Every month, the gap between the AI you rent and the AI you can own gets a little smaller. You can now download a model for free, run it on a single graphics card or a well-equipped Mac, and get answers that would have beaten the best paid chatbots of 2025. Nothing leaves your computer, nothing costs per message, and it works with the Wi-Fi off.
Our verdict: Qwen3.8 27B is the best free local LLM you can run in 2026. It's a 27-billion-parameter model from Alibaba's Qwen team, released August 14 under the Apache 2.0 license, and it ranks #1 of 142 open models in its size class on the Artificial Analysis Intelligence Index. It needs about 24GB of memory to run well. It still trails the frontier cloud models by a wide margin: 34 on the index, against 58 for Claude Opus 5.5. The best cloud models remain meaningfully smarter. For private, free, everyday work, local is now genuinely good.
The Short Version
Best free local LLM: Qwen3.8 27B. It's an 18GB download in Ollama and comfortable with 32GB of memory or a 24GB graphics card.
Best for a 16GB laptop: gpt-oss-20b or the smaller Gemma 4 models.
Fastest on a 32GB Mac: Qwen3.6 35B-A3B, which only uses about 3 billion parameters per word.
How it compares: roughly 60% of Claude Opus 5.5 on the independent index, for $0 and full privacy.
The Scoreboard: Local vs Cloud
The fairest way to compare local and cloud models is a single independent score. The Artificial Analysis Intelligence Index combines reasoning, coding, math and knowledge tests into one number:
| Model | Type | AA Intelligence Index | Cost | Runs on |
|---|---|---|---|---|
| Claude Opus 5.5 | Cloud | 58 | $4 / $20 per 1M tokens | Anthropic's servers |
| GPT-6 Astra | Cloud | 53 | $10 / $50 per 1M tokens | OpenAI's servers |
| MiMo-V2.6-Pro | Open weights | 46 | Free to download | Multi-GPU server (300GB+) |
| GLM-5.3 | Open weights | 45 | Free to download | Multi-GPU server (300GB+) |
| Gemini 3.8 Flash | Cloud | 41 | $0.75 / $3.75 (promo) | Google's servers |
| DeepSeek V4.1 Flash | Open weights | 39 | Free, or $0.30 / $1.20 API | Server (about 614GB of GPU memory) |
| Qwen3.8 27B | Open weights | 34 | Free | One 24GB GPU or a 32GB Mac |
Read the table in two halves. The top open-weight models (Xiaomi's MiMo-V2.6-Pro and Zhipu's GLM-5.3) are close to Gemini's cloud models, but they need a rack of server GPUs. They're "free" only if you already own a data center. Qwen3.8 27B is the best model that fits on hardware a person can actually buy. The median open model its size scores just 8.
Why Qwen3.8 27B Wins
- It's genuinely strong. On Qwen's own tests it scores 61.7 on SWE-bench Pro and 89.2 on GPQA-Diamond, trading blows with frontier models from early 2026 on coding. Treat those vendor numbers with care until others reproduce them. The independent index score of 34 is the number to trust.
- It sees images. It's a vision-language model, so it can read screenshots, charts and photos locally.
- It remembers a lot. Its 256K-token context window holds a long codebase or a stack of documents.
- It's truly open. The Apache 2.0 license allows commercial use with no strings.
- It's easy to install. One Ollama command pulls the default 4-bit build, an 18GB download. It had more than 2.7 million downloads of community builds in its first four days.
What Hardware You Need
| Your machine | Best pick | What to expect |
|---|---|---|
| 8–16GB laptop | gpt-oss-20b or the small Gemma 4 models | Fine for chat, summaries and simple code; noticeably weaker reasoning |
| 24GB Mac | Qwen3.8 27B (4-bit) | Works, but slow: under 10 tokens per second |
| 32GB Mac | Qwen3.6 35B-A3B for speed, Qwen3.8 27B for quality | Qwen3.8 runs about 5–6 tokens per second on a base M4 Mac mini |
| PC with a 24GB GPU (RTX 4090/5090) | Qwen3.8 27B | Fast: 40–57 tokens per second on typical replies, far more with tuned setups |
| 128GB+ workstation | gpt-oss-120b, larger quantized models | Near-cloud experience for most tasks |
Two practical warnings. Don't go below 4-bit on Qwen3.8; quality drops sharply. And long context costs memory. The full 256K window needs roughly another 16GB on top of the model, so on a 32GB machine keep conversations shorter. For a deeper breakdown by memory tier, see Best Local LLM by RAM or try our RAM calculator.
Local vs Cloud: Where Each Wins
Local wins on privacy, cost and control. Client documents, medical notes, proprietary code and anything under an NDA never leave your machine. There's no subscription, no per-token bill and no rate limit, and it works on a plane.
The cloud wins on hard problems and speed. Long, multi-step coding tasks, tricky reasoning and research where a wrong answer is expensive still belong to Claude Opus 5.5 or GPT-6. Those models are 20-plus points ahead on the index, and on a laptop a local model can be several times slower.
The smart setup uses both. Run Qwen3.8 locally for everyday drafting, summaries, private documents and quick code, and send the hardest 10% to a frontier model. If you'd rather pay a little than buy hardware, GPT-6 Luna costs pennies per million tokens.
How to Run It
The three easiest apps all use the same engine underneath:
- Ollama: best for developers. One terminal command downloads and runs the model, with a local API other apps can use.
- LM Studio: best for tinkerers. A polished app for browsing models, comparing builds and tuning settings.
- Jan: best for newcomers. A simple chat window that feels like ChatGPT, fully offline.
We compare all three in Ollama vs LM Studio vs Jan. For the full open-weight field, including the server-class models, see Best Non-Cloud LLMs 2026.
The Verdict
Qwen3.8 27B is the best free local LLM of 2026. It's the smartest model that fits on a single graphics card or a 32GB Mac, it's free for any use, and it handles most everyday work well. It isn't a replacement for Claude Opus 5.5 or GPT-6 on the hardest problems, and on a laptop it's slow. As a private, zero-cost everyday assistant, it's the first local model we'd recommend to people who aren't hobbyists.
FAQ
What is the best free local LLM in 2026?
Qwen3.8 27B, released August 14, 2026 under the Apache 2.0 license. It ranks first of 142 open-weight models in its size class on the Artificial Analysis Intelligence Index with a score of 34, and runs on a 24GB graphics card or a Mac with 32GB of memory.
How does a local LLM compare to ChatGPT and Claude?
The best local model scores 34 on the Artificial Analysis Intelligence Index, against 58 for Claude Opus 5.5 and 53 for GPT-6 Astra. It's good enough for everyday writing, summaries and simple coding, but frontier cloud models are still clearly better at hard reasoning and long coding tasks.
How much RAM do I need to run a local LLM?
16GB runs smaller models like gpt-oss-20b. About 24GB is the practical minimum for Qwen3.8 27B, and 32GB is comfortable. A PC with a 24GB graphics card runs it fastest. The largest open models need 128GB or more.
Is Qwen3.8 safe and free for commercial use?
It's released under the Apache 2.0 license, which allows free commercial use. When run locally, your prompts and files stay on your computer. As with any model, review outputs before relying on them for important work.
What is the best local LLM for a 16GB laptop?
gpt-oss-20b or one of the smaller Gemma 4 models. They handle chat, summaries and light coding well, but they're noticeably weaker at complex reasoning than Qwen3.8 27B.