Battle of the Models

Compare specific LLM models, context windows, and capabilities.

DeepSeek-V4 Flash

A-TIER

DeepSeek

Intelligence Score 83/100

Model Popularity 0 votes

Context Window 1M

Pricing Model Commercial / Paid

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A-TIER

Mistral (La Plateforme)

Intelligence Score 80/100

Context Window 128k

Pricing Model Free / Open

Model Popularity 0 votes

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FINAL VERDICT

With an intelligence score of 83/100 vs 80/100, DeepSeek-V4 Flash outperforms Mistral Nemo by 3 points.

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

HEAD-TO-HEAD

Feature	DeepSeek-V4 Flash	Mistral Nemo
Context Window	1M	128k
Architecture	Dense Transformer	Transformer (Open Weight)
Est. MMLU Score	~75-79%	~75-79%
Release Date	2024	2024
Pricing Model	Paid / Commercial	Free Tier
Rate Limit (RPM)	60 RPM	1 request/second
Daily Limit	Credit-based	-
Capabilities	No specific data	No specific data
Performance Tier	B-Tier (Strong)	B-Tier (Strong)
Speed Estimate	⚡ Very Fast	Medium
Primary Use Case	⚡ Fast Chat & Apps	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	Phone verification required Data training opt-in required 1 request/second rate limit
Key Strengths	DeepSeek-R1: OpenAI o1-level reasoning (open-source) Mixture-of-Experts architecture for efficiency OpenAI-compatible API (drop-in replacement)	Access to Mistral's open-weight models OpenAI-compatible API endpoints Function calling support