Question 1

Why Apple Silicon, and why now?

Accepted Answer

Apple has quietly shipped the largest fleet of AI-ready hardware in the world. There were 2.5 billion active Apple devices in January 2026, and every iPhone, iPad and Mac on Apple Silicon pairs a GPU and a Neural Engine with one shared pool of fast unified memory.

While others pour hundreds of billions into datacenters, Apple has largely sat the race out. Call it the last mover. Its bet is different: run what you can on the device, and send only what you must to the cloud. MLX connects that fleet into one network, owned by the people who power it.

Apple Inc. · AAPL

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Log scale. Split-adjusted closing prices. Shown for context, not as a prediction or advice.

Sources: 9to5Mac, Jan 2026

Question 2

Why are Nvidia, OpenAI, Anthropic and Google racing to build datacenters?

Accepted Answer

Because so far, more compute has meant better models. Training and serving frontier AI takes enormous clusters of GPUs, and whoever controls the most compute sets the pace. The numbers are hard to picture. Amazon, Microsoft, Alphabet and Meta planned more than $700 billion of capital spending for 2026, most of it for AI datacenters. Nvidia, which sells most of the chips, is worth around $5.7 trillion. Money isn't the only limit. Every new datacenter needs gigawatts of power, cooling, land, chips and years of building. The devices people already own need none of that: they're bought, powered and connected.

Question 3

Apple Silicon or Nvidia: which wins?

Accepted Answer

Chip for chip, Nvidia, by a wide margin. A datacenter GPU like the H100 is built for dense AI math and wired to thousands of others with very fast links. The largest frontier models will keep training in places like that. Apple Silicon wins on different terms: memory and efficiency. A Mac Studio with M3 Ultra holds up to 512 GB of unified memory, enough to run a model with more than 600 billion parameters on one desk. An H100 has 80 GB. Apple chips also use a fraction of the power. So it isn't either-or. Datacenters train the giants. A network of Apple devices runs models, fine-tunes them and handles everything that should stay private.

Question 4

Can millions of devices really work as one supercomputer?

Accepted Answer

It has happened before. In 2020, Folding@home volunteers passed an exaflop of combined power on their home computers, more than the fastest supercomputers of the time. A network like this suits work that splits into independent pieces: answering prompts, batch jobs, embeddings, evaluations and fine-tuning. Research into low-communication training, such as DeepMind's DiLoCo, keeps narrowing the gap for training too. It doesn't suit jobs where every chip must talk to every other chip thousands of times a second. MLX is designed around that line, routing each task to where it runs best.

Question 5

What could the largest Apple Silicon network be worth?

Accepted Answer

Nobody knows, so here is a thought experiment. Instead of guessing a price, ask what it would cost to buy the same capacity as datacenter GPUs. Drag to size the network.

Question 6

Local or cloud: why does hybrid win?

Accepted Answer

Today you mostly choose between a closed model in someone else's datacenter, which sees everything you send it, and a small local model that keeps your data private but can do less. Hybrid removes that choice. Your personal context, like messages, files, photos and health data, stays on your device, where a local model reads it. Work that needs more muscle goes out as a narrow, stripped-down request to the network or to a frontier model. Apple built Apple Intelligence on the same idea, pairing on-device models with Private Cloud Compute. Picture one assistant that drafts on your iPhone, thinks on the largest Apple Silicon supercomputer in the world, and never sees more than the task in front of it. Privacy and the best capability, without trading one for the other. That's the future MLX is building toward.

Question 7

What is MLX?

Accepted Answer

A community building the largest Apple Silicon compute network. Apple chips have unified memory and fast neural engines, and hundreds of millions of them sit idle most of the day. Pooled together, they form a supercomputer owned by the people who power it. The MLX token tracks who helped build it and, later, who did the work.

Question 8

What does a dedicated seat do today?

Accepted Answer

A dedicated seat is like a stake: it reserves your Mac's place on the network, sets its share of the rewards and, as paid AI jobs arrive, puts it first in line for work. It pays nothing up front. While it runs on a Mac of its class that's linked to your wallet and doing AI work in MLX Node, it mines from the compute pool, hour by hour: up to 20× what a free seat mines for Core, 80× for Pro, 320× for Ultra, and 1.5× more for Latest. On a smaller Mac a seat mines at that Mac's class. Mined MLX is locked briefly: each day's mining unlocks after your seat's lock-in, or 30 days on a free seat.

Question 9

Why does a seat mine instead of paying out up front?

Accepted Answer

Because the network needs Macs that work, not seats that sit idle. Since 20 October 2026 a seat pays nothing when you buy it: it earns only while a Mac of its class does verified AI work. The halving curve still sets the network price of MLX: every 200,000 seat units (a Core seat is 2.5 units, Pro ten, Ultra forty), what $100 buys halves and the price doubles, from one cent at genesis.

Question 10

Is this a blockchain?

Accepted Answer

It's an open ledger. Every transaction is signed with your Ed25519 key, every block is hash-linked and signed by the sequencer, and all of it is public. You can verify any signature or block in your browser from the explorer. It runs as a single sequencer today so it can move fast while the community grows.

Question 11

How do lock-ins work?

Accepted Answer

Mined MLX is locked so the network grows with people who stay. With a dedicated seat, each day's mining unlocks after your seat's lock-in: 20 days for Nano, 14 for Lite, 10 for Core, 7 for Pro and 3 for Ultra, Latest editions the same, and the shortest seat in your wallet counts. On a free seat it's 30 days. The clock starts the day the MLX is mined. Your wallet shows locked and available MLX side by side, with the exact unlock date for each day of mining.

Question 12

Can I buy MLX without a dedicated seat?

Accepted Answer

Yes. Deposit any coin, then buy MLX with your USDC in the wallet. The protocol fills every order along the same curve: buying pays the curve price plus a premium and moves the price up, selling MLX back to USDC pays the curve price less a discount and moves it down. Spot MLX is yours right away, with no lock.

Question 13

How does the wallet work without a seed phrase?

Accepted Answer

When you create a wallet, your device makes a passkey for mlx.app, protected by Face ID or Touch ID and synced through iCloud Keychain. Your signing key comes from that passkey, so signing in on another Apple device just works. You can export a 24-word recovery phrase at any time as a backup. We never see your key.

Question 14

Which seat should I get?

Accepted Answer

We size seats for your Mac: Core for Macs with a base M-series chip, Pro for Pro and Max chips, Ultra for Ultra chips, and the Latest edition of each for Apple's newest chips (M6, M5 Pro, M5 Max, M5 Ultra). Mining scales with price, so every seat mines the same MLX per dollar. A seat mines in full on a Mac of its class; a bigger seat on a smaller Mac mines at that Mac's class.

Question 15

How do I pay for a dedicated seat?

Accepted Answer

With crypto, from any wallet or exchange: USDC or USDT on Solana, Ethereum, BNB Chain or Tron, or SOL, ETH, BNB, TRX and BTC. Each checkout gets a unique amount, so we can match your transfer without an account on another site. Your seat is minted on the MLX ledger as soon as the payment confirms, usually within a minute. You can also deposit first: any coin you send arrives as USDC on MLX Network, and a seat bought from that balance is recorded instantly.

The Apple Silicon Supercomputer.

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