Battle of the Models

Compare specific LLM models, context windows, and capabilities.

No matches found
VS
No matches found

DeepSeek-R1

S-TIER

Chutes.ai

Intelligence Score 97/100
Model Popularity 0 votes
Context Window 64K
Pricing Model Free / Open

Mistral Nemo

A-TIER

Mistral (La Plateforme)

Intelligence Score 80/100
Context Window 128k
Pricing Model Free / Open
Model Popularity 0 votes
FINAL VERDICT

DeepSeek-R1 Wins

With an intelligence score of 97/100 vs 80/100, DeepSeek-R1 outperforms Mistral Nemo by 17 points.

Clear Winner: Significant performance advantage for DeepSeek-R1.
HEAD-TO-HEAD

Detailed Comparison

Feature
DeepSeek-R1
Mistral Nemo
Context Window
64K 128k
Architecture
Dense Transformer Transformer (Open Weight)
Est. MMLU Score
~92-95% ~75-79%
Release Date
Jan 2025 2024
Pricing Model
Free Tier Free Tier
Rate Limit (RPM)
Varies (community capacity) 1 request/second
Daily Limit
Subject to availability -
Capabilities
Reasoning
No specific data
Performance Tier
S-Tier (Elite) B-Tier (Strong)
Speed Estimate
🐢 Slower (Reasoning) Medium
Primary Use Case
🧠 Complex Reasoning General Purpose
Model Size
Undisclosed Undisclosed
Limitations
  • Availability depends on community GPU donors
  • Speed varies with demand
  • Models may be temporarily unavailable
  • Phone verification required
  • Data training opt-in required
  • 1 request/second rate limit
Key Strengths
  • Community-powered GPU network
  • Free access to large open-source models
  • OpenAI-compatible API format
  • Access to Mistral's open-weight models
  • OpenAI-compatible API endpoints
  • Function calling support

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