Nick Lothian
I wrote a new Agentic text-to-SQL benchmark and tested every local model I could against it: sql-benchmark.nicklothian.com Thanks to DuckDB WASM you can try your own models from the browser.
@ajfisher.social there are some interesting results in this for Inception Mercury 2 - it's certainly fast! See sql-benchmark.nicklothian.com#fastest-models for details around the issues I had with it.
I wrote a new Agentic text-to-SQL benchmark and tested every local model I could against it: sql-benchmark.nicklothian.com Thanks to DuckDB WASM you can try your own models from the browser.
Levels and Locks as Agent Orchestration primitives nicklothian.com/blog/2026/02...
Llama 3.1 8B running at 16,000 tokens per second on taalas.com custom hardware. umm yeah ok.
@timkellogg.me you might find x.com/AJakkli/stat... interesting: "What happens when you leave two copies of the same model talking to each other? They have different attractor states: Grok devolves into gibberish while GPT-5.2 starts writing code and editing imaginary spreadsheets"
Nemotron is a *great* model and the 3B and 12B models are free on OpenRouter for people to try out.
Nvidia’s Nemotron is the closest thing the U.S. has to a Qwen approach to open models, but most people don’t know it yet. I’m very bullish on Nvidia’s open model efforts in 2026. Interconnects interview #17 on the past, present, and future of the Nemotron project. www.youtube.com/watch?v=Y3Vb...
Looking for feedback on a new HTML tool I created, heavily inspired by @simonwillison.net's fantastic collection of HTML tools. LLM Comparator lets you try the same prompt on multiple LLMs, and continue the conversation across them. tools.nicklothian.com/llm_comparat...
Nick Lothian reposted
🚀Happy to announce my recent open source project- LightPHE: A Lightweight Partially Homomorphic Encryption Library for #Python. It allows computations on encrypted data without decryption. It wraps many algorithms such as RSA, ElGamal, Paillier and more! github.com/serengil/Lig...
Nick Lothian reposted
Replying to @neuroai.bsky.social
We evaluate the combined architecture on two challenging planning tasks: -Graph traversal -Tower of Hanoi Graph traversal: significant improvements over zero-shot prompting or in-context learning. Notably the architecture lowers hallucination of invalid moves to 0% (from ~20% for 4-step paths!) 4/n
You are up to date.