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Open Source

Open-Source Model Selector

Choosing an open model is really four decisions, not one: what you are building, how sensitive the data is, how much infrastructure you can run, and what you can spend. This free tool asks those four questions and returns one or two open models that fit, with the license class spelled out and an honest note on when a closed frontier model would still serve you better. It is a rule engine over our verified comparison table, so every answer traces back to a model we have actually checked.

Models verified 2026-06-30. Grounded in the Best Open-Source AI Models comparison.

Read this first: the word "open" hides three legal realities. OSI open source (Apache 2.0, MIT) lets you use, modify, and redistribute commercially. Open-weight means the weights download freely but the license restricts use, as with the Llama 4 Community License. Source-available, non-free licenses block commercial deployment. The selector labels which class every recommendation falls into, because for a business that distinction is the whole decision.


Run the Selector

Answer the four questions and the tool returns a primary pick and a secondary option, each with its license and the caveats your answers imply. Nothing is stored; this free version runs entirely in your browser.

Answer Four Questions
Every recommendation is one of six on-table open models. It will never return a model we have not verified.
[PREMIUM]
Save and export your shortlist
This free version runs in your browser and forgets everything on refresh. Save your answers, compare multiple scenarios side by side, and export a shortlist (with licenses and caveats) as a shareable PDF. Coming with TJS membership.
Membership coming soon

How It Reads Your Answers

The logic is deliberately simple and transparent, so you can audit it. Your use case selects a base model family. Your infrastructure maturity and budget then choose between a heavier self-hosted variant and a lighter one: managed-only infrastructure or a minimal budget steers you to the model you can run without a cluster. Your data sensitivity adds the residency and licensing caveats, which is where the China-hosted DeepSeek API, the proprietary Qwen Max API, and the EU restriction in the Llama license all get flagged.

  • General chat: Mistral Large 3 (Apache 2.0) when you can self-host, Gemma 3 27B when you cannot.
  • Coding and agents: Qwen3-Coder or the lighter Qwen3.6-35B-A3B, both Apache 2.0 open weights.
  • Long-context: DeepSeek V4-Pro or the lighter V4-Flash, both MIT, with Llama 4 Scout noted when you truly need beyond 1M tokens.
  • On-device / edge: Phi-4 Reasoning (MIT) or Gemma 4 edge variants (Apache 2.0).
  • Multilingual: Mistral Large 3 or the lighter Ministral 3, both Apache 2.0 with European data residency.

When a Frontier Model Is Still the Better Call

Open weights hand you the operational burden along with the control. If you need the absolute top-end reasoning or multimodal ceiling, a zero-ops managed API with an enterprise SLA, or you cannot staff self-hosting at all, a managed frontier model such as GPT-5.5, Claude Opus 4.8, or Gemini 3 is the right answer. The sharpest case is regulated data on managed-only infrastructure: the cleanest open path needs self-hosting you cannot run, so a compliant, region-locked frontier model can be safer than a China-hosted open API. The tool surfaces this note with every result rather than pretending open is always the answer.


The Models It Draws From

These six are the only models the selector can output. Each carries a license we have verified against primary sources. For the full profiles, trade-offs, and the five more models on the watch list, read the Best Open-Source AI Models comparison.

ModelMakerLicense classBest fit
Llama 4 (Maverick / Scout)MetaOpen-weight (not OSI)Ultra-long context, multimodal
DeepSeek V4 (Pro / Flash)DeepSeekMIT (OSI open source)Cheap long-context reasoning
Qwen open line (Coder / 35B-A3B)AlibabaApache 2.0 (OSI open source)Agentic coding
Mistral Large 3 / Ministral 3Mistral AIApache 2.0 (OSI open source)Multilingual, EU residency
Gemma 4 / Gemma 3 27BGoogle DeepMindApache 2.0 / source-availableSingle-accelerator multimodal
Phi-4 ReasoningMicrosoftMIT (OSI open source)On-device reasoning

Models verified 2026-06-30. Licenses and context windows move fast; confirm on each model card before you build.


Test Your Open-Source Licensing Knowledge

The selector is only as useful as your grasp of what "open" really means. Three tiers, from a quick check to a procurement-grade scenario.

Knowledge Check
Pick a tier, then answer. Explanations appear as you go.

Frequently Asked Questions

How does the open-source model selector decide?
It is a rule engine, not an opinion. Your use case picks a base model, then your data sensitivity, infrastructure maturity, and budget choose between a heavier self-hosted variant and a lighter one, and add the license and residency caveats that apply. Every output is one of six models on our verified comparison table, so the tool cannot invent a model it has not checked.
Which models can the selector recommend?
Only on-table open models with a grounded license: Llama 4 (open-weight), DeepSeek V4 (MIT), the open Qwen line Qwen3-Coder and Qwen3.6-35B-A3B (Apache 2.0), Mistral Large 3 and Ministral 3 (Apache 2.0), Gemma 4 (Apache 2.0) and Gemma 3 27B (source-available), and Phi-4 Reasoning (MIT). It never recommends the proprietary Qwen3.7-Max, nor ungrounded models such as Kimi K2, GLM, Command, or Nemotron.
Is open-weight the same as open source?
No. OSI open source means an Open Source Initiative approved license such as Apache 2.0 or MIT, which allows commercial use, modification, and redistribution. Open-weight means the weights download freely but the license restricts use, as with the Llama 4 Community License or the Gemma Terms of Use. Source-available, non-free licenses block commercial deployment entirely. The selector labels the license class on every pick.
When should I pick a frontier model instead?
When you need the absolute top-end reasoning or multimodal ceiling, a zero-ops managed API with an enterprise SLA, or you cannot staff self-hosting at all. If your data is regulated but you can only consume managed endpoints, a compliant, region-locked frontier model may be safer than a China-hosted open API. The tool surfaces this honest note with every recommendation.
Recommendations grounded in verified model licenses. Models verified 2026-06-30.
Llama is a trademark of Meta Platforms. DeepSeek, Qwen, Mistral, Gemma, and Phi are trademarks of their respective owners (DeepSeek, Alibaba, Mistral AI, Google, and Microsoft). Tech Jacks Solutions is independent and has no affiliate relationship with the model makers listed here. License classes and benchmark figures are current as of June 2026 and mix vendor reports with public leaderboards.
Before You Use AI
Your Privacy

This selector runs entirely in your browser. It does not send your answers anywhere, and the free version stores nothing after you close the tab. The models it recommends have their own privacy profiles: the biggest advantage of open weights is that you can run them on your own hardware, so no prompt leaves your environment. Hosted endpoints differ by region; DeepSeek's hosted API runs from China, and Mistral is based in the EU.

Free tiers and hosted endpoints may log inputs for abuse monitoring. Check each provider's data-processing terms before sending sensitive data, and prefer on-premise deployment when residency rules apply.

Mental Health & AI Dependency

This tool helps you choose infrastructure. It is not a substitute for professional mental health support, and neither are the AI models it recommends. If you are experiencing distress, please reach out to trained professionals:

  • 988 Suicide & Crisis Lifeline: Call or text 988
  • SAMHSA Helpline: 1-800-662-4357
  • Crisis Text Line: Text HOME to 741741

AI systems can produce plausible-sounding but incorrect guidance. For mental health, medical, legal, or financial decisions, always consult a qualified professional.

Your Rights & Our Transparency

Under GDPR and CCPA, you have the right to access, correct, and delete personal data. Tech Jacks Solutions does not sell personal data. This tool is independently produced. We have no affiliate relationship with the model makers it recommends.

Open-source and open-weight models are still subject to the EU AI Act and applicable national regulations once you deploy them. Self-hosting does not remove your compliance obligations. This selector is a directional starting point, not a legal or compliance decision.