Battle of the Models

Compare specific LLM models, context windows, and capabilities.

Qwen 2.5

LLM7.io

Intelligence Score 65/100

Model Popularity 0 votes

Context Window 32K

Pricing Model Free / Open

View Provider Analysis →

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

With an intelligence score of 80/100 vs 65/100, Mistral Nemo Instruct 2407 outperforms Qwen 2.5 by 15 points.

Clear Winner: Significant performance advantage for Mistral Nemo Instruct 2407.

HEAD-TO-HEAD

Feature	Qwen 2.5	Mistral Nemo Instruct 2407
Context Window	32K	128K Context
Architecture	Transformer (Open Weight)	Transformer (Open Weight)
Est. MMLU Score	~60-64%	~75-79%
Release Date	Sep-Nov 2024	2024
Pricing Model	Free Tier	Free Tier
Rate Limit (RPM)	30 RPM (no signup) / 120 RPM (free email token)	30 RPM (no signup) / 120 RPM (free email token)
Daily Limit	Up to 5M tokens/day (rolling 24h, with free token)	Up to 5M tokens/day (rolling 24h, with free token)
Capabilities	No specific data	No specific data
Performance Tier	C-Tier (Good)	B-Tier (Strong)
Speed Estimate	Medium	Medium
Primary Use Case	General Purpose	General Purpose
Model Size	Undisclosed	Undisclosed
Limitations	No signup tier is heavily rate-limited (30 RPM) Smaller, less well-known provider — verify uptime before production use	No signup tier is heavily rate-limited (30 RPM) Smaller, less well-known provider — verify uptime before production use
Key Strengths	Works with zero signup OpenAI-compatible endpoint — swap base_url + key No signup required for basic use	Works with zero signup OpenAI-compatible endpoint — swap base_url + key No signup required for basic use