An 18MB KV-cache bank rewrites a model's behavior at runtime — no weights touched, unloadable anytime.
Top Signal
An 18MB KV-cache bank changes model behavior with zero weight edits
research to practice
r/LocalLLaMA
An r/LocalLLaMA post demonstrates training a small bank of KV-cache entries (~18MB), injecting it into a model's context state at inference to shift refusal behavior without modifying weights — and unloading it at will. The uncensoring demo is the least interesting part. What matters is the shape: a runtime-attachable behavior module with no merge step, no separate checkpoint, and no base-model reload. If it generalizes past refusal steering to tone, format compliance, or domain priors, you get per-request personality swaps on a single loaded model — a serving pattern that today requires adapter hot-swapping. Caveat: one source, one demo, no independent reproduction yet. What to do: watch for someone reproducing it on an instruct model at long context and measuring quality drift outside the target behavior. Bookmark it as the cheapest known lever for behavior control when fine-tuning isn't on the table.
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Fast Signals
Xiaomi drops MiMo v2.6 weights: Flash-RL, Pro-RL, and a 9B Qwen distill
new tool
HN Front Page, r/LocalLLaMA
Xiaomi published the full MiMo v2.6 family to Hugging Face — Flash-RL, Pro-RL, and Distill-Qwen-9B — five days after streaming its RL post-training run live. The 9B distill is the one to grab: RL-trained reasoning at a size that fits a 12GB card. Comparison threads against other open-weight models are already up; wait for independent evals before swapping anything into production.
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Willison and TypeSafe's CEO finally explain what Jev actually is
emerging signal
Simon Willison, Latent Space
Simon Willison published a full explainer on Jev's "System One" decision-model shape, and Latent Space ran an interview with TypeSafe AI CEO Diogo Almeida the same day. After a week of benchmark chatter, this is the first coherent account of the architecture and its purpose: fast, narrow decisions in production rather than open-ended generation. Read both before deciding whether a decision model should replace a classifier or a small LLM call in your stack.
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Cloudflare Python Workers hit GA after a two-year preview
platform change
Simon Willison
Python is now a first-class, fully supported Workers runtime rather than a beta. Edge-deployed Python glue — webhook handlers, LLM proxies, retrieval shims — becomes a production option with no container. If you've been wrapping Python logic in JS to get it to the edge, delete the wrapper.
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Linear rebuilt its CI because agent-written PRs swamped it
workflow
HN Front Page
Linear published a concrete writeup of how AI-assisted coding turned CI into the team's bottleneck, and what they changed to absorb the volume. This is the second-order cost nobody budgets for: agent throughput is nearly free, your test runners are not. If your team adopted coding agents in the last six months, read this before your next CI invoice.
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Vercel Labs open-sources json-render for generative UI
new tool
GitHub Trending
A framework for having models emit JSON that renders into real UI components instead of markdown blobs. It targets the structured-output-to-interface gap directly. Worth an evaluation if you're currently hand-rolling a renderer for tool results or LLM-generated forms.
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A 100M-parameter text-to-image model claims SOTA-tier output
new tool
r/LocalLLaMA
Open release of Supra2-IMG, a 100M text-to-image model — orders of magnitude smaller than the diffusion models most apps call out to. If the quality claims survive other people's prompts, on-device and per-request image generation gets cheap enough to stop being an API line item. Treat the SOTA claim as unverified until someone outside the release thread posts comparisons.
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r/LocalLLaMA argues 16GB is the VRAM ceiling that actually matters
emerging signal
r/LocalLLaMA
A heavily-upvoted thread makes the case that 12–16GB is the realistic maximum most users will ever have, landing the same day as more RAM/GPU price-hike posts and news that Huawei shelved its global AI chip rollout. If you ship local inference, treat 12–16GB as the target envelope rather than 24GB. The memory price shock is now a product constraint, not a hobbyist gripe.
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Radar
lossless-memory: an AI memory that never summarizes
A Show HN repo betting that compaction is the bug, not the feature — it stores everything and retrieves instead of summarizing. A useful counter-position now that compaction summaries are a known correctness and prompt-injection surface.
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mini-AGI: continual learning trained on one 8GB card
A solo dev's dynamic continual-learning model, deliberately scoped to 8GB VRAM. The name oversells it; the constraint is what makes the experiment worth reading.
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Stanford's CS146S assignments are public on GitHub
The assignment repo for "The Modern Software Dev," Fall 2026. A free, structured curriculum for getting a team fluent in agent-assisted development instead of learning it by anecdote.
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yandex/AliceAI-Foundation-80B-A3B-Base lands open
An 80B A3B MoE base model positioned against Qwen 35B and DeepSeek V4 Flash. Base, not instruct — relevant only if you fine-tune, but another data point that the open MoE floor keeps rising.
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Convergence Watch
jev
TRENDING
2 mentions across Simon Willison, Latent Space
Fourth straight day in the feed, and the coverage has shifted from benchmark chatter to architectural explanation — Willison's explainer plus a founder interview on the same day. That transition, from 'what scores did it get' to 'what shape is it,' is usually when a category becomes real. The term to watch is 'decision models.'
xiaomi mimo
5 mentions across HN Front Page, r/LocalLLaMA
Five mentions across two independent sources in one day — HN front page plus four separate r/LocalLLaMA threads covering Flash-RL, Pro-RL, the 9B distill, and comparison charts. This is a release-day spike, not sustained momentum: MiMo last appeared on 09-16 when the RL run was streamed. Revisit in three days to see whether the evals hold.
local hardware capex
TRENDING
4 mentions across r/LocalLLaMA
Fifth day in seven. Today's four threads — price-hike complaints, the 16GB-ceiling argument, Huawei shelving its global chip rollout, and an M5 Ultra review — all converge on the same conclusion from different angles. Single-source, so discount accordingly, but the consistency matters: memory scarcity is shaping which models people can actually deploy.