Battle of the Models

Compare specific LLM models, context windows, and capabilities.

No matches found
VS
No matches found

DeepSeek Coder V2

A-TIER

Ollama

Intelligence Score 85/100
Model Popularity 0 votes
Context Window 64K tokens
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 Coder V2 Wins

With an intelligence score of 85/100 vs 84/100, DeepSeek Coder V2 outperforms Mistral Nemo 12B by 1 point.

Close Match: The difference is minimal. Consider other factors like pricing and features.
HEAD-TO-HEAD

Detailed Comparison

Feature
DeepSeek Coder V2
Mistral Nemo 12B
Context Window
64K tokens 32K tokens
Architecture
Dense Transformer Transformer (Open Weight)
Est. MMLU Score
~80-84% ~75-79%
Release Date
2024 2024
Pricing Model
Free Tier Free Tier
Rate Limit (RPM)
Hardware limited Hardware limited
Daily Limit
Unlimited Unlimited
Capabilities
No specific data
Multilingual
Performance Tier
A-Tier (Excellent) B-Tier (Strong)
Speed Estimate
Medium Medium
Primary Use Case
💻 Code Generation General Purpose
Model Size
Undisclosed 12B
Limitations
  • Depends on your RAM/GPU
  • Laptop fans will spin up
  • Large models (70B+) need heavy hardware
  • Depends on your RAM/GPU
  • Laptop fans will spin up
  • Large models (70B+) need heavy hardware
Key Strengths
  • Local Inference: Data never leaves your device
  • Modelfiles: Script your own system prompts
  • API: Local REST API for app integration
  • Local Inference: Data never leaves your device
  • Modelfiles: Script your own system prompts
  • API: Local REST API for app integration

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