Battle of the Models

Compare specific LLM models, context windows, and capabilities.

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Mistral Nemo Instruct 2407

A-TIER

LLM7.io

Intelligence Score 80/100
Model Popularity 0 votes
Context Window 128K Context
Pricing Model Free / Open

Qwen3.8 27B

Groq

Intelligence Score 65/100
Context Window 131K Context
Pricing Model Free / Open
Model Popularity 0 votes
FINAL VERDICT

Mistral Nemo Instruct 2407 Wins

With an intelligence score of 80/100 vs 65/100, Mistral Nemo Instruct 2407 outperforms Qwen3.8 27B by 15 points.

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

Detailed Comparison

Feature
Mistral Nemo Instruct 2407
Qwen3.8 27B
Context Window
128K Context 131K Context
Architecture
Transformer (Open Weight) Transformer (Open Weight)
Est. MMLU Score
~75-79% ~60-64%
Release Date
2024 2024
Pricing Model
Free Tier Free Tier
Rate Limit (RPM)
30 RPM (no signup) / 120 RPM (free email token) 30 RPM, 14.4k RPD
Daily Limit
Up to 5M tokens/day (rolling 24h, with free token) 14,400 Requests/Day
Capabilities
No specific data
No specific data
Performance Tier
B-Tier (Strong) C-Tier (Good)
Speed Estimate
Medium ⚡ Very Fast
Primary Use Case
General Purpose General Purpose
Model Size
Undisclosed 27B
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

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