Disclaimer: This page discusses open source conversational AI models. ChatGPT is a trademark of OpenAI, Inc. This site is an independent resource providing information about open source alternatives and is not affiliated with or endorsed by OpenAI, Inc.

Open Source Chatbots

Best Open Source Conversational AI Models in 2025

Build your own AI chatbot with these free, open source conversational models. Get data privacy, unlimited usage, and full customization without subscription fees.

Quick Answer

Best open source conversational AI models for 2025: LLaMA 3.1 70B and Mixtral 8x22B offer high-quality conversational capabilities, completely free to run. Use Ollama for easy local setup or deploy on cloud GPUs starting at $0.50/hour.

Why Use an Open Source Conversational AI?

Free Forever

No monthly subscription fees. Pay only for compute resources. Run on your own hardware or cloud GPUs.

Private & Secure

All conversations stay on your infrastructure. No data sent to external servers. Perfect for sensitive business use.

No Limits

Unlimited messages, no rate limits, no usage caps. Use as much as needed without quota concerns.

Full Control

Customize responses, fine-tune for specific tasks, integrate with your apps. Complete flexibility.

Top 10 Open Source Conversational AI Models

Best Choice70B
LLaMA 3.1 70B
A powerful 70B parameter model that balances performance and efficiency, ideal for production deployments requiring high-quality outputs.
Quality Score:9.1/10
Context:128K tokens
freeConversational
Google27B
Gemma 2 27B
Google's open model built on Gemini research, offering strong performance with efficient architecture and safety features.
Quality Score:8.5/10
Context:8K tokens
freeConversational
Microsoft14B
Phi-3 Medium
Microsoft's efficient small language model that punches above its weight class with strong reasoning and coding abilities.
Quality Score:8.3/10
Context:128K tokens
freeConversational
01.AI34B
Yi 34B
High-performance bilingual model excelling in both English and Chinese tasks.
Quality Score:8.4/10
Context:200K tokens
freeConversational
Mistral AI7B
Mistral 7B
Efficient 7B model that outperforms larger models through superior architecture.
Quality Score:8.1/10
Context:32K tokens
freeConversational
LMSYS33B
Vicuna 33B
Fine-tuned LLaMA model trained on user conversations, excelling at dialogue.
Quality Score:7.8/10
Context:2K tokens
freeConversational
MosaicML30B
MPT 30B
Commercially-usable model with strong performance and flexible licensing.
Quality Score:7.9/10
Context:8K tokens
freeConversational
Teknium7B
OpenHermes 2.5
High-quality fine-tune focused on instruction following and helpfulness.
Quality Score:7.7/10
Context:8K tokens
freeConversational
Berkeley7B
Starling 7B Alpha
RLAIF-trained model achieving strong performance through reinforcement learning.
Quality Score:7.9/10
Context:8K tokens
freeConversational
Upstage10.7B
Solar 10.7B
Depth-upscaled model achieving strong performance through innovative architecture.
Quality Score:7.8/10
Context:4K tokens
freeConversational

How to Set Up Your Own Open Source Conversational AI

Step 1
Choose Your Model

Start with LLaMA 3.1 8B for local machines or LLaMA 3.1 70B for cloud deployment. Both offer excellent conversational abilities.

Step 2
Install Runtime

Use Ollama for the easiest setup. One command installs everything you need to run models locally on Mac, Windows, or Linux.

Step 3
Build Interface

Create a conversational AI-like UI with our Next.js tutorial, or use existing tools like Open WebUI for instant chat interface.

Proprietary vs Open Source: Feature Comparison

FeatureProprietary ServicesOpen Source
Monthly Cost$0-$20+ (subscription)$0-$50 (hardware only)
Message LimitsVaries by tierUnlimited
Data PrivacyStored by provider100% private
CustomizationLimitedFull fine-tuning
Offline UseNoYes
API AccessAdditional pricingFree (self-hosted)
Setup TimeInstant15-30 minutes

Frequently Asked Questions

Can open source models match proprietary conversational AI quality?

Yes, modern open source models like LLaMA 3.1 70B and Mixtral 8x22B offer comparable conversational quality to leading proprietary solutions for most tasks, excelling at reasoning, coding assistance, and general chat.

What hardware is needed to run conversational AI models?

For local use: 16GB RAM + modern CPU for 8B models, or RTX 4090 GPU for faster inference. Cloud deployment: GPU instances starting at $0.50/hour. Most models run on consumer hardware.

Is it legal to build conversational AI applications?

Yes, using open source models like LLaMA or Mixtral to build chat applications is completely legal. These models have permissive licenses allowing commercial use. Just avoid using others' trademarks or claiming false affiliations.

How do I get started with the easiest setup?

Install Ollama (one command), then run "ollama run llama3.1". You'll have a functional conversational AI running locally in under 5 minutes. Check our getting started guide for detailed instructions.

Start Building Your Own Conversational AI Today

Follow our step-by-step tutorials to deploy your own AI chatbot in minutes. Free, private, and unlimited.