For the first time in history! Google TPU runs Gemma 4 in orbit.

"Write a haiku about being in space."

A few days ago, Google engineers sent such a prompt to a satellite orbiting Earth via a ground station.

Upon receiving the instruction, the TPU carried by the satellite booted up, and the pre-deployed Gemma 4 started to perform inference tasks. Later, when the satellite flew near the Svalbard Archipelago of Norway, the ground station finally received the response from space.

Blue marble below

Data streams in silent grace

Starlight feeds my core.

Not long ago, Google CEO Sundar Pichai excitedly shared this news, calling it the "Hello World" moment of Project Suncatcher. This is also the first time a data center-grade TPU has generated and transmitted back a complete AI response in orbit.

From announcing plans to send AI computing power into space last year to actually receiving a poem from orbit now, Google's space data center project has finally taken a step toward actual operation.

Google TPU is actually running in space

The starting point of this experiment dates back to a month ago.

On October 1, the Project Suncatcher prototype satellite, jointly developed by Google and satellite company Planet, entered Earth orbit aboard SpaceX's Transporter-18 rideshare mission.

In the following weeks, the engineering team successively completed the debugging of all satellite systems, started the host and TPU computing equipment, and carried out early machine learning tests.

Until this week, the team finally attempted to let the satellite perform a real generative AI task.

After completing the first response, the team also tried to get the model to generate other forms of space-themed poetry, and queried the technical status of the computing payload through natural language prompts. Google said that subsequent experiments will gradually shift to more practical system tests to observe the performance of TPU under orbital thermal stress and radiation environments.

According to TechCrunch, this prototype satellite is equipped with four Google TPUs, which can provide a maximum power of about 1kW. However, due to the current power supply limitation of the system, only one of the TPUs can be started at a time, and the running time is about 20 minutes.

This also reminds people of the scene when Google first proposed this plan a year ago.

In November 2025, we introduced this project in the article *AI Space Race? Nvidia H100 Has Just Been Launched into Space, and Google Project Suncatcher Will Also Send TPU to Space*.

According to the originally announced arrangement, Google planned to cooperate with Planet to launch two prototype satellites in early 2027 to test key technologies such as TPU in-orbit operation and inter-satellite optical communication. After that, Google further adjusted the experimental progress, used Planet's satellite platform to carry out the first phase of verification in advance, and successfully sent the TPU into orbit in October this year.

Google is not the first company to bring large models into space.

Last November, startup Starcloud sent the Starcloud-1 satellite carrying Nvidia H100 GPU into orbit, and later completed experiments on large language model operation and small model training based on nanoGPT.

In August this year, SpaceX and Nvidia announced another cooperation to develop Starmind AI1, planning to use Rubin GPU and Vera CPU to build a larger-scale satellite computing payload.

From Nvidia GPUs to Google TPUs, space AI computing is attracting more and more technology companies to participate.

From a single TPU to a real space data center

Why go to such great lengths to send AI chips into space?

This question has repeatedly appeared in the comment sections of various companies over the past year.

In fact, the answer is very simple, that is, power supply.

According to the previous research results released by Google, under appropriate orbital conditions, the power generation capacity of space solar panels can reach up to about 8 times that of ground conditions. If the satellite operates in a dawn-dusk sun-synchronous orbit, it can also get nearly continuous sunlight, and does not even need to rely too much on large batteries.

Around this goal, Project Suncatcher does not adopt the idea of building a large space station-style data center, but lets a large number of relatively small satellites form a close formation, each satellite is equipped with solar panels and TPUs, and then uses free-space optical communication technology to connect them together.

In the research paper previously published by Google, which has now been published in *Joule*, the team demonstrated an example of formation design composed of 81 satellites. These satellites operate in low-Earth orbit at an average altitude of about 650 kilometers, the radius of the entire cluster is about 1 kilometer, and the distance between some adjacent satellites varies within the range of about 100 to 200 meters.

Why make the satellites fly so close? Simply put, it is for the convenience of communication.

In ground data centers, large-scale model training usually needs to assign tasks to many accelerators to complete together, and different chips must frequently exchange intermediate calculation results. If the communication bandwidth is insufficient or the latency is too high, even if there are enough computing chips, the performance of the entire system may be severely limited.

Google hopes to move a similar distributed computing method to space, so satellites need to establish bandwidth connections that are much higher than the requirements of traditional satellite communications. According to the team's research, to achieve computing capabilities similar to ground data centers in the future, the transmission rate of inter-satellite links needs to reach 10 Tbps.

To approach this goal, Google is studying the use of dense wavelength division multiplexing and space multiplexing technologies to increase laser communication bandwidth, while allowing satellites to operate in a relatively close formation.

In previous ground experiments, the team has achieved a unidirectional transmission rate of 800Gbps and a total bidirectional transmission rate of 1.6Tbps through a pair of optical communication transceivers.

This is a fairly impressive figure, but there is still a gap from the inter-satellite communication capability required in the future. Moreover, the communication between ground equipment is completely different in engineering difficulty from maintaining a stable connection when multiple satellites are moving continuously at high speed in orbit.

In order to keep dozens or even hundreds of satellites in the proper relative positions for a long time, Google also needs to consider factors such as the non-spherical gravitational field of the Earth, atmospheric drag, and orbital perturbations, and assist formation control through physical models and machine learning methods.

At the same time, data exchange between satellites is only part of the problem, the problem of data transmission between the ground and satellites is more difficult to solve.

Especially for tasks that need to frequently read a large amount of ground data, update model parameters or respond to user requests, how to balance the communication window, transmission bandwidth and latency will also affect the actual operation efficiency.

In contrast, processing the data generated by Earth observation satellites in orbit, if image analysis can be completed directly in orbit, and then the results rather than all the raw data are transmitted back to the ground, there is an opportunity to reduce the downlink communication burden. This is the most advantageous field of space computing.

However, Google's goal is obviously more than that. It wants to verify whether it is possible to form a truly large-scale AI computing cluster in space in the future.

This idea has also been questioned by many netizens.

Previously, in the r/space community on Reddit, someone specifically raised a question: Since the construction and maintenance of space data centers are so difficult, why not place data centers on the seabed?

This question is not without practical basis. Microsoft's previous Project Natick has verified the operational feasibility of underwater data centers, and building data centers in cold regions such as Iceland and Northern Europe is already a practical choice to reduce part of the cooling burden.

The problem with going to space is that even if more solar energy can be obtained in space, is the computing power it can provide really worth such great efforts?

The answer is obviously not that simple.

Heat dissipation? Space radiation? Cost?

After the news was announced on October 30, discussions on the feasibility of space data centers on X emerged again.

User Luke Leisher said sarcastically: "How is this possible? Didn't the smartest people on the Internet tell me that the laws of physics have completely determined that orbital data centers are impossible to realize?"

Another user, Robert de Negro, raised a more specific question: The real difficulty may be scale. If a satellite is eventually equipped with a large number of computing devices, managing the heat generated by dozens or even hundreds of chips is completely different from managing a small number of chips.

At the end of the day, heat dissipation in space is still an unavoidable problem.

On Earth, computing devices can take away heat through air flow, liquid cooling and other methods, and the heat is finally discharged to the surrounding environment through corresponding facilities. But in space near a vacuum, there is no available air convection, and the waste heat generated by chips is finally released outward mainly by thermal radiation.

This means that space data centers must transfer the heat generated by computing devices to radiators with sufficient area through thermal conduction structures and cooling working fluids, and then discharge it in the form of electromagnetic radiation.

Google previously introduced a cooling scheme combining heat pipes and radiators, which has been tested in a thermal vacuum experimental cabin simulating the space thermal environment. Although this technical route is not new in the aerospace field, with the continuous increase of the power of computing equipment, the area and mass of the heat dissipation system and its structural relationship with other satellite equipment must be redesigned.

The prototype satellite of Project Suncatcher is currently equipped with four TPUs, but it can only start one at a time and run continuously for about 20 minutes, which just shows that the current power and thermal management capabilities still have much room for improvement before large-scale continuous computing can be realized.

Moreover, the heat dissipation problem will eventually come back to cost.

In the relevant discussions on Hacker News, some netizens believe that the controversy is not whether humans know how to dissipate heat through thermal radiation, but how many radiators, heat conduction pipelines and other supporting equipment need to be added to discharge enough heat. Once these extra weights are calculated, the launch cost of the satellite will also rise accordingly.

Another problem that needs long-term verification is space radiation.

For satellites that rely on solar power generation, sunlight is an important energy source, but radiation environments such as solar energetic particles and galactic cosmic rays may also affect electronic devices. When high-energy particles interact with sensitive areas in the chip, it may cause bit flips in the memory, turning the original 0 into 1, or causing errors in some calculation results.

In response to this, Google has previously carried out special ground experiments.

The research team used a 67MeV proton beam to test the sixth-generation Trillium TPU, and observed the effects of total ionizing dose and single event effect on the chip. The results showed that the high-bandwidth memory system is a more sensitive part, but related anomalies did not begin to appear until the cumulative dose reached about 2krad (Si), which is close to three times the expected 5-year mission dose under shielded conditions.

At the maximum test dose of 15krad (Si) for a single chip, the team did not observe any permanent hard failures that could be attributed to the total ionizing dose.

Such results make Google more optimistic about the space adaptability of existing TPUs, but after all, ground particle beam experiments cannot fully simulate the long-term radiation, thermal cycles and other complex factors in the real orbital environment. Therefore, one of the important purposes of this satellite mission is to further verify the performance of the chip in the real environment.

Even if both the heat dissipation and radiation problems can be solved engineeringly, Google still has to face the long-term maintenance and upgrading of computing equipment.

Ground data centers can gradually replace old equipment as the performance of AI chips improves, while power supply, network and cooling infrastructure can continue to be used. But for satellites, chips, solar panels, radiators and communication systems are often highly integrated. After equipment failures or computing chips gradually fall behind, how to continue to use the rest of the infrastructure becomes a complex problem.

Someone on Hacker News also specifically pointed out that space computing facilities may face a different depreciation logic from ground data centers: If the GPU or TPU on a satellite is no longer competitive, even if its solar panels and cooling systems are still usable, it may not be easy to continue to give full play to their original value.

This does not even take into account additional problems such as possible orbital debris and micrometeoroids that spacecraft may encounter, as well as the need for satellites to carry out regular orbital maintenance and final deorbit disposal.

Therefore, the debate about space data centers often ends up at the same problem: cost.

In the research paper previously published by Google, the future launch cost was specifically analyzed, and an important reference figure was given —— 200 US dollars per kilogram.

Under this assumption, after amortizing the launch cost according to the service life of the equipment and the power supply, it may correspond to a cost of about 810 US dollars per kilowatt per year.

As a comparison, the paper cites that the energy expenditure of ground data centers in the United States is about 570 to 3000 US dollars per kilowatt per year.

From this point of view, space data centers have a certain degree of feasibility. But Google's calculation is very rough, and some netizens on Reddit immediately saw the problem.

"Launch cost of 200 US dollars per kilogram?"

Google's calculation has a hypothetical premise, that is, the future rocket reusability and launch scale will continue to improve, and the cost downward trend observed in history can be maintained.

According to the paper's estimate, to reach the cost level of 200 US dollars per kilogram around 2