting during high demand periods	Test
Key Strengths	DeepSeek-R1: OpenAI o1-level reasoning (open-source) Mixture-of-Experts architecture for efficiency OpenAI-compatible API (drop-in replacement)	LPU Accelerated Extremely Fast Inference Open Source Models