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.

Balatro proved poker could be a rogue like. I'm proving Air hockey can too. #indiedev #indiegame #indie #gamedev #game #indiegamedev

Back in my hometown for the holidays. 32°C+ every day… Hell mode enabled 🔥

🎄🎄🎄🎄🎄

run with the colors of the wind 🍃🦋

Finished Path of Pain in Hollow Knight. Mostly patience, repetition, and refusing to quit 🫡🫡 Despite the insane difficulty, the whole journey felt strangely calm, almost like a safe space

Boss fight wip!

Rule 1: Don’t die Rule 2: Never trust plants

We published a new devlog which goes into how we do art for enemies! Link below 👇

Wait, what?! 😻😻

Here’s a pic we took while we were getting ready to showcase Randel’s Quest at a great venue in Buenos Aires: Palermo Wine Club! 🫂 (There was also the awesome Kenzu by @gamesbyforge! Have you tried their demo yet?)

A new release of our metroidvania is out! 🍃 We developed a new biome, which included not only making concepts and assets for the backgrounds 🍃 We changed how we draw terrain: we were using Tilemap assets which the artists found difficult to work with to get the results they wanted, and we switched to 9-slice which is much more intuituve for the team to create beautiful hand-painted terrain. 🍃 We created new enemies and platforms for this biome. In order to progress more quickly, we're taking advantage of opportunities to reuse animations for similar enemies. After all, other games like Blasphemous have enemy variations that only change color palettes. So far we decorated just a few rooms of the biome as a test. The others are raw, without art. Try to discover the nice ones! 🍃 Game saves. With this new update, you'll be able to save your game on Itch! We'll be testing it but please let us know if you experience any issues. 🍃 Custom keybinds. Today we're adding customizable keybindings only for the main keys: - Jump - Attack - Parry We're sorry for the delay in making fully customizable keybindings, which we plan to deliver early next week. 🍃 Asset quality improvements We improved how assets are loaded so that they don't show up pixelated. And that's it! We hope you enjoy the new biome as it develops. Please leave a rating and comment if you like it, it helps us a lot! Thank you as always, The Dev Team 😸

Hope you’re ready, because biome 2 is going to be wild (wild ’cause it’s a forest, cuak)

Who does it remind you of?