Battle of the Models

Compare specific LLM models, context windows, and capabilities.

Mistral Nemo Instruct 2407

A-TIER

LLM7.io

Intelligence Score 80/100

Model Popularity 0 votes

Context Window 128K Context

Pricing Model Free / Open

View Provider Analysis →

Groq

Intelligence Score 65/100

Context Window 131K 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 GPT-OSS 20B by 15 points.

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

HEAD-TO-HEAD

Feature	Mistral Nemo Instruct 2407	GPT-OSS 20B
Context Window	128K Context	131K Context
Architecture	Transformer (Open Weight)	Transformer (Proprietary)
Est. MMLU Score	~75-79%	~60-64%
Release Date	2024	2024
Pricing Model	Free Tier	Free Tier
Rate Limit (RPM)	1 req/s, 60/min, 250/hour (free token from dash.llm7.io)	30 RPM; 8K TPM on most chat models (varies by model)
Daily Limit	100,000 tokens per 24h (free token; may be reduced without notice)	1,000 requests/day and 200K tokens/day on gpt-oss / Qwen (varies by model)
Capabilities	No specific data	No specific data
Performance Tier	B-Tier (Strong)	C-Tier (Good)
Speed Estimate	Medium	Medium
Primary Use Case	General Purpose	General Purpose
Model Size	Undisclosed	20B
Limitations	No signup tier is heavily rate-limited (30 RPM) Smaller, less well-known provider — verify uptime before production use	Test
Key Strengths	Works with zero signup OpenAI-compatible endpoint — swap base_url + key No signup required for basic use	LPU Accelerated Extremely Fast Inference Open Source Models