Moonshot AI has kept the promise it made when Kimi K3.1 Pro was announced on 23 October 2026. The open weights of the company’s biggest model are now available on Hugging Face, in the repository named moonshotai/Kimi-K3.1-Pro. Anyone can download them, study them, fine-tune them, or run them on their own servers. There is no access request to fill in and no waiting list to join. That is the headline, and it matters, because the weights were only a promise two weeks ago. When the model launched, Moonshot said the weights would follow by 4 November 2026, and they have now arrived.
But the headline comes with a warning that every reader in Pakistan should understand before getting excited. Downloading the weights is free. Running them is not a job for a laptop, a desktop, or even a powerful gaming PC. The download itself is about 1.56 terabytes, split across 96 files, and the hardware needed to run the model is a rack of data-centre graphics cards. For most people, the sensible way to use Kimi K3.1 Pro is through its hosted API or through the Kimi apps, not by downloading the weights at all. This article explains what was released, what it costs to run, what the licence actually allows, and how good the model really is, using only facts that have been verified.
The Release Date Question: 2 November or 4 November?
If you search for the release date of the Kimi K3.1 Pro weights, you will find two different dates, and both of them are correct in their own way. The files in the Hugging Face repository carry a first commit dated 2 November 2026, and some trackers say the weights went public on that day. Moonshot’s own public announcement, posted on X, came on 4 November 2026 at 16:00 UTC, with the words “Releasing the model weights of Kimi K3.1 Pro”. Most of the coverage that followed dates the release to 4 November.
This article does not pick one date and hide the other. The honest way to describe it is that the files appeared in the repository on 2 November and Moonshot announced them publicly on 4 November. That is the same promise kept either way: the weights were promised by 4 November, and they were out by then. If Moonshot posts a clarification later, that would settle the question, but until then readers should know that both dates are in circulation and why. What matters for you is not the exact day the files appeared, but that they are there now, downloadable, with no gate in front of them.
What Exactly Was Released?
Kimi K3.1 Pro is a very large mixture-of-experts model. It has 2.8 trillion total parameters, of which 104 billion are active for each token it processes. A mixture-of-experts design means the model contains many specialist sub-models, called experts, and only a few of them work on any single token. Kimi K3.1 Pro has 896 experts, and 16 of them are selected for each token. The model has 93 layers and a context window of one million tokens, which means it can take in an enormous amount of text at once, far more than a normal chat conversation. It is natively multimodal, so it accepts both text and image input.
The download is about 1.56 terabytes, delivered as 96 files. The weights use MXFP4 precision, with MXFP8 activations, and the model was trained with quantization in mind, which is one reason it can be served at lower precision at all. There is no smaller official download and no compressed community build from Moonshot itself, so anyone planning to use the weights must be ready to move and store more than a terabyte and a half of data.
| Fact | Detail |
|---|---|
| Total parameters | 2.8 trillion |
| Active parameters per token | 104 billion |
| Architecture | Mixture of experts, 896 experts, 16 selected per token |
| Layers | 93 |
| Context window | 1 million tokens |
| Input types | Text and images |
| Download size | About 1.56 TB in 96 files |
| Weight format | MXFP4 weights, MXFP8 activations |
| Repository | moonshotai/Kimi-K3.1-Pro on Hugging Face |
| Access gate | None, no request needed |
This release also closes a watch that this site has been following since the launch article. When Kimi K3.1 Pro was announced on 23 October 2026, the weights were only promised, with a date of 4 November attached. That promise is now kept. It is a different story from the earlier Kimi K3 model, which is a separate and smaller model, and it is also different from the Mistral Large 4 open-weights release of 29 October 2026, which was covered in a separate article. Kimi K3.1 Pro is Moonshot’s flagship, and this is its full-weight release.
Why Your Laptop Cannot Run It
The most common misunderstanding about open weights is that “open” means “runs anywhere”. It does not. Open weights mean you can download the files and run them yourself, but the hardware still has to be big enough, and for Kimi K3.1 Pro it is very big indeed.
The simplest setup published by vLLM, the serving framework many teams use for large models, calls for eight data-centre GPUs with 288 GB of video memory each. That is not a gaming graphics card. A top gaming card today carries 16 or 24 GB of video memory. Eight server cards at 288 GB each is a different world, the kind of hardware that lives in a data centre, not on a desk. Estimates put the memory needed at around 861 GB of video memory at 2-bit precision and around 1,509 GB at 4-bit precision. Those are estimates, but they show the scale clearly: even in its most compressed form, this model needs hundreds of gigabytes of video memory.
There is also no GGUF build of the model as of 4 November 2026. GGUF is the format that lets ordinary tools run models on consumer hardware, and its absence means there is no easy path to squeeze Kimi K3.1 Pro onto a laptop or a home PC. Do not search for a GGUF file expecting an official one, and do not trust a random download that claims to be one, because no such build existed at the time of writing.
So the plain advice is this: do not download 1.56 TB of weights onto your home internet connection in Pakistan and expect to run them. The download alone would take a very long time on a normal connection, and at the end of it you would still not have hardware that can load the model. The weights are meant for research labs, cloud providers, and companies that already own or rent multi-GPU servers. If you are a student, a developer, or a curious reader, the hosted options below are the practical route.
The Easier Way: Use the Hosted API
For almost everyone, the way to use Kimi K3.1 Pro is through Moonshot’s hosted services. The model is live on Kimi.ai, Kimi Work, and Kimi Code, and it is available through the Kimi API. You send your requests over the internet, Moonshot’s servers do the heavy work, and you pay only for what you use.
The hosted API price is 2 US dollars per million input tokens and 10 US dollars per million output tokens, with cached input priced at 0.20 US dollars per million tokens. Those are US dollar prices, and they are the only prices that exist for the API. There is no rupee price for Kimi K3.1 Pro, and converting the dollar figures into rupees would not give you “the price”, because the billing is in dollars and the exchange rate moves. Anyone quoting you a fixed rupee price for the API is guessing.
| Way to use Kimi K3.1 Pro | What you need | Cost |
|---|---|---|
| Download the open weights | Eight data-centre GPUs, about 1.56 TB of storage | Free download, very expensive hardware |
| Kimi API (hosted) | An API key and internet | $2 per million input tokens, $10 per million output tokens |
| Kimi.ai / Kimi Work / Kimi Code | A browser or the app | Varies by plan, check in the app |
| Kimi K3.1 Pro Highspeed | Same as the hosted API | Faster, 2 to 3 times the speed |
There is also a faster variant called Kimi K3.1 Pro Highspeed, which runs at two to three times the speed of the standard model. It does not have a weights repository of its own, so if you want the fastest version, the hosted route is the only option. That is worth knowing before you plan any project around it.
If you are a developer in Pakistan and want to try the model, the practical steps are simple. Start with the Kimi.ai website or the Kimi app, which needs nothing more than a browser. If you want to build something with it, get an API key from Moonshot’s platform and test with a small number of tokens first, so you can see the cost before you scale up. Do not begin by downloading the weights, and do not rent a multi-GPU server until you have confirmed that the model does what your project needs, because that rental bill arrives whether your experiment works or not.
The Licence Is Not Plain MIT
Open weights often make people assume the model is fully open source under a standard licence such as MIT. Kimi K3.1 Pro is not. It is released under a custom licence called the Kimi K3.1-Pro License, and the difference matters, especially if you plan to use the model commercially.
The licence is MIT-style in its basics. It allows you to use, copy, change, and fine-tune the model, and to sell products built with it, as long as you keep the copyright notice. But it adds conditions for the largest users. Model-as-a-service providers with more than 20 million US dollars of revenue in twelve months need a separate agreement with Moonshot. Products with more than 100 million monthly users, or more than 20 million US dollars of monthly revenue, must display the model’s name. These are real conditions, not small print, and they mean the licence is a custom agreement with revenue and user thresholds, not a plain MIT licence and not fully open source in the usual sense.
The advice here is simple: read the licence before you use the weights for a commercial product or a self-hosted service. If you are only experimenting, learning, or building a small project, the licence is unlikely to trouble you. If you are building a service that could grow large, the thresholds are exactly the kind of thing you need to check with a lawyer or with Moonshot directly, before you invest time and money. Do not assume that “open weights” means “no conditions at all”, because for this model that is not true.
How Good Is It? Moonshot’s Own Numbers
Every benchmark number below comes from Moonshot itself, and that must be said clearly. No independent testing of the released checkpoint was available at the time of writing, so these figures are the company’s own claims about its own model, not results confirmed by anyone else.
On Terminal-Bench 4.0, a test of agentic coding ability, Moonshot reports 65.7 percent for Kimi K3.1 Pro, against 66.4 percent for Claude Opus 5.5 and 58.2 percent for GPT-6 Astra. In other words, on Moonshot’s own numbers, Kimi K3.1 Pro sits just behind Claude Opus 5.5 and ahead of GPT-6 Astra on that test. On cyber-security tests, Moonshot reports 81.0 on its internal exploit benchmark, 74.7 on ExploitBench, and 20.7 on ExploitGym. Those are specialist scores that matter mainly to security researchers, not to everyday users.
Benchmarks should always be read with care. A single test never tells the whole story, companies choose the tests that show their model well, and results can change when the model is tested by someone else on different tasks. The honest summary is that Moonshot claims its model is close to the best in the world on coding-agent tests, and that claim has not yet been checked independently on the released weights. If you are choosing a model for real work, try it on your own tasks, with your own data, before you believe any benchmark, including this one.
One more point needs care. There is an unconfirmed report that Kimi K3.1 Pro was trained using outputs from GPT-6 Astra. That report has not been confirmed, and this article does not present it as a fact. Treat it as an unverified claim until Moonshot or a reliable source confirms or denies it.
What This Means for You in Pakistan
There is no Pakistan launch, Pakistan availability date, or Pakistan-specific version of this release, because there does not need to be one. The weights are on Hugging Face, a global platform, and the API is available over the internet. A developer in Bahawalnagar has the same access as a developer anywhere else, as long as they have an internet connection and, for the API, a way to pay in dollars.
That said, the practical advice for readers in Pakistan is the same as for readers anywhere. If you are a student learning about large models, read the model card, study the architecture, and try the hosted version through Kimi.ai, which costs you nothing to open. If you are a developer, test the API with a small budget and measure the cost per task, because the dollar pricing means a careless loop can spend money quickly. If you are a researcher, the open weights are genuinely useful, because you can inspect, fine-tune, and test the model in ways a closed API never allows, but you will need access to a cloud GPU service, since local hardware will not be enough. And if you are a business owner wondering whether to build on this model, read the licence first, test the API second, and only think about self-hosting third.
The bigger picture is also worth noting. Open-weight releases from companies like Moonshot and Mistral are becoming a regular part of the AI world. Each one gives developers more choice and more control, and each one comes with its own licence, its own hardware demands, and its own limits. Kimi K3.1 Pro is the latest and the largest of these releases, and its promise, made on 23 October and kept by 4 November, is a small sign that the open-weights trend is continuing. Whether it becomes a model that Pakistani developers actually use will depend on the API price, the quality of the hosted service, and the results of independent testing once the released weights have been studied properly.
The proof of this release is public and easy to check. According to enjoy.dev, Moonshot published the Kimi K3.1 Pro weights on 4 November 2026, the download is about 1.56 TB with no access gate, and no GGUF build existed at the time of writing.
FAQs
What is the Kimi K3.1 Pro open weights release?
It is Moonshot AI publishing the full weight files of its Kimi K3.1 Pro model on Hugging Face, in the repository moonshotai/Kimi-K3.1-Pro. The model has 2.8 trillion total parameters, 104 billion active per token, and a one-million-token context window. The download is about 1.56 TB in 96 files, and there is no access request or waiting list.
Can I run Kimi K3.1 Pro on my laptop or phone? No. The model needs a multi-GPU server, with the simplest published setup calling for eight data-centre GPUs with 288 GB of video memory each. It needs around 861 GB of video memory at 2-bit precision and around 1,509 GB at 4-bit precision, and there is no GGUF build for consumer hardware as of 4 November 2026. Use the hosted API or the Kimi apps instead.
How much does it cost to use Kimi K3.1 Pro? Downloading the weights is free, but running them needs very expensive server hardware. The hosted API costs 2 US dollars per million input tokens and 10 US dollars per million output tokens, with cached input at 0.20 US dollars per million tokens. Those are US dollar prices, and there is no official rupee price.
Is Kimi K3.1 Pro fully open source under the MIT licence? No. It is released under a custom licence called the Kimi K3.1-Pro License. It is MIT-style in allowing use, copying, changes, fine-tuning, and selling, but it adds conditions for large users: model-as-a-service providers with over 20 million US dollars of revenue in twelve months need a separate agreement, and products with over 100 million monthly users or 20 million US dollars of monthly revenue must display the model’s name. Read the licence before commercial use.