A Combine energy cabinet at golden hour in dry grassland, beside a row of solar panels, its etched mark and status light in sharp focus.
Solar-assisted compute for small AI labs

Intelligence powered by sunlight.

Combine is a practical way for independent builders and small teams to adapt open-weight models and run private AI on their own hardware, powered mostly by the sun.

Energy model validated against NREL SAMLab, yard and data center scalesOpen model, data and code

One workstation, one solar array, one battery. Fine-tune and run your own models on energy you can see, with the grid as backup.

A small lab node: about 2 kWp of panels, 5 to 15 kWh of storage, and one accelerator workstation. Flexible fine-tuning work moves into the sunniest hours. Private inference runs through the working day.

Validated · 2 November 2026

Numbers you can check, in public.

We validate our energy model against two industry-standard open solar models, pvlib and the NREL System Advisor Model, on real hourly weather, and every sizing on this page uses the result.

2.5%

pvlib and NREL SAM agree within 2.5% on the same weather, at every site.

pvlibNREL SAMkWh per kWp a year
5–8%

Output lost to panel heat at hot sites, now built into every sizing.

Heat lossMean daytime cell temperature
~97%

Modelled solar share of a full year's load for a 2 kWp, 5 kWh node. The gap sits in the rainy months.

Solar, kWh a dayDaily load, 6.7 kWh
7–20%

How far two satellite records differ on sunlight at the same place. We size against both.

NASA POWERPVGIS SARAH2kWh/m² a day
One idea, three scales

From one workstation to a yard to a campus.

Pick a scale, watch it, then change the inputs and see what capacity it takes. Every result shows its working.

Your model. Your workstation. More sunlight.

Adapt an open-weight model to your domain, train a small model, or run private local inference on a solar-assisted workstation.

Presets set typical power and session length for each workload. Solar yield is 75%, validated against NREL SAM for hot sites. Sessions are placed in the sunniest hours.

0%Daily coverage
Solar a day-
Session energy-
SolarWorkstationFrom storage or grid

The node

Three parts. Each one modelled, none of it hidden.

Accelerator workstation

  • One 600 W class accelerator
  • Parameter-efficient fine-tuning and private local inference
  • Energy-aware scheduling moves flexible work into sunny hours
G1 finding

Energy-aware scheduling earns its place. In the tightest modelled case it cuts grid import from 286 to 107 kWh a year by moving flexible sessions into sunnier days.

The Combine workstation beside a developer's desk in a sunlit studio, its etched mark and green status diamond lit.
Inside the chip

A proposed energy management block. Explored in simulation only.

Initial systems use existing accelerators. Custom silicon follows workload validation and a feasibility decision. We claim no RTL, no EDA licence and no tape-out.

Stage 1

Set targets from a measured system baseline: the energy model, then real workload traces.

Stages 2 to 4

Simulation-only exploration of a small scheduling and power control block.

Gate

A written feasibility note says what would justify or end the silicon path.

Evidence sprint · Nov to Dec 2026

Build. Measure. Earn the next step.

Done

Baseline

Energy model v1, 54 scenarios, published with its assumptions.

Done early

Model check

pvlib and NREL SAM cross-check. Findings corrected the same day.

Next

Measure

Real power and memory traces for fine-tuning and inference on a cloud GPU.

Planned

Scheduler and twin

Replay on measured traces. Scope a digital twin of one node.

Planned

Silicon gate

Feasibility note for the energy management block, simulation only.

Planned

Build

Build the first production node from the measured design.

Solar Atlas

Where could sunlight support more compute?

The atlas maps NASA POWER climatology for candidate regions. Our cross-check found that a second dataset can disagree by up to a fifth at the same point, so every site is sized against both.

Open the Atlas
NASA POWERPVGIS SARAH2
Douala
+17%
Accra
+20%
Addis Ababa
−7%

Bars scaled to 7 kWh/m²/day. Validation reference points.

FAQ

Plain answers.

Who is Combine for?

Independent builders and small LLM labs who want to fine-tune and run their own models on hardware they control, with energy they can see. The same system scales to yards and data center campuses.

How accurate is the energy model?

We validate it against pvlib and NREL SAM on real hourly weather. That work built panel heat into every yield figure and made storage sizing follow seasonal demand. The model, data and code are open, so anyone can rerun it.

Where can I read the full story?

In the founder's letter: why Combine exists, where it stands and what comes next.

What would a pilot involve?

One open-weight model, one agreed quality bar, and whole-workstation power measured on a conventional supply before any solar is added.

Get started

Bring one model. Let's test its potential.

Tell us what you want to fine-tune or run privately. We will size it against the model and share the numbers.

Discuss a Pilot