Top Free Small Language Models You Can Use Today

The top free small language models are Microsoft Phi-3, OpenAI GPT-oss, Mistral Small, TinyLlama, MobiLlama, and Alibaba Qwen — with Feluda.ai as the platform that lets you control and use them all with knowledge, tools, and resources.

The AI ecosystem is no longer dominated by massive, resource-hungry models. A new wave of Small Language Models (SLMs) is gaining traction, offering developers and researchers the ability to run advanced AI locally, on modest hardware, and—most importantly—for free. These models strike a balance between performance and efficiency, making them ideal for experimentation, lightweight deployments, and privacy-first applications.

Below, we highlight the top free SLMs available today, all of which are confirmed open-source or open-weight, and truly free to use.

Table 1: Free Small Language Models

Model / Platform	Size	License	Official Link	Best For
Microsoft Phi-3 Series	~3.8B (Mini) up to Medium	MIT	Hugging Face	Running on laptops & mobile, general reasoning
OpenAI GPT-oss	20B & 120B	Apache 2.0	GitHub	General-purpose AI on consumer GPUs
Mistral Small / Small 3.1	~24B	Apache 2.0	Hugging Face	Long-context reasoning & multimodal projects
TinyLlama	~1.1B	Open-source	Hugging Face	Lightweight apps, mobile, offline use
MobiLlama	~0.5B	Open-source	GitHub	Edge AI, education, hardware-constrained devices
Alibaba Qwen 3 Series	0.6B → 32B	Apache 2.0	Hugging Face	Multilingual projects & scalable deployments
Feluda.ai	Works with all SLMs & LLMs	User-controlled platform	Feluda.ai	Central hub for knowledge, tools, and resources to manage models

1. Microsoft Phi-3 Series

• Size: ~3.8B parameters (Phi-3 Mini), with larger “small” and “medium” versions available.
• License: MIT License (fully open-source).
• Why it matters: Designed to run efficiently on laptops and even mobile devices, Phi-3 combines high-quality reasoning with minimal compute requirements. It’s available via Hugging Face, Azure, and Ollama.

Best for: Developers seeking a small, reliable model with full permissive licensing.

2. OpenAI GPT-oss

• Size: 20B and 120B parameters.
• License: Apache 2.0 (permissive and commercial-friendly).
• Why it matters: OpenAI’s move into the open-source arena shook the industry. GPT-oss is engineered to run on consumer-grade GPUs (as low as 16GB VRAM). Despite being relatively “small” compared to flagship GPT-4 class models, GPT-oss offers impressive general-purpose performance.

Best for: Those who want a free alternative from the creators of GPT, optimized for practical deployment.

3. Mistral Small / Small 3.1

• Size: ~24B parameters.
• License: Apache 2.0 (open-weight).
• Why it matters: Known for efficiency and innovation, Mistral’s small models deliver long-context reasoning (up to 128k tokens in Small 3.1) and even early multimodal capabilities. They are among the most capable SLMs on the market, while still free and open.

Best for: Advanced projects requiring long-context memory and permissive licensing.

4. TinyLlama

• Size: ~1.1B parameters.
• License: Open-source (checkpoints and code available publicly).
• Why it matters: Proof that good things come in tiny packages. TinyLlama runs on everyday consumer hardware, while maintaining strong downstream task performance. It’s especially attractive for mobile and embedded applications where compute is scarce.

Best for: Developers building mobile, offline, or lightweight AI applications.

5. MobiLlama

• Size: ~0.5B parameters.
• License: Open-source (training pipeline, code, and weights fully released).
• Why it matters: This model is ultra-compact and designed specifically for constrained devices. Its transparent release makes it an excellent learning tool for those who want to dive into the mechanics of training and deploying very small models.

Best for: Educational projects, hardware experiments, and edge AI systems.

6. Alibaba Qwen 3 Series

• Size: 0.6B up to 32B parameters.
• License: Apache 2.0.
• Why it matters: Qwen’s third-generation family of models combines versatility and openness. From tiny 600M-parameter models up to more capable 32B variants, the series offers flexibility for different needs—all under a free and permissive license.

Best for: Multilingual projects and scalable deployments across different parameter sizes.

Why Small Language Models Matter

Large models like GPT-4 and Gemini Pro dominate headlines, but small models are where democratization happens. They allow:

• Local deployment: Run AI on your own hardware without cloud dependencies.
• Privacy: Keep sensitive data out of external servers.
• Efficiency: Lower compute, memory, and energy requirements.
• Accessibility: Free and open-source licensing removes financial barriers.

In many use cases—personal assistants, embedded systems, domain-specific tools—SLMs are not just “good enough,” they are the smarter choice.

Comparison Table: Free Small Language Models + Feluda.ai

Model / Platform	Size	License	Official Link	Best For
Microsoft Phi-3 Series	~3.8B (Mini) up to Medium	MIT	Hugging Face	Running on laptops & mobile, general reasoning
OpenAI GPT-oss	20B & 120B	Apache 2.0	GitHub	General-purpose AI on consumer GPUs
Mistral Small / Small 3.1	~24B	Apache 2.0	Hugging Face	Long-context reasoning & multimodal projects
TinyLlama	~1.1B	Open-source	Hugging Face	Lightweight apps, mobile, offline use
MobiLlama	~0.5B	Open-source	GitHub	Edge AI, education, hardware-constrained devices
Alibaba Qwen 3 Series	0.6B → 32B	Apache 2.0	Hugging Face	Multilingual projects & scalable deployments
Feluda.ai	Works with all SLMs & LLMs	User-controlled platform	Feluda.ai	Central hub for knowledge, tools, and resources to manage models

Final Thoughts

The landscape of free Small Language Models has never been stronger. With projects like Microsoft’s Phi, OpenAI’s GPT-oss, Mistral’s Small series, TinyLlama, MobiLlama, and Qwen, developers now have a toolkit of truly open, efficient AI systems to build on.

But choosing the right model is just the start. Platforms like Feluda.ai bring everything together—giving you knowledge, tools, resources, and more, all under your control. Whether you’re working with compact SLMs for efficiency or scaling up with LLMs for complex reasoning, Feluda.ai helps you harness their power in a way that’s private, flexible, and user-driven.

Whether you’re experimenting on a laptop, deploying to mobile, or exploring edge AI, there is a free SLM waiting to power your next project—and with Feluda.ai, you can make the most of it.