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Microsoft Phi-4 is a 14 billion parameter model that answers maths and reasoning questions well enough to embarrass models several times its size. Microsoft Research released it in December 2024 and published the weights on Hugging Face under the MIT licence, which is about as permissive as a licence gets. On this page it is free, with no account and nothing to install.
Phi-4 is the clearest example of an idea that has quietly reshaped the field: what a model is trained on matters more than how big it is. Microsoft built it largely on carefully generated synthetic data, curated textbook-style material rather than a scrape of everything, and the result is a 14B model that competes with much larger ones on exactly the tasks where size usually wins: mathematics, logical reasoning, structured problem solving.
What it is not is a general-knowledge model. Ask it about a film, a footballer or last year's news and a larger model will do better. The trade is deliberate and it is worth understanding before you judge it.
Phi-4 is a 14B dense decoder-only transformer with a 16,000 token context window. It is text only: no images. The weights are on Hugging Face under the MIT licence, so it can be downloaded, modified and used commercially with very few conditions. Its knowledge has a cutoff and it does not browse, so anything current has to be given to it in the prompt.
The 16K window is the real constraint to plan around. It is plenty for a problem, a proof or a function, and not enough for a long report. For those, Gemini 3.1 or DeepSeek V4 in the model bar have windows dozens of times larger.
| Self-hosted | Azure AI Foundry | AIFreeForever Phi-4 | |
|---|---|---|---|
| Price | Your hardware | Metered | Free |
| Account | None | Azure subscription | None |
| Setup | Download and serve | Deploy an endpoint | None |
| Licence | MIT | MIT | MIT |
| Good for | Production | Scale | Trying it out |
| Model | Size | Context | Best at |
|---|---|---|---|
| Microsoft Phi-4 | 14B | 16K | Maths and reasoning |
| Meta Llama 3.1 | 8B | 128K | General open-weight text |
| DeepSeek V3.2 | 671B MoE | 128K | Technical answers at length |
| Grok 4 | Not published | Large | Step-by-step reasoning |
| GPT 5 | Not published | 400K | Reasoning and tool use |
The two small open models on this site, and they do not overlap much. Phi-4 is the better reasoner and the better mathematician. Llama 3.1 is smaller, faster and takes eight times as much text in one go. Choose by whether your bottleneck is thinking or length.
DeepSeek V3.2 is the stronger model on almost any hard question, and it is also open weights. The interesting comparison is what it costs to run: Phi-4 fits on a single consumer GPU and DeepSeek V3.2 does not. If you are evaluating what you can realistically self-host, that difference is the whole story.
Phi-4 is trained to show its working and the working is usually where you catch a mistake. If step three is wrong, say so and ask it to continue from step two rather than starting over.
It responds well to precision. Give the constraints, the units, what is known and what is being asked. Loose phrasing is where small models lose their advantage.
Long conversations eventually push the beginning out of the window. For a long problem, restate the essentials when you follow up, or move to a model with a larger window.
It was trained for reasoning rather than recall, and it will answer a factual question it does not know rather than decline. For facts, use GPT 5 or Gemini 3.1 in the bar.
The chat box at the top of this page is already on Microsoft Phi-4.
State the problem precisely, with its constraints.
Attach a document if it is short. Remember the 16K window. Images are not supported.
Read the working and challenge any step that looks wrong.
Requests go over HTTPS through our server. Conversations are not stored and uploaded files are removed at the end of the session. There is no account involved. If your requirement is that nothing leaves your own machine, download the weights and run it locally; the MIT licence exists precisely so you can.
Phi-4 is a research-grade small model and it has the failure modes of one. Its general knowledge is thin and it fills gaps confidently rather than admitting them. Its context window is small enough to matter. It has been trained heavily on synthetic material, which makes it sharp on problems that resemble textbook problems and less sure-footed on messy real-world text. Use it for the reasoning, and use a bigger model in the bar when the question needs to know things.
Yes. No login, no card, no message cap.
14 billion parameters, dense, not a mixture of experts.
16,000 tokens. The smallest of any model on this site, so plan around it.
Yes, from Hugging Face under the MIT licence, which permits commercial use.
No. Phi-4 is text only. The multimodal variants are separate models.
No, and that is by design. It was trained for reasoning. For facts, switch models in the bar.
It is good at small, well-defined programming problems. For a real codebase, use DeepSeek V4.
No. This is an independent site offering free access to an openly published model.
A 14B model that argues its way to the right answer. Microsoft Phi-4 is free at the top of this page.
