Battle of the Models

Compare specific LLM models, context windows, and capabilities.

DeepSeek V4 Pro (0813)

A-TIER

NVIDIA NIM

Intelligence Score 80/100

Model Popularity 0 votes

Context Window Long context

Pricing Model Free / Open

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A-TIER

LLM7.io

Intelligence Score 80/100

Context Window 128K Context

Pricing Model Free / Open

Model Popularity 0 votes

View Provider Analysis →

FINAL VERDICT

Equal intelligence scores (80/100), but Mistral Nemo Instruct 2407 offers a significantly larger context window.

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

HEAD-TO-HEAD

Feature	DeepSeek V4 Pro (0813)	Mistral Nemo Instruct 2407
Context Window	Long context	128K Context
Architecture	Dense Transformer	Transformer (Open Weight)
Est. MMLU Score	~75-79%	~75-79%
Release Date	2024	2024
Pricing Model	Free Tier	Free Tier
Rate Limit (RPM)	40 requests/minute	30 RPM (no signup) / 120 RPM (free email token)
Daily Limit	-	Up to 5M tokens/day (rolling 24h, with free token)
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	Undisclosed
Limitations	Phone number verification required Free credits are limited Rate limits on free tier	No signup tier is heavily rate-limited (30 RPM) Smaller, less well-known provider — verify uptime before production use
Key Strengths	High performance models	Works with zero signup OpenAI-compatible endpoint — swap base_url + key No signup required for basic use