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AI social digest — 2026-10-06

2026-10-06 AI social

Top line: The X layer is product drip and benchmark noise today; the two things with signal both land on the models: a Perplexity decision-model update (pplx-decider-v1.1 — top score on the new HF Decision Index 0.3, price halved to $0.02/M, Arav's Oct 1 price-cut promise delivered in five days) and the Mistral Large 4 eval layer (blind human review #2 overall; 4,000 training GPUs vs Astra's 100,000). 2 kept as stories, everything else is brief-or-noise.


1. pplx-decider-v1.1: Perplexity's decision model bumps, halves its price

What happened: Perplexity Developers (~1:25 PM ET): pplx-decider-v1.1-27b, "our updated open weights multimodal decision model, is now available. It scores the highest on the new @huggingface Decision Index 0.3 benchmark" — pointing at the multimodalart/jev-decision-index space. Arav doubles down 20 minutes later (~4:46 PM ET): "Also, Perplexity Decision API pricing was cut by half, now to 2 cents per million input tokens. Enjoy!"

What's genuinely new: version bump (v1-27b → v1.1-27b), a claimed top score on a benchmark space Perplexity doesn't own, and the price halving to $0.02/M input — half the v1 price and half Jev's. Ledger item resolved: Arav's Oct 1 "we intend to bring down the price even further over the coming days" — delivered day 5, review-by (Oct 8) not yet due. The decision-models runner question (Jev vs AnyJev vs d1 vs OpenAI Decisions API vs pplx-decider vs Clef/Strands) gains a v1.1 cell; the independent run on identical labeled workloads still doesn't exist.

Watch: whether HF Decision Index 0.3 is the community's scoring harness (whose table wins); Jev/Cloudflare responses; still no runner.

Links: Arav

2. Mistral Large 4's eval layer: blind human review and the 4,000-GPU line

What happened: Mistral's announcement tweet + Surge AI: "For their Mistral Large 4 release, @MistralAI ran a blind Surge human eval... five frontier models on coding quality. Le Chonk ranked #1 among open-weight models and #2 overall, behind only Opus 5." — with Surge's framing: "Unit tests ask: does it work? Human code review asks: would you merge it?" Peter Gostev (RT'd by LeCun, 9:58 AM ET) supplies the disparity metric: "Mistral Large 4 was trained on 4,000 GPUs and Astra was trained on 100,000 of them. We'll see what the kitten can pull off..."

What's genuinely new: the X layer of the release covered in today's ai digest (story 6) — the eval genre here is blind human code review, not a benchmark board, and the compute-disparity frame is doing the anti-scaling-narrative work. Vendor-run and vendor-floated numbers, both disclosed as such.

Watch: independent runs once weights circulate; whether the blind-human-eval announcement move spreads.

Links: Surge/Mistral · Gostev RT via LeCun (no link captured in feed)

3. Grok Bot's platform hooks: @bot tagging goes live; Creator Rewards

What happened: (1) Larsen Cundric (RT'd by Musk, 7:38 PM ET): "@bot tagging just went live" — reply to any post with "> @bot add this to my Notion reading list," "@bot remind me to read this tomorrow," "@bot summarize this thread," "@bot draft a reply" — working in replies, posts, quote-tweets, "lands right in your Grok Bot." (2) Sawyer Merritt (RT'd by Musk Oct 5 6:27 PM ET, landed after our Oct 5 cut): Grok @Bot Creator Rewards — biweekly, usage-based rewards for template creators. (3) A public changelog now exists: x.ai/changelog/bot.

What's genuinely new: the consumer-agent surface keeps accreting hooks into third-party surfaces — Notion named in the tagging examples is integration color, and a changelog channel is the platform-ization tell. Continuation of the Grok Bot cadence strand (agent-harness race thread). X-grade; no docs beyond the changelog link.

Watch: what the changelog itemizes; whether Dots/Dots-equivalents get the same reply-hooks; reward economics in practice.

Links: @bot tagging RT · Creator Rewards RT

Brief

Dropped