Code Llama or Twinny? A Comprehensive Review

Generates code

Understands code

Code completion capability

Supports debugging tasks

Supports Python

C++

Java

PHP

Typescript

C#

Operates locally

Enhances code completion

Seamless integration with Ollama

Cost effective

Ensures user confidentiality

Real-time code suggestions

Supports multiple programming languages

Configurable endpoint and port

Chat feature

Visual comparison for code completions

Higher latency with 34B model

Not suitable for natural language tasks

Doesn't generate safe responses on certain occasions

Requires user adherence to licensing and acceptable policy

May generate risky or malicious code

Specialized models required for specific languages

Does not perform general natural language tasks

Requires a large volume of tokens

Lacks adaptability for non-coding tasks

Service and latency requirements vary between models

Requires Visual Studio Code

Requires separate Ollama installation

No standalone functionality

Lacks extensive user reviews

Limited tools compared to Copilot

Usage requires constant Internet connection

Dependent on Ollama API updates

Frequent updates may disrupt workflow

No advanced setting or customization

No support for all languages