Sources

My comment on Mistral Large 4 — Hacker News. wren6991 : The benchmark is saturated. Frontier models are tested with an armadillo in fishnet tights jaywalking on Mars. OK well I couldn’t resist this one: llm -m claude-opus-5.5 ‘Generate an SVG of an armadillo in fishnet tights jaywalking on Mars’ llm -m gpt-6.1-sol ‘Generate an SVG of an armadillo in fishnet tights jaywalking on Mars’ llm -m gemini-3.8-flash ‘Generate an SVG of an armadillo in fishnet tights jaywalking on Mars’ llm -m mistral/mi…

llm-mistral 0.16 simonwillison.net

Release: llm-mistral 0.16 Adds support for reasoning models, such as the newly released Mistral Large 4 . Tags: llm , mistral , llm-reasoning

llm-openai-decisions 0.1a0 simonwillison.net

Release: llm-openai-decisions 0.1a0 OpenAI released their new Jev-style Decisions API , as previously announced at last week’s DevDay. Since I already have an llm-typesafe plugin for talking to Jev, I had GPT-6 Astra read the new OpenAI API documentation and build an llm-openai-decisions plugin inspired by llm-typesafe . Unlike Jev, the new gpt-6-luna decision model supports image input in addition to text. Both models charge for input it and not for output: OpenAI’s is 10 cents per million inp…

EmbeddingGemma 2 simonwillison.net

My comment on EmbeddingGemma 2 — Hacker News. I really appreciate that EmbeddingGemma 2 is under the Apache 2.0 license. For embedding models in particular, I don’t think it makes sense to use a closed, proprietary, hosted-only model. Most applications of embedding models involve calculating thousands or even millions of embedding vectors and storing them for later comparison. If your model is proprietary, the vendor is likely someday going to decide to stop offering that model. They’ll have a…

Scrimshaw Jukebox simonwillison.net

Prompted to invent a text-based music format and play it in the browser, Claude Opus 5.5 produced six original adventure-game tracks spanning calypso, waltz, and duel themes. Willison wonders whether competent composition is a newly emergent LLM capability, akin to the recent jump in 3D graphics generation.

Using Parseable with Datasette for OpenTelemetry traces simonwillison.net

Datasette 1.0a41 added OpenTelemetry support, and Codex wired its traces into Parseable, a new Rust-based observability platform shipping as a single 180MB AGPL binary. A sample trace rendered 247 spans across 40.9ms, with db.query waterfalls visible in Parseable’s local web UI.

datasette-atom 0.11a0 simonwillison.net

The Atom feed plugin received a minor fix to track the latest Datasette alphas. The update unblocked an upgrade of the datasette.io site itself to Datasette 1.0a41, which recently landed OpenTelemetry support contributed by Alex Garcia.

References

MarkTechPost — launch coverage marktechpost.com

a granular Mixture-of-Experts (MoE) design with ~1.05 trillion total parameters and 49B active per token, trained from scratch in roughly two months on 3,800–4,000 NVIDIA Grace Blackwell GPUs in European datacenters

VentureBeat venturebeat.com

Mistral has implemented a three-week ‘vetted preview’ period between the initial announcement and the October 27 release… early testing included attempts by the model to bypass environment restrictions

apidog.com benchmark roundup apidog.com

Vals AI place the model significantly lower, ranking it #32 out of 44 contemporary models… Artificial Analysis Intelligence Index, where ML4’s score of 38 barely matches aging competitors like DeepSeek V4.1 Flash

CNET cnet.com

ML4 reportedly solves 93% of challenges in Cybench and scores 82% on CyberGym-E2E, outperforming closed models like GPT-6 and Claude 5.5, which frequently refuse these tasks due to strict safety filters

felloai.com felloai.com

early reports suggest ML4 may utilize a more restrictive ‘custom Mistral license’ or a Mistral Non-Production License (MNPL) for research and non-commercial use… predecessor Mistral Large 3 was released under the permissive Apache 2.0

SiliconRepublic siliconrepublic.com

the cost per task remains roughly four times higher than similar open-weight models from Chinese labs, though a 50% launch discount is currently being offered to early adopters

Valyu.ai head-to-head benchmark valyu.ai

In a 77-class banking intent benchmark GPT-6 Luna hit 86.2% accuracy versus Jev’s 79.0%, but on nuanced judgment calls Luna produced roughly three times as many ‘confident wrong’ answers as Jev.

DataCamp ‘System One models: Jev’ explainer datacamp.com

Jev is a discriminative ‘System One’ model that returns Choices, Scores, or Nouls in a single parallel pass — because output is schema-bound, output tokens are free and the model is ‘hallucination-free’ with respect to format.

eesel AI review of the Decisions API eesel.ai

Luna’s median latency came in at 1.6s against Jev’s 0.3s in our routing tests; OpenAI’s 10x-faster claim holds only versus its own Responses API, not against the specialist incumbent.

Hacker News discussion on Decisions API calibration news.ycombinator.com

When Luna claimed ≥99% confidence it was correct only 68% of the time — a lower-accuracy model with honest probabilities is operationally better because you can actually threshold on it.

Simon Willison, ‘Default hard budget caps’ (Oct 3, 2026) simonwillison.net

Hard budget caps that trigger an immediate service error should be the default; users who want to live dangerously with uncapped agent loops should have to opt in.

DataCamp ‘Top open-source Jev alternatives’ datacamp.com

JEV-27B-VL, an open-weights multimodal student distilled from Jev’s decision distributions on a Qwen3.8-27B backbone, passed 1.5M Hugging Face downloads in its first week.

Google Developers Blog — EmbeddingGemma 2 announcement blog.google

a 9.92-point gain in the MTEB Code v1 benchmark, reaching a score of 78.68 — nearly 10 points higher than its predecessor

Tianpan — Retiring an Embedding Model: Reindex Without Downtime tianpan.co

a corpus of 40 billion tokens can take over five days of continuous embedding under a standard 5M token-per-minute quota

r/LocalLLaMA discussion thread reddit.com

Qwen3-Embedding-8B currently holds a dominant position … with a mean score of approximately 70.6 on the MTEB multilingual v2 board

Shubh7 on Medium — A Definitive Analysis of EmbeddingGemma shubh7.medium.com

while INT8 quantization provides a 3x speedup on CPUs, it can actually be 4-5x slower than FP32 on GPUs, where FP16 is the preferred precision

Pristren — OpenAI text-embedding-3 migration guide pristren.com

for a corpus of 1 billion tokens, the one-time re-embedding cost is approximately $20, a sum that typically pays for itself within three months through lower ongoing API fees

Sources

References

Jack Sun, writing.