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Model Inference

TPM reservation

A TPM reservation locks dedicated inference capacity for a specified model, ensuring that your services are not affected by public rate limits during peak business hours. This topic describes how to create, integrate, and manage TPM reservations.

Overview

With a TPM (Tokens Per Minute) reservation, you can lock dedicated inference throughput for a specified model. Calls within the reserved capacity are not subject to the rate limits of the public resource pool.
  • Capacity guarantee: The reserved TPM capacity is dedicated to your workload and is not shared with other users.
  • Dedicated model code: After you create a TPM reservation, the system automatically generates a dedicated model code. You must replace the model parameter in your API requests with this code.
  • Overflow strategy: When creating a reservation, you can choose how to handle excess traffic — automatically overflow to pay-as-you-go (default, no service interruption) or use reserved capacity only (excess requests return 429, no additional charges incurred).

Compare and select a plan

Model Studio offers multiple capacity and billing plans for inference calls, including pay-as-you-go, resource plans and savings plans, TPM reservations, and PTU dedicated deployments. Each plan has different characteristics regarding billing unit, capacity guarantee level, overflow handling, and integration changes. This section helps you choose the appropriate plan based on your business needs.

Plan

Billing unit

Capacity guarantee

Use cases

Overflow handling

Code changes

Pay-as-you-go

Per token

None (shared public pool)

Highly variable/short-term traffic

Served automatically, subject to public rate limits

No changes required

Resource plan/Savings plan

Prepaid quota

Committed-use discount (not dedicated capacity)

Cost optimization

Excess traffic switches to pay-as-you-go

No changes required

TPM reservation

Prepaid per kTPM

Dedicated capacity with a firm guarantee

Predictable traffic, no tolerance for rate limiting

Optional: auto-overflow to pay-as-you-go (default) / reserved-capacity-only returns 429

Replace the model parameter

PTU (Model deployment)

Prepaid per kTPM

Dedicated deployment instance

High throughput and high performance

Optional: auto-overflow to pay-as-you-go (default) / PTU-capacity-only returns 429

Replace the model parameter

Supported models

Prices are subject to the console; the tables are for reference only.
  • China (Beijing)
  • Singapore

Model name

Prepaid - daily

Input (per 10,000 TPM)

Output (per 1,000 TPM)

Qwen3.8-Max

$16.63

$4.99

Qwen3.7-Flash-2026-07-15 Contact your account manager to activate

$0.28

$0.11

Qwen3.7-Max-2026-05-20

$16.63

$4.99

Qwen3.7-Plus-2026-05-26

$2.77

$1.11

Qwen3.6-Flash-2026-04-16

$1.66

$1.00

GLM-5.2

$11.09

$3.88

GLM-5.1

$8.32

$3.33

DeepSeek-v4-Pro-0813

$12.82

$3.85

DeepSeek-v4-Flash

$1.39

$0.28

DeepSeek-v4-Pro

$16.63

$3.33

DeepSeek-v4-Flash-0731

$4.27

$1.28

Kimi-K2.6

$9.01

$3.74

Billing and usage notes

  • Billing starts once deployment succeeds. Calls within the reserved capacity incur no additional charges.
  • Prepaid fees are paid in a one-off upfront payment and remain in effect from the moment of purchase. Refer to the Bailian console for the actual charges.
  • The "daily" billing cycle is calculated by natural day: from the moment the instance takes effect until 00:00:00 the next day, rather than a continuous 24 hours from the purchase time. For example, a 1-day reservation purchased at 16:00 expires at 00:00 (effective for about 8 hours). We recommend purchasing at the start of a day, or enabling Auto-renewal on expiry to avoid service interruption.
  • Downgrade and unsubscribe refund: the used portion is settled at a 1.2x coefficient. Formula: Refund = prepaid fee of the reduced portion - (prepaid fee of the reduced portion × used duration / purchased duration × 1.2)
  • When the overflow policy is "Auto overflow": requests exceeding the guaranteed quota automatically degrade to standard pay-as-you-go billing without service interruption. You can view the degradation count on the detail page at Overflow degradation statistics. When set to "Reserved capacity only": requests exceeding the quota return 429 and incur no additional charges.
  • Within 2 hours after the service expires: the instance is still running, can be called, and can be renewed; 2 to 14 hours after expiry: the instance is stopped, cannot be called, but can still be renewed; 14 hours after expiry: the instance is deleted and cannot be recovered.
Some models support long-input tier coefficients and cache discounts. The capacity calculator applies these parameters automatically. Details are as follows:

Model

Max input length

Cache discount

Long-input tier coefficient

Qwen3.8-max

1 Million

0.125

No tiers (1.0)

Qwen3.6-flash-2026-04-16

256K

Cache not supported

No tiers (1.0)

Other Qwen series

256K

0.2 (cache hits consume capacity at 20% of the normal rate)

No tiers (1.0)

glm-5.2

1 Million

0.25 (cache hits consume capacity at 25% of the normal rate)

No tiers (1.0)

glm-5.1

200K

0.2 (cache hits consume capacity at 20% of the normal rate)

[0, 32K): input 1.0 / output 1.0
[32K, 200K]: input 1.33 / output 1.17

DeepSeek-v4-Pro-0813

1 Million

0.1 (cache hits consume capacity at 10% of the normal rate)

No tiers (1.0)

DeepSeek-v4-Pro

256K

0.08 (cache hits consume capacity at 8% of the normal rate)

No tiers (1.0)

DeepSeek-v4-Flash-0731

1 Million

0.1 (cache hits consume capacity at 10% of the normal rate)

No tiers (1.0)

DeepSeek-v4-Flash

256K

0.2 (cache hits consume capacity at 20% of the normal rate)

No tiers (1.0)

Kimi-K2.6

256K

0.2 (cache hits consume capacity at 20% of the normal rate)

No tiers (1.0)

Create a TPM reservation

Prerequisites: Bailian model service is activated and a workspace has been created. Sign in to the Bailian console and click Create TPM reservation.
image
Creating a TPM reservation requires a one-off upfront payment. We recommend using the TPM capacity calculator to estimate the required TPM and confirm the cost before submitting.
  1. Fill in the following parameters:

    Parameter

    Description

    Required

    Value description

    Reservation name

    Custom name for identification.

    Yes

    ≤ 50 characters

    Select model

    Select the model for which to reserve capacity. A dedicated model code is generated automatically upon submission.

    Yes

    Only models that support TPM reservation are available; refer to the console display.

    Billing cycle

    Billing cycle.

    Yes

    Daily

    Input TPM

    Reserved input throughput, in kTPM (1 kTPM = 1,000 tokens/minute).

    Yes

    The starting value and step vary by model; refer to the console display.

    Output TPM

    Reserved output throughput, in kTPM.

    Yes

    The starting value and step vary by model; refer to the console display.

    Purchase duration

    Valid duration of the reservation.

    Yes

    Enter the number of days in the input box. Supported values: 1-30, 60, 90, 120, 365 days.

    Auto-renewal on expiry

    Automatically deducts payment and renews at 08:00 one day before expiry. Enabled by default.

    No

    On / Off

    Single renewal duration

    Duration of each automatic renewal.

    No

    Enter the number of days in the input box. The value range is the same as the purchase duration.

    Overflow policy

    How requests exceeding the reserved capacity are handled when it is exhausted.

    Yes

    Auto overflow to per-token pay-as-you-go (default; overflow switches to pay-as-you-go, no service interruption) / Reserved capacity only (overflow returns 429, no additional charges)

  2. After confirming the parameters, click Buy now. In the fee confirmation dialog, verify the charges and click Confirm payment.
  3. On the Overview tab of the TPM reservation detail page, find the Dedicated model code and click copy.
  4. Replace the model parameter in your API request with the copied dedicated model code:
    Prerequisite: a TPM reservation instance has been created and its status is Running.
    The thinking_budget parameter of GLM-5.2 (which limits thinking length) does not take effect when called.
# When the request volume surges within a short period, the system needs a brief warm-up to match the required compute.
# During warm-up, some requests may experience latency fluctuations. Stability recovers after warm-up completes.
# Ensure you have request queuing or retry mechanisms in place.

import dashscope

response = dashscope.Generation.call(
    api_key="your-api-key",
    model="your-dedicated-model-code",   # Replace with your dedicated model code
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.output.text)
# When the request volume surges within a short period, the system needs a brief warm-up to match the required compute.
# During warm-up, some requests may experience latency fluctuations. Stability recovers after warm-up completes.
# Ensure you have request queuing or retry mechanisms in place.
curl -X POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
  -H "Authorization: Bearer $DASHSCOPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"your-dedicated-model-code","messages":[{"role":"user","content":"Hello"}]}'

TPM capacity calculator

The TPM capacity calculator on the right side of the creation page helps you estimate the TPM quota to purchase based on your business load. After you fill in the following parameters, the calculator automatically outputs the recommended input TPM and output TPM.

Parameter

Description

Impact on result

Requests per minute (RPM)

Number of requests sent per minute during peak business hours.

The larger the RPM, the larger the recommended input and output TPM in proportion.

Average input length (tokens)

Average number of input tokens per request.

The longer the input, the higher the tier and the larger the coefficient, so the higher the recommended input TPM. Tier boundaries differ by model; refer to the actual console display.

Average output length (tokens)

Average number of output tokens per request.

The longer the output, the larger the coefficient may be, so the higher the recommended output TPM.

Cache hit rate

The proportion of requests whose repeated prefixes are cache hits. The actual hit rate depends on the repetition of request content; refer to the runtime result.

The higher the hit rate, the slower the input capacity is consumed, so the lower the recommended input TPM. Affects only input TPM, not output TPM.

image

View and manage

Go to the Bailian console and open the reservation list page. The list displays all reservation instances as model cards and supports filtering by model, time, and status.
image

Reservation details

Click a target model card to open the detail page, which contains the following 3 tabs:
  • Overview
  • Monitoring
  • API access
image
  • Basic information: reservation name, dedicated model code (copyable), base model, input/output capacity.
  • Statistics cards (last 7 days): active reservation count, total and peak TPM usage, average utilization.
  • Utilization trend: switch between input/output directions; shows the reserved capacity line and actual usage.
  • Overflow degradation statistics: shows the number of requests degraded after exceeding the reserved capacity (degradation occurs only under the "Auto overflow" policy).

Management operations

In the reservation list on the Overview tab of the detail page, find the target instance and use the Operation column to perform the following:
  • Scaling
  • Renewal
  • Unsubscribe
image
Click Scaling and adjust the input TPM and output TPM in the dialog.
Input TPM and output TPM can be set to 0: after zeroing, no capacity charges accrue and the dedicated model code is retained, avoiding code invalidation caused by expiry or unsubscription. However, zeroing is a downgrade, and the used portion is settled at a 1.5x penalty coefficient (see Billing and usage notes above).
Within 2 hours after the service expires, the status is Running; from 2 to 14 hours after expiry, it becomes Stopped; after 14 hours, it becomes Expired and is eventually deleted.

Status

Description

Running

Running normally; can be called using the dedicated model code.

Pending

Created; waiting to take effect.

Modifying

Scaling in progress; service is not interrupted during this period.

Stopped

Stopped due to reasons such as overdue payment; can be restored after renewal.

Expired

Expired without renewal; resources have been released.

Canceled

Unsubscription completed; irreversible.

FAQ

It depends on the overflow policy selected at creation: under "Auto overflow", requests exceeding the reserved capacity automatically degrade to pay-as-you-go billing without service interruption. You can view the degradation count and time on the Overview tab of the detail page at Overflow degradation statistics; if degradations occur frequently, we recommend scaling up. Under "Reserved capacity only", requests exceeding the quota return a 429 error and incur no additional charges; if 429s occur frequently, we recommend scaling up.
After a TPM reservation is created, the system automatically generates a dedicated model code. You can copy the code on the Overview tab of the TPM reservation detail page. You must replace the model parameter in your API request with this code to use the reserved capacity.
After a reservation expires, the dedicated model code becomes invalid, and subsequent requests automatically fall back to public resource processing (pay-as-you-go). We recommend enabling Auto-renewal on expiry in advance to avoid service impact.
On the Overview tab of the detail page, view the TPM usage trend chart and overflow degradation statistics. If utilization stays close to 100% or degradations occur frequently, we recommend scaling up the input/output TPM.
"Daily" is calculated by natural day: the validity period runs from the moment the instance takes effect until 00:00:00 the next day, rather than a continuous 24 hours from the purchase time. For example, a reservation purchased at 16:00 expires at 00:00, with an effective duration of about 8 hours. To obtain a full day of capacity, we recommend purchasing at the start of a day, or enabling Auto-renewal on expiry to ensure continuous service.
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