LLMs now make critical decisions in hospitals, defense, banks, and governments. Yet nobody can verify which model actually ran, or whether the output was tampered with. A provider or middleman can swap weights, silently requantize the model, alter decoding, inject hidden prompts, do supply chain attacks, or change the deployment surface without the user knowing. This problem is already serious. It will become critical. We think this needs a practical solution, not just a theoretically clean one. CommitLLM is designed to be deployable on existing serving stacks now: the provider keeps the normal GPU serving path, does not need a proving circuit, does not need a kernel rewrite, and does not generate a heavy proof for every response. In practice, two families of approaches dominated the conversation before this work: fingerprinting, which can be gamed, and proof-based systems, which are theoretically strong but too expensive for production inference. We built CommitLLM to target the middle ground. The core idea is to keep the verification discipline of proof systems, but specialize it to open weight LLM inference. The cryptographic core is simple: Freivalds style randomized checks for the large linear layers, plus Merkle commitments for the traced execution. Then a lot of engineering work is needed to make that line up with real GPU inference. The key trick is this. A provider claims `z = W × x` for a massive weight matrix. Normally you would verify that by redoing the multiply. Instead, the verifier samples a secret random vector `r`, precomputes `v = rᵀ × W`, and later checks whether `v · x = rᵀ · z`. Two dot products instead of a full matrix multiply. In the current implementation, a wrong result passes with probability at most `1 / (2^32 - 5)` per check. A full matrix multiply, audited with two dot products. Most of the transformer can then be checked exactly or canonically from committed openings. Nonlinear operations such as activations and layer norms are canonically re executed by the CPU verifier. The one honest caveat is attention: native FP16/BF16 attention is not bit reproducible across hardware. CommitLLM verifies the shell around attention exactly, then independently replays attention and checks that the committed post attention output stays within a measured INT8 corridor. So attention is bounded and audited, not proved exactly. That means the protocol already gives very strong exact guarantees on the parts that matter operationally most. If an audited response used the wrong model, the wrong quantization/configuration, or a tampered input/deployment surface, the audit catches that exactly. That includes things like model swaps, silent requantization, and provider side prompt or system prompt injection. Today the implementation and measurements are strongest on Qwen and Llama. But the protocol itself is not meant to be Qwen or Llama specific: we expect it to generalize across open weight decoder only families. What still has to be done is the engineering work to integrate and validate more families explicitly, and we are already working on that. On the measured path, online generation overhead is about 12 to 14% with the provider staying on the normal GPU serving path. The heavier receipt finalization cost is separate and can be deferred off the user facing path. The main systems costs are RAM and bandwidth, not proof generation. The full response is always committed, but only a random fraction of responses are opened for audit. Individual audits are much larger, roughly 4 MB to 100 MB depending on audit depth. The important number is the amortized one: under a reasonable audit policy, the added bandwidth averages to roughly 300 KB per response. After too many weeks without sleep, I’m proud to show what I built with @diego_aligned: CommitLLM. Thanks Diego for your patience. I've been calling you at random hours. The code and paper still need some cleaning and formalization. We’re already in talks with multiple providers and teams that have cryptography related ideas on how to improve it even more. We’re really excited about this and we will continue doubling down on building products in AI, cryptography and security with my company @class_lambda. If governments, hospitals, defense and financial systems are going to run on LLMs, verifiable inference is not optional. It is infrastructure. I will be explaining this in more details in the days to come and I will show how to test it and run it.

Argentinean coach teaching the US how to play great futbol.

both are annoying

Ethereum can already start preparing accounts for a post quantum world, without waiting for a hard fork. Today, it would be just 0.07$ . Further audits incoming. Though I squeezed in a review with Fable before Uncle Sam crashed my party. Verity formal proof included for my lean enjoyers ethresear.ch/t/sphincs-minus…

Congrats to the US for the win against Paraguay. Pochettino 🇦🇷 is teaching the US how to play futbol!

Argentina, Colombia, Ecuador, Uruguay, Paraguay and the US have argentinean coaches! Argentine coaching school, Bielsa/Menotti/Bilardo lineage running through almost all of them.

Let's do it.

It's been only a couple of days since @ethrex_client started running the new benchmarkoor BAL suites, and it's already among the top three clients in both benchmarks. Ethrex currently leads the compute suite at ~1.95 Ggas/s gas-weighted aggregated throughput, ahead of every other execution client. We've also made a strong jump in the stateful suite, moving into second place. There’s still plenty of room for optimization, but Glamsterdam is already looking very promising. Ethereum will win. @class_lambda will fight for this to become a reality.

Ethrex @ethrex_client doing almost 2 gigagas/s. I've been saying it for the last year and a half. Ethereum is gonna win.

sometimes money and "genuine, positive, non-zero sum value creation" are not highly correlated, and sometimes they *really* are. well-earned!

ETH investor Stanley Druckenmiller: “Our whole payment system will be stablecoins in 10-15 years” BitMine (BMNR), the ETH treasury company chaired by Tom Lee, holds almost $10 billion of ETH. Legendary investor Stanley Druckenmiller is listed among key backers like Founders Fund, ARK's Cathie Wood, and Bill Miller. This aligns with his recent bullish comments on stablecoins and blockchain payments: “Blockchain and the use of stablecoins — if you want to throw crypto and tokens into that — are incredibly useful in terms of productivity. I assume our whole payment system will be stablecoins in 10-15 years. Efficient. Quicker. Cheaper.”

My favorite @elonmusk quote that I often send friends: Do not fear losing. “You will lose,” Musk says. “It will hurt the first fifty times. When you get used to losing, you will play each game with less emotion.” You will be more fearless, take more risks.

i still can't understand why people say tradfi has better ux. not only fees are insane but also you have zero visibility of what's happening in a slow and expensive process. for millions of users even sending 200usd that are flying around without any transparency can generate a lot of stress. few things make people more anxious than moving money without knowing what's happening. that's the case for 200usd or 2M usd.

i still can't understand why people say tradfi has better ux. not only fees are insane but also you have zero visibility of what's happening in a slow and expensive process. and for millions of users even sending 200usd that are flying around without any transparency can generate a lot of stress. few things make people more anxious than moving money without knowing what's happening. that's the case for 200usd or 2M usd.

Github repo: github.com/AbdelStark/Provab… Explainer website: abdelstark.github.io/Provabl… Built on LeWorldModel by @lucasmaes_ , extending LambdaClass's @fede_intern CommitLLM commit-and-audit scheme from LLMs to world models.

Darlings what are you guys waiting? Don't miss the boat, this will take over everything. Join us and build your own PropAMMs. Ethereum will take over. @ambergroup_io @keyrock @FlowTraders @CyantArb @wintermute_t @GSR_io @SeliniCapital @Auros_global @JumpCrypto @PortofinoTech @ManifoldTrading @Arbelosxyz @GalaxyHQ

amazing quote

We're fighting in every front. We will make sure @ethereum wins in every front.