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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Nebius (Token Factory)

Intelligence Score 65/100

Context Window Long context

Pricing Model Free / Open

Model Popularity 0 votes

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FINAL VERDICT

With an intelligence score of 80/100 vs 65/100, DeepSeek-V4 Pro outperforms Qwen3.5 397B A17B by 15 points.

Clear Winner: Significant performance advantage for DeepSeek-V4 Pro.

HEAD-TO-HEAD

Feature	DeepSeek-V4 Pro	Qwen3.5 397B A17B
Context Window	128K	Long context
Architecture	Dense Transformer	Transformer (Open Weight)
Est. MMLU Score	~75-79%	~60-64%
Release Date	2024	2024
Pricing Model	Paid / Commercial	Free Tier
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)	C-Tier (Good)
Speed Estimate	Medium	⚡ Very Fast
Primary Use Case	General Purpose	General Purpose
Model Size	Undisclosed	397B
Limitations	10M tokens is one-time only API can be slow during peak hours (Chinese business hours) Rate limiting during high demand periods	$1 credit is small (good for testing) Limited model selection compared to aggregators Beta features may change
Key Strengths	DeepSeek-R1: OpenAI o1-level reasoning (open-source) Mixture-of-Experts architecture for efficiency OpenAI-compatible API (drop-in replacement)	Nebius Studio: Interactive playground OpenAI Compatibility: Easy swap Cost Effective: Competitive pricing