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
View Provider Analysis →

Mistral Nemo 12B

A-TIER

Ollama

Intelligence Score 84/100
Context Window 32K tokens
Pricing Model Free / Open
Model Popularity 0 votes
View Provider Analysis →
FINAL VERDICT

DeepSeek-R1 Wins

With an intelligence score of 97/100 vs 84/100, DeepSeek-R1 outperforms Mistral Nemo 12B by 13 points.

HEAD-TO-HEAD

Detailed Comparison

Feature
DeepSeek-R1
Mistral Nemo 12B
Context Window
64K 32K tokens
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) Hardware limited
Daily Limit
Subject to availability Unlimited
Capabilities
Reasoning
Multilingual
Performance Tier
S-Tier (Elite) B-Tier (Strong)
Speed Estimate
🐢 Slower (Reasoning) Medium
Primary Use Case
🧠 Complex Reasoning General Purpose
Model Size
Undisclosed 12B
Limitations
  • Availability depends on community GPU donors
  • Speed varies with demand
  • Models may be temporarily unavailable
  • Depends on your RAM/GPU
  • Laptop fans will spin up
  • Large models (70B+) need heavy hardware
Key Strengths
  • Community-powered GPU network
  • Free access to large open-source models
  • OpenAI-compatible API format
  • Local Inference: Data never leaves your device
  • Modelfiles: Script your own system prompts
  • API: Local REST API for app integration

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