Adam Sioud

Exemplars

The Compute Bazaar: Tinkering with Compute Markets

WIP - EARLY AUGUST 2026

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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GPU prices, Updated hourly
Price history Loading observations
H100 observed benchmark pending
Loading price history
Recent observations USD per GPU hour · band shows provider-floor p25-p75
Requestable GPU offers

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.

H100 offer market
pending Prime median / GPU-hour
waiting for market comparison
WAITING waiting for the next public snapshot
Market benchmark pending
Best on Prime pending
Prime middle 50% pending
Near Prime median pending
Visible on Prime pending
Price references through time retained hourly observations
Loading retained market observations
Current offer shelf $0.25 display levels
Loading current offer levels
Current upstream sources
Waiting for the current Prime catalogue
Latest observable change
Waiting for consecutive hourly snapshots
The solid market line is the wider provider-balanced benchmark. The stepped Prime line and band use one lowest eligible base rate per upstream Prime provider. Bars count low-price providers; shelf bars count returned configurations. Neither is physical GPU inventory or traded volume. Required resources can raise the final machine total.

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.

Loading public sandbox observations
Compute market pulse

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.

GPU market H100 observed provider-floor benchmark and Akash capacity
Observed price waiting for gold history
pending
Loading H100 prices
Available GPU share Akash online providers
pending
Loading available GPU capacity
CPU market 4 vCPU / 8 GiB seven public VM offers and Akash CPU capacity
Observed VM median exact-shape public offers
pending
Loading VM prices
Available CPU share Akash online providers
pending
Loading available CPU capacity
Sandbox work StarSling fixed six-service batch · public runs
Median estimated job cost processor and memory only
pending
Loading compatible benchmark runs
Median measured runtime ten timed task phases
pending
Loading measured runtimes
Waiting for the latest retained observations.
CPU CAPACITY PRICES, checking public sources

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.

Underlying VM median pending seven exact public offers
Managed sandbox median pending eight fixed services
Observed rate ratio pending sandbox / VM; not provider margin
Source check pending public APIs checked hourly
Public VM/VPS and managed sandbox prices VM and managed sandbox medians · USD per hour · log scale
Loading price history
The pale VM envelope spans all seven current offers; the darker bands show each cohort's middle 50%. Every complete hourly VM check remains plotted, including unchanged prices. No earlier VM history is inferred. Vertical scale is logarithmic.
Rates behind the sandbox median retained public rate histories · USD per hour · log scale
Loading individual sandbox rates
A dot marks a series start or changed public rate. Unchanged retained observations remain inspectable without adding marks. A step carries the last observed rate forward; it is not an hourly transaction print. The bold median uses the fixed eight services. Beam, Freestyle, and Sailboxes remain visible but do not change that cohort.
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 median

Akash 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 only
What moved the line
effective dates where stated; observed bounds otherwise
Audit 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.


II One software workload

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.

Lowest median estimate pending processor and memory only
Highest median estimate pending same pinned workload
Latest complete jobs pending three source slots incomplete
Retained source history pending seven batches over five days
Estimated cost of the same job complete jobs · median and middle 50%
Loading comparable workload results
Dots are complete job estimates; diamonds are service medians; bars span the middle 50%. Measured time and source rates remain available below each estimate.
Cost ranking
median job estimate · matching public hourly rate
Inspect 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.


III Price and capacity

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.

H100 observed benchmark
pending loading history
Relative advertised-rate movement each series begins at 100 when its retained history starts
Loading relative series
The selected band is cross-sectional price dispersion, not a confidence interval or traded volume. The VM/VPS line starts later because no earlier hourly checks are invented. Loading reproducible build
Inspect the H100 provider-coverage gate
H100 provider coverage retained through time loading retained history
Loading provider coverage
Bars show the maximum contributing provider count seen that day. Provider count is coverage, not volume.
Current observed rental occupancy
loading hourly market state
Observed rental occupancy and capacity rented share above · source-reported capacity below
Akash GPU-unit occupancy
pending loading retained observations
Waiting for hourly rented-and-total observations
Akash counts GPU units; Clore counts public on-demand servers. The lower pane is observed rentable capacity, not traded volume. Commercial rental occupancy, not GPU engine activity.
Available now
direct feeds preferred over matching aggregator rows

Rental 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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