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Issue 22: Power Queues and Open Weights

Permanent copy of issue 22. Today's issue is always the front page.

Central clusters keep ordering chips and power, but open laptop-scale weights and local runtimes now divert measurable work from paid APIs.

Date: 2026-08-25
Updated: 2026-08-25 02:00
Status: LIVE

Broadcast

Central operators keep ordering chips and building power plants while token prices fall and open-weight releases continue. Grid queues and capex ratios show the scale of the central buildout. At the same time, local runtimes and new open models give developers workable alternatives on laptops and small clusters. The gap between list API prices remains wide, but the share of work that can avoid those prices is growing. The direction of capital is still central; the direction of runnable weights is not.

Watch

• Texas grid queues for new data centers
• Hyperscaler capex above 100% of cloud revenue
• New open-weight coding model release

Stories

Hyperscalers' Off-Grid Power Push Comes With Risks
Hyperscalers are building behind-the-meter generation to bypass grid queues. The move raises fuel, emissions, and permitting questions.
Central operators are spending heavily to secure power, widening the gap between grid-tied local clusters and hyperscale builds.
2026-08-20 / WSJ / energy, chip / central

AI's Absurd Spending Boom? Hyperscalers Are Spending 102% of Cloud Revenue on Capex
Cloud revenue growth no longer covers AI hardware outlays. The ratio signals sustained central concentration of spend.
Capex at 102% of revenue locks capital into large clusters and delays any shift of workloads to smaller local sites.
2026-08-22 / Yahoo Finance / chip / central

Best Local LLM Tools in 2026: Runtimes, Apps, and Agents
New runtimes and agent frameworks target Apple silicon and consumer GPUs. Developers report usable inference speeds on laptops.
Local inference tools lower the cost of running open-weight models on personal hardware, pulling work away from paid central APIs.
2026-08-19 / StorageReview.com / efficiency / local

Poolside Launches Laguna S 2.1 Open-Weight Coding Model
A new 200B-class open-weight model targets code completion and agent tasks. Weights are released under a permissive license.
Open weights allow organizations to run code models locally or on private clusters, reducing reliance on central token APIs.
2026-08-24 / HPCwire / efficiency / local

Axis
local [##################------------] central
Score: 61   clusters still winning   -1 toward local this week
Most AI still runs in big central data centers, but open-weight models and on-device runtimes are taking some work off paid APIs.

Forces

Line charts (0=local 100=central 2026-08-10 to 2026-08-25)

Market overlay (2026-07-27 to 2026-08-25)

Latest: BTC $80,681 / hashrate ~866.35 EH/s / token markers avg $5.3033/M / axis 61. These lines are different units. We compare timing, not dollars-to-hashrate.

Not shown: GPU cloud $/hour, hub electricity, miner hashprice, or lab cost per token -- none of those are a clean public feed.

Power and list prices
BTC $80,681 / hashrate ~866 EH/s. List-price gap (not a subsidy %): 44.4x list gap (blended) GPT-5.6 Luna -> Claude Fable 5 ($0.45/M to $20.00/M). (mempool.space + Coinbase/CoinGecko)

Marker prices (USD per 1M tokens; verified 2026-08-19; blended = (3*input + 1*output) / 4; -- = open/self-host or no single public list)

Full 20-model board

If useful, support the broadcast.
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