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 76/100

Context Window 256K Context

Pricing Model Free / Open

Model Popularity 0 votes

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FINAL VERDICT

With an intelligence score of 80/100 vs 76/100, DeepSeek-V4 Pro outperforms Qwen3 235B A22B Instruct 2507 by 4 points.

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

HEAD-TO-HEAD

Feature	DeepSeek-V4 Pro	Qwen3 235B A22B Instruct 2507
Context Window	128K	256K Context
Architecture	Dense Transformer	Transformer (Open Weight)
Est. MMLU Score	~75-79%	~70-74%
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)	B-Tier (Strong)
Speed Estimate	Medium	Medium
Primary Use Case	General Purpose	General Purpose
Model Size	Undisclosed	235B
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