The Compute Bazaar: Tinkering with Compute Markets
this is just me iterating on the article before i fill in and finish the project, lorem ipsum for now. see oudau project article for now, see oudau for now.
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I Tinkering
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Price history
Four Prime shelves against one broader market
Prime Intellect lists requestable H100, H200, B200, and B300 machine configurations from named upstream providers. Each hour I keep one lowest eligible secure, on-demand base rate per provider and take their median, so one provider does not receive more weight for listing more machine shapes. Beside it sits the Compute Bazaar benchmark built from all eligible providers in the wider feed.
The shelf shows exact returned configurations, grouped into quarter-dollar display levels. It can show a configuration entering, remaining, repricing, or leaving public availability. Prime does not publish posted GPU quantity, fills, cancellations, or remaining volume here, so those fields are left blank rather than inferred.
Hourly observations come from Prime Intellect's GPU availability API, whose rows name the upstream provider and configuration. Open the matching Prime GPU catalogue to inspect what can currently be requested.
Price, available capacity, and one measured software job
Each row keeps unlike measures apart. Prices and estimated job cost sit on the left; available share or measured runtime sits on the right. GPU and CPU observations update with the hourly market run. The sandbox row advances only when StarSling publishes another compatible public benchmark batch.
Four vCPUs and 8 GiB, before and after the sandbox layer
A sandbox is managed software wrapped around compute capacity. To see both layers, I track one exact four-vCPU, 8-GiB public VM offer from Akamai Linode, Vultr, Scaleway, Microsoft Azure, Amazon EC2, OVHcloud, and Oracle Cloud, then compare their median with the public processor-and-memory rates of managed sandboxes at the same requested shape. These are observed offer rates, not transaction prices, capacity guarantees, or invoices.
Both lines use fixed membership, with the median as the headline and the 25th–75th percentile as the band. The seven-vendor VM series starts with its first complete hourly check; the earlier four-vendor evidence remains in the dataset but is not relabeled as seven-vendor history. Every complete check is retained even when prices are unchanged. Regions, CPU models, tenancy, burst policy, storage, networking, lifecycle management, and delivered work still differ. VM storage treatment is shown row by row. The sandbox comparison covers processor and memory only. See the sources and dated changes.
Inspect the seven underlying VM offers
Current vendor offers
four vCPUs · 8 GiB · Linux on-demand| Provider and plan | Region | Observed rate | CPU, tenancy, and storage | Original source |
|---|
Marketplace indication
shown separately · not included in the VM medianAkash is a request-specific monthly estimate normalized over 730 hours for four CPU units, 8 GiB of memory, and 20 GiB of storage. It is not a live provider bid, lease, or executed price, so it is not mixed into the seven-vendor VM median.
Managed sandbox rate cards
same requested shape · processor and memory rates onlyWhat moved the line
effective dates where stated; observed bounds otherwiseAudit all 33 dated price observations
| Service | Date | Normalized rate | Billing basis and date meaning | Original source |
|---|
The VM cohort is Akamai Linode, Vultr, Scaleway, Microsoft Azure, Amazon EC2, OVHcloud, and Oracle Cloud. The managed sandbox cohort is E2B, Daytona, Vercel, Novita, Modal, Runloop, Blaxel, and Fly Sprites. An effective date is stated by the provider. An observed time is when our hourly source check retrieved the quote; it does not invent an earlier price history. Read the maintained methodology and source register.
What the same software job costs on each sandbox
Hourly rates still do not tell us what a completed job costs. The public StarSling HPC Sandbox Benchmark ran ten pinned Better Auth development workload on fresh sandboxes. For each complete job, I multiply its measured phase seconds by that service's matching public processor-and-memory rate. The result is an estimated cost for the same pinned software work on six services.
The latest comparable batch has 72 provider-and-job slots. Sixty-nine contain all ten measurements and appear below; three incomplete slots remain missing rather than estimated. The estimate is: measured seconds ÷ 3,600 × the matching public hourly rate. It covers processor and memory only. It is not an invoice and excludes startup, teardown, retries, storage, network, credits, and minimum billing increments.
Measured time remains underneath the estimate as auditable evidence, not the headline. The primary chart ranks cost and retains every complete job plus each service median and middle 50%. Seven source batches over five calendar days remain in the audit record, but their six harness revisions are not joined into one false performance history.
Cost ranking
median job estimate · matching public hourly rateInspect measured time behind the cost estimates
Where the timed work went
sum of phase medians · three largest shares shown| Service | Job | Measured phase time | Marginal estimate | Original batch |
|---|
Earlier source batches: 38 provider-batch summaries
| Service | Batch time | Mean measured phase time | Samples per task | Harness method | Original batch |
|---|
This answers a narrow question: how long the pinned tasks ran and what those measured phase windows would cost at the matching public rate. It does not measure time-to-ready, client-visible latency, concurrency, reliability, storage, network, plans, credits, or the final provider bill. Read the benchmark's published methodology or open any original batch above. Every retained record is pinned to a source commit and validated before publication.
Three advertised prices, then what left the shelf
An H100 GPU-hour, a four-vCPU VM/VPS hour, and a managed sandbox hour are different products. Their raw dollar prices do not belong on one linear axis, so the next chart rebases each series to 100 at its own first retained observation. H100 uses the first print with at least ten providers; VM/VPS starts when the first complete seven-vendor check exists; sandbox uses the rate in force at the H100 starting print.
H100 and VM/VPS are observed hourly. The sandbox line steps only when a reviewed public rate changes. Select a series to bring its price-dispersion band forward while the other median lines remain visible. This compares direction and dispersion, not absolute cost, traded volume, or executed transactions. Absolute VM/VPS and sandbox prices remain in the first chart above.
Inspect the H100 provider-coverage gate
Current observed rental occupancy
loading hourly market stateAvailable now
direct feeds preferred over matching aggregator rowsRental occupancy needs both a rented count and the matching total. Akash reports active, available, pending, and total GPU units. Clore exposes an on-demand rented flag for each public server. Other feeds show current stock or deployable configurations without the total fleet, so they remain availability observations rather than occupancy percentages. The VM and sandbox sources on this page expose prices and workload timing, but not a comparable public rented-and-total denominator.
DataFusion rebuilds this view from maintained gold tables. The inputs, ten-provider gate, fixed-cohort rule, formulas, source hierarchy, and excluded history are documented in the Compute Bazaar benchmark methodology.
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II The Substrate
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III The Markets
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IV Frictions and Futures
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Etiam id orci a justo varius porta. Integer sed tincidunt sapien, sit amet euismod nibh. Vivamus euismod arcu vitae feugiat sodales. Phasellus rhoncus posuere risus, vitae fermentum velit fermentum vel.
Sed luctus erat aliquet. Aliquam erat volutpat. Donec quis volutpat eros. Cras vitae lacinia metus, in pharetra orci. Nulla facilisi. Quisque blandit, justo nec convallis sodales.