How LLM providers sell reserved capacity

Provisioned deployments are "billed at an hourly rate ($/PTU/hr) based on the number of PTUs deployed, regardless of the number of tokens consumed"; Azure Reservations exchange a 1-month or 1-year commitment for a discounted effective rate, and "Reservations don't guarantee capacity"; the tokens per minute a given PTU count delivers varies by model and each model carries a minimum deployment size; spillover routes overflow requests to a standard deployment for Azure OpenAI models, while "Foundry Models from other providers (Azure DeepSeek, Meta Llama) don't currently support spillover". No $/PTU/hr figure appears on this page.

"You're billed hourly for a Provisioned Throughput that you purchase"; a Model Unit specifies the input tokens it can process and the output tokens it can generate across all requests within one minute; commitment levels are none, 1 month, or 6 months, with no deletion before the term ends and "billing continues until you delete the Provisioned Throughput"; the MU specification and the price per MU are directed to an AWS account manager.

The model list available for Provisioned Throughput purchases, which includes the open-weight Meta Llama 3.1 70B and 8B Instruct and Llama 3.2 1B, 3B, 11B, and 90B Instruct entries, each shown with us-west-2 single-region support.

Provisioned Throughput described as "a fixed-cost, fixed-term subscription available in several term-lengths that reserves throughput for supported generative AI models", bought for deterministic costs "by paying a fixed monthly or weekly price with control of overages".

"A Generative AI Scale Unit (GSU) is a measure of throughput for your prompts and responses"; a burndown rate "converts the input and output units ... to input tokens per second" to produce a standard unit across models; unused throughput does not carry over to the next month; the cache discount is applied as a reduced burndown rate, so 1,000 cached tokens burn down 100 tokens per second on the page's Gemini example.

"Your per-second throughput is defined as your prompt input and generated output across all requests per second"; Gemini 3.8, 3.7, and 3.6 Flash are listed at 675 tokens per second per GSU with an output text token burning 5 tokens; a separate table covers "open models that support Provisioned Throughput" in Preview, including OpenAI gpt-oss 120B at 11,205 tokens per second per GSU, GLM 5, Qwen3-Next-80B, Llama, Kimi K2 Thinking, MiniMax M2, and DeepSeek-V3.2.

"you can't cancel the order in the middle of your term"; monthly subscriptions can renew automatically while "Weekly terms don't support automatic renewal"; "If your throughput exceeds your Provisioned Throughput order amount, overages are processed and billed as standard pay-as-you-go. You can control overages on a per-request basis"; orders are processed against available capacity and "might take from a few minutes to a few weeks".

Published price per GSU for global endpoints: $7.14 per hour on a 1-week commit, $3.698630137 on 1 month, $3.287671233 on 3 months, and $2.739726027 on 1 year, with higher non-global rates; the page's own worked example converts these to $1,200 per GSU per week and $2,700, $2,400, and $2,000 per GSU per month. A 50% monthly billing credit on Provisioned Throughput spending for three Gemini Flash models runs from August 13 to December 31, 2026.

"Scale Tier lets you purchase a set number of API input and output tokens per minute (known as "token units") upfront for access to one specific model snapshot. Each token unit is purchased for a minimum of 30 days."; published per-model prices per unit per day, such as GPT-5.5 at 50,000 TPM for $750.00 and GPT-4.1 at 30,000 input TPM for $110.00 with a 2,500 output TPM bundle at $36.00; combined bundles on GPT-5.4 and GPT-5.5 where "one output token counts as 6"; billing TPM averaged over 15-minute intervals aligned to the top of the hour, with excess "billed at pay-as-you-go (PAYG) rates on Fast mode"; "This offering is available to Enterprise customers." A successor, Reserved Tier, is named for GPT-5.6 and later models.

Confirms the same token-unit definition and 30-day minimum, and adds the purchase path: units are added and removed in the API Platform account after an order form is signed, and "Any units purchased will be active until the start of the next invoice period, and renew daily after that."

"Priority Tier capacity commitments are no longer available for purchase"; a commitment consisted of "A number of input tokens per minute, A number of output tokens per minute, A commitment duration (1, 3, 6, or 12 months), A specific model version"; "Requests beyond your committed capacity automatically fall back to standard tier"; cache reads count as 0.1 tokens per token read.

"Reserve dedicated capacity in throughput units (PTUs). Each PTU represents fixed capacity. The tokens-per-minute it delivers depends on the model and the token type."; the PTU table's columns are Input TPM/PTU, Cached TPM/PTU, Output TPM/PTU, and Price PTU/MIN, but its per-model rows render client-side and did not load in our fetch, so no PTU figure is quoted here. Hardware is priced per GPU per hour: NVIDIA HGX H100 at $5.49 on-demand, HGX B200 at $8.99, and every reserved-hardware cell reading "Contact sales". Read again on 2026-09-29: the $5.49 list rate was unchanged; a dated promotional rate that ended on 09/30/26 is not carried in the article.

On-demand deployments "Pay per GPU second, with no extra charges for start-up times". The hourly table carries two dated columns headed "Price ($) per hour - upto Aug 31" and "Price ($) per hour - from Sep 1", with no year stated; the current column reads H100 80 GB $8.00, H200 141 GB $8.00, B200 180 GB $13.00, B300 288 GB $15.00, and GB300 288 GB $20.00. Region-restricted deployments carry a 1.5x premium. No token-throughput entitlement is published for these deployments.

Dedicated deployments: "Only pay for the compute you use, down to the minute" and "you do not pay for idle time". Per-minute GPU instance rates run from T4 at $0.01052 to H100 80 GiB at $0.10833 and B200 180 GiB at $0.16633, with the entry plan at $0 per month, pay as you go, and volume discounts negotiated on higher plans. "You can deploy open source and custom models on Baseten."

The unit definition (one model's base allocation of aggregate output tokens per second: Kimi K3 40, GLM-5.3 100, DeepSeek V4.1 Flash 300), $1,200 per unit per model per month, the $3,000 three-model bundle, extra capacity above the base that is free while the shared pool has room and is not reserved, auto scaling at "$5 per extra unit, per two-hour period" after authorization and subject to availability, no monthly token cap, and the statement that "The throughput figures do not describe a single request's speed or a monthly token allowance."