Create deployment - Alibaba Cloud Model Studio

Prerequisites

Read Introduction to model deployment and Deploy a model by using the API to understand how model deployment works and the basic workflow on Alibaba Cloud Model Studio.
Configure your API key for Model Studio. For details, see Get an API key.

Model deployment

Endpoint

POST https://dashscope-intl.aliyuncs.com/api/v1/deployments

Request examples

Billing by provisioned throughput units (PTU)
Billing by model unit usage duration
Billing by token usage

After running the deployment command below, billing starts immediately upon successful deployment—even if you have not yet called the model. Confirm the billing rules before deploying.

The PTU billing mode charges based on the duration of provisioned throughput usage. It suits scenarios requiring stable throughput guarantees, high concurrency, low latency, and predictable traffic. In this mode, throughput/concurrency and generation speed are preset by the platform and cannot be adjusted.

curl "https://dashscope-intl.aliyuncs.com/api/v1/deployments" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "name": "my_qwen_flash",
    "model_name": "qwen-flash-2025-07-28",
    "plan": "ptu",
    "ptu_capacity": {
        "input_tpm": 10000,
	"output_tpm": 1000
    }
}'

After running the deployment command below, billing starts immediately upon successful deployment—even if you have not yet called the model. Confirm the billing rules before deploying.
Model unit pay-as-you-go computing resources are allocated on a first-come, first-served basis. If purchase fails, you receive a full refund.

Select the model unit billing method. This mode charges based on model unit usage duration and suits large-scale inference workloads after model fine-tuning. Resources are dedicated, and performance and cost are flexible. Throughput/concurrency and generation speed are customizable.

curl "https://dashscope-intl.aliyuncs.com/api/v1/deployments" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "name": "my_qwen_plus",
    "model_name": "qwen-plus-2025-12-01",
    "plan": "mu",
    "deploy_spec": "MU1",
    "enable_thinking": true,
    "capacity": 4,
    "max_context_length": 10000,
    "rpm_limit": 500,
    "tpm_limit": 1000
}'

The model unit deployment mode supports additional settings:

Configuration item	Configuration details
Service name	Custom name for the deployment service.
Select model	Select the model to deploy, including platform built-in models and fine-tuned models.
Model unit type	Select the deployment specification. Different specifications correspond to different compute power and performance.
Deployment replica count	Set the initial number of deployment replicas, which affects the concurrency capacity of the service.
Deployment template	Select a deployment template (such as "single-node deployment"). Different templates correspond to different resource configuration schemes. Available only under the model unit billing mode.
Configure model inference mode	For some models deployed in Model Unit mode, you can configure the inference mode, maximum context length, and more. Instruct - After deployment, the model performs inference in non-thinking mode. Thinking - After deployment, the model performs inference in thinking mode.
Maximum context length	The Model Unit deployment mode of some models supports this setting. The maximum context length depends on the model type.
Service rate limiting	The Model Unit deployment mode of some models supports this setting. You can limit the RPM and TPM of model invocations.

For details on setting these options via API, see Create a model deployment task using the API.

Select the token-based billing method. This mode charges based on token usage and suits cost-sensitive scenarios with low requirements for concurrency and latency. It offers the highest price advantage. Throughput/concurrency and generation speed are preset by the platform and cannot be adjusted.

curl "https://dashscope-intl.aliyuncs.com/api/v1/deployments" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model_name": "qwen3-8b-ft-202511132025-0260",
    "plan": "lora",
    "capacity": 1,
    "name": "qwen3-8b-ft"
}'

The capacity parameter has no effect but must be included. To scale up or down, go to the Model Studio model deployment console and submit a form request.

Request parameters

Parameter

Type

Location

Required

Description

model_name

String

body

Yes

The name of the model to deploy. This corresponds to the model ID in My Models. You can also get this ID from the output of the Create Training Job or Create Import Job operations.

plan

String

body

Yes

The deployment plan. The following billing methods are supported:

Billing method	Plan setting
Billing by model unit	`"plan": "mu"`
Billing by compute unit	`"plan": "cu"`
Provisioned throughput	`"plan": "ptu"`
LoRA shared deployment (billed by token usage)	`"plan": "lora"`

You can quickly find the supported deployment plans for a fine-tuned model in My Models.

Fine-tuned CosyVoice models currently only support "plan": "mu".

name

String

body

Yes

The display name of the model in the console.

capacity

Integer

body

Required only when "plan": "mu" is specified. Specifies the number of resource units for the deployment. The value must be an integer multiple of base_capacity. The constraints vary based on the deploy_spec value. For example, for MU2, the value must be a multiple of 8, while for MU5, it can be 1. Example: "capacity": 1.

CosyVoice models currently provide the following two deployment templates with corresponding capacity constraints:

single-node deployment: capacity must be an integer multiple of 1, such as 1, 2, 3, 4, or 5.
single-node deployment - flagship complex inference edition: capacity must be an integer multiple of 8, such as 8, 16, 24, or 32.

billing_method

String

body

Required only when "plan": "mu" is specified. Currently, only "POST_PAY" (Post-paid) is supported. Example: "billing_method": "POST_PAY".

deploy_spec

String

body

This setting is applicable only when "plan": "mu" is specified.

For details about feature support, see Feature support for model unit deployment.

This parameter is required when "plan": "mu" is specified. Example: "deploy_spec": "MU1".

You can get this value from the template_id field returned by the Get Deployable Model List operation.

enable_thinking

Boolean

body

Supported by some models. You can set this to true or false.

max_context_length

Number

body

Supported by some models. Example: "max_context_length": 131072.

rpm_limit

Number

body

Supported by some models. Specifies the maximum number of requests per minute (RPM).

tpm_limit

Number

body

Supported by some models. Specifies the maximum number of tokens per minute (TPM).

ptu_capacity

Object

body

This setting is applicable only when "plan": "ptu" is specified.

For details about feature support, see Feature Support for PTU Deployment.

If you do not specify this parameter, the system defaults to 10,000 input_tpm and 1,000 output_tpm.

Example: "ptu_capacity": { "input_tpm": 10000, "output_tpm": 1000 }.

ptu_capacity.input_tpm

Number

body

Supported by all models. Specifies the maximum number of input tokens per minute (TPM).

ptu_capacity.output_tpm

Number

body

Supported by all models. Specifies the maximum number of output tokens per minute (TPM).

ptu_capacity.thinking_output_tpm

Number

body

Supported by some models. Specifies the maximum number of provisioned thinking output tokens per minute (TPM).

suffix

String

body

After a model is deployed, a new model name is generated. The suffix parameter specifies the suffix for this new name. It must be globally unique and have a maximum length of 8 characters. You can omit the suffix for the first deployment of a model. If you deploy the same model multiple times, you must specify a unique suffix for each deployment.

See the deployed_model output parameter for more information.

Supported models

View supported features and billing.

Usage duration billing (Provisioned Throughput)
Billing by usage duration (model unit)
By model Token usage

Cost = Usage duration × (Input TPM unit price × Input TPM + Output TPM unit price × Output TPM)Postpaid is calculated by hour: the usage duration unit is hours, and the unit price takes the "1 hour continuous" column in the table below; prepaid is calculated by day: the usage duration unit is days, and the unit price takes the "1 day continuous" column in the table below.

Prepaid orders take effect immediately after payment, valid for N days until 23:59 on day N. If ordered after 22:00, the expiration date is automatically extended by 1 day.
After a prepaid order expires, the service will be stopped with a 2-hour delay, and resources will be retained for 14 hours after stopping before being released.
Prepaid orders cannot be terminated early.
For post-paid billing, if your account is in arrears, the deployed resources will be retained and billed for 24 hours, during which the service can still be used normally. After 24 hours, the system stops billing, the model deployment enters an arrears state, and the underlying resources will be deleted, but the model deployment task will be retained. After you pay off the arrears, the system will reallocate resources and resume usage (fees will continue to accrue after resumption). If you do not want to continue incurring charges, you can delete the model deployment task; once deleted successfully, billing will stop.

When the model input exceeds the maximum input Token, the relevant call will automatically switch to the pay-as-you-go mode of the current model; when the purchased TPM is exceeded, it is handled according to the overflow policy selected at creation ("Auto-overflow" switches to pay-as-you-go, "PTU capacity only" returns 429). At this time, inference performance may degrade and will be governed by the public traffic of the current snapshot model in the workspace, and the fee is charged according to the model invocation (pay-as-you-go) standard.

At this time (only under the "Auto-overflow" policy), the call API response Header will include: x-dashscope-ptu-overflow:true.
For TPM statistics, go to: Model Monitoring.

For specific fee-reduction and refund rules for scale-in (downgrade) scenarios, please refer to: Refund rules for configuration downgrades.

PTU deployment supports stepped capacity coefficients and cache discounts for long inputs. For details, see Provisioned Throughput long input and cache.

Singapore
North China 2 (Beijing)

Qwen
DeepSeek
GLM
Qwen-VL

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Prepaid input Per 10K TPM/day	Prepaid output Per 1K TPM/day
Qwen3.8-Max	qwen3.8-max	1M	$4.8	$1.44	$57.6	$17.28

Qwen3.7-Max-2026-05-20	qwen3.7-max-2026-05-20	256K	$1.92	$1.8	$72	$21.6
Qwen3.7-Plus-2026-05-26	qwen3.7-plus-2026-05-26	256K	$0.96	$0.384	$11.52	$4.608

Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	128K	$1.2	$0.72	$14.4	$8.64

Qwen3.5-Plus-2026-04-20	qwen3.5-plus-2026-04-20	128K	$0.96	$0.576	$11.52	$6.912

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Prepaid input Per 10K TPM/day	Prepaid output Per 1K TPM/day
DeepSeek-v4-Flash	deepseek-v4-flash	256K	$0.72	$0.144	$8.64	$1.728
DeepSeek-v4-Pro	deepseek-v4-pro	256K	$0.96	$1.728	$103.68	$20.736
DeepSeek-v3.2	deepseek-v3.2	64K	$2.05	$0.616	$24.62	$7.387

Model name

Model code

Max input tokens

Postpaid input

Per 10K TPM/hour

Postpaid output

Per 1K TPM/hour

Prepaid input

Per 10K TPM/day

Prepaid output

Per 1K TPM/day

DeepSeek-v4-Flash

deepseek-v4-flash

256K

$0.72

$0.144

$8.64

$1.728

DeepSeek-v4-Pro

deepseek-v4-pro

256K

$0.96

$1.728

$103.68

$20.736

DeepSeek-v3.2

deepseek-v3.2

64K

$2.05

$0.616

$24.62

$7.387

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Prepaid input Per 10K TPM/day	Prepaid output Per 1K TPM/day
GLM-5.2	glm-5.2	1M	$5.04	$1.584	$60.48	$19.008
GLM-5.1	glm-5.1	64K	$5.04	$1.584	$64.8	$19.008

Model name

Model code

Max input tokens

Postpaid input

Per 10K TPM/hour

Postpaid output

Per 1K TPM/hour

Prepaid input

Per 10K TPM/day

Prepaid output

Per 1K TPM/day

GLM-5.2

glm-5.2

$5.04

$1.584

$60.48

$19.008

GLM-5.1

glm-5.1

64K

$5.04

$1.584

$64.8

$19.008

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Prepaid input Per 10K TPM/day	Prepaid output Per 1K TPM/day
Qwen3-VL-Plus-2025-09-23	qwen3-vl-plus-2025-09-23	128K	$0.48	$0.384	$5.76	$4.608

Model name

Model code

Max input tokens

Postpaid input

Per 10K TPM/hour

Postpaid output

Per 1K TPM/hour

Prepaid input

Per 10K TPM/day

Prepaid output

Per 1K TPM/day

Qwen3-VL-Plus-2025-09-23

qwen3-vl-plus-2025-09-23

128K

$0.48

$0.384

$5.76

$4.608

Qwen
DeepSeek
GLM
Qwen-VL

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Subscription input Per 10K TPM/day	Subscription output Per 1K TPM/day
Qwen3.8-Max	qwen3.8-max	1M	$3.96	$1.188	$47.53	$14.258

Qwen3.7-Max-2026-05-20	qwen3.7-max-2026-05-20	256K	$3.96	$1.188	$47.53	$14.258
Qwen3.7-Plus-2026-05-26	qwen3.7-plus-2026-05-26	256K	$0.66	$0.264	$7.92	$3.168

Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	128K	$0.67	$0.066	$7.93	$4.753

Qwen3.5-Plus-2026-04-20	qwen3.5-plus-2026-04-20	128K	$0.26	$0.16	$3.17	$1.9

Qwen3-Max-2025-09-23	qwen3-max-2025-09-23	128K	$1.11	$0.45	$13.32	$5.4

Qwen-Flash-2025-07-28	qwen-flash-2025-07-28	128K	$0.06	$0.06	$0.72	$0.72
Qwen-Plus-2025-12-01	qwen-plus-2025-12-01	128K	$0.28	Non-thinking: $0.07 Thinking: $0.28	$3.36	Non-thinking: $0.84 Thinking: $3.36

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Subscription input Per 10K TPM/day	Subscription output Per 1K TPM/day
DeepSeek-v4-Flash	deepseek-v4-flash	256K	$0.5	$0.099	$5.94	$1.188
DeepSeek-v4-Pro	deepseek-v4-pro	256K	$5.94	$1.188	$71.3	$14.26
DeepSeek-v3.2	deepseek-v3.2	64K	$1.04	$0.16	$12.48	$1.92
DeepSeek-v3	deepseek-v3	64K	$0.99	$0.396	$11.9	$4.75

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Subscription input Per 10K TPM/day	Subscription output Per 1K TPM/day
GLM-5.2	glm-5.2	1M	$3.96	$1.386	$47.53	$16.635
GLM-5.1	glm-5.1	64K	$2.97	$1.19	$35.65	$14.26

Model name

Model code

Max input tokens

Postpaid input

Per 10K TPM/hour

Postpaid output

Per 1K TPM/hour

Subscription input

Per 10K TPM/day

Subscription output

Per 1K TPM/day

GLM-5.2

glm-5.2

$3.96

$1.386

$47.53

$16.635

GLM-5.1

glm-5.1

64K

$2.97

$1.19

$35.65

$14.26

Model name	Model code	Max input tokens	Postpaid input Per 10K TPM/hour	Postpaid output Per 1K TPM/hour	Subscription input Per 10K TPM/day	Subscription output Per 1K TPM/day
Qwen3-VL-Plus-2025-09-23	qwen3-vl-plus-2025-09-23	128K	$0.35	$0.35	$4.2	$4.2

Model name

Model code

Max input tokens

Postpaid input

Per 10K TPM/hour

Postpaid output

Per 1K TPM/hour

Subscription input

Per 10K TPM/day

Subscription output

Per 1K TPM/day

Qwen3-VL-Plus-2025-09-23

qwen3-vl-plus-2025-09-23

128K

$0.35

$4.2

Cost = Usage duration (hours) × Number of model units × Model unit price"Model unit price" takes the "Hourly unit price" column in the table below for pay-as-you-go scenarios; for monthly prepaid billing, the formula becomes Number of months × Number of model units × Monthly unit price.

For the first month of a prepaid purchase, if you cancel early within the first month, the daily unit price (≈ Monthly unit price / 30) is billed at 1.2× (less than one day is billed as one day)

Compute resources under the model unit pay-as-you-go method are first-come, first-served. If the purchase fails, a full refund is issued.

Singapore
North China 2 (Beijing)

Text generation
Multimodal

Model name	Model code	Model unit specification	Hourly unit price (USD) Minimum billing: minute	Monthly unit price (USD) Minimum billing: day
Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	MU1 x 8	$88	$41,832

Qwen3.5-397B-A17B	qwen3.5-397b-a17b	MU2 x 8	$112	$52,392
Qwen3.5-122B-A10B	qwen3.5-122b-a10b	MU2 x 8	$112	$52,392
Qwen3.5-27B	qwen3.5-27b	MU1 x 2	$22	$10,458
Qwen3.5-9B	qwen3.5-9b	MU1 x 2	$22	$10,458

GLM-5.1	glm-5.1	MU2 x 8	$112	$52,392
GLM-5.1	glm-5.1	MU3 x 8	$216	$102,696

DeepSeek-v4-Flash	deepseek-v4-flash	MU2 x 8	$112	$52,392

Qwen-Plus-Character-2025-11-06	qwen-plus-character-2025-11-06	MU1 x 4	$44	$20,916

Model name	Model code	Model unit specification	Hourly unit price (USD) Minimum billing: minute	Monthly unit price (USD) Minimum billing: day
Qwen3-VL-32B-Instruct	qwen3-vl-32b-instruct	MU2 x 8	$112	$52,392

Model type:

Instruct - After model deployment, inference is performed in non-thinking mode.

Text generation
Multimodal

Qwen

Model name	Model code	Model unit specification	Hourly unit price (USD) Minimum billing: minute	Monthly unit price (USD) Minimum billing: day
Qwen3.6-35B-A3B	qwen3.6-35b-a3b	MU1 x 8	$59.408	$28,734.256
		MU2 x 8	$69.312	$33,044.72
		MU3 x 8	$150.72	$72,577.152
		MU9 x 1	$7.014	$3,383.024
Qwen3.6-27B	qwen3.6-27b	MU9 x 1	$7.014	$3,383.024
Qwen3.6-Flash-2026-04-16	qwen3.6-flash-2026-04-16	MU1 x 2	$14.852	$7,183.564
Qwen3.6-Flash-2026-04-16	qwen3.6-flash-2026-04-16	MU3 x 8	$150.72	$72,577.152
Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	MU1 x 8 MU1 x 16(PD separation mode)	$59.408 PD separation mode:$118.816	$28,734.256 PD separation mode:$57,468.512

Qwen3.5-397B-A17B	qwen3.5-397b-a17b	MU3 x 8 MU3 x 16(PD separation mode)	$150.72 PD separation mode:$301.44	$72,577.152 PD separation mode:$145,154.304
Qwen3.5-397B-A17B	qwen3.5-397b-a17b	MU6 x 16	$55.008	$26,599.92
Qwen3.5-122B-A10B	qwen3.5-122b-a10b	MU1 x 4	$29.704	$14,367.128
Qwen3.5-122B-A10B	qwen3.5-122b-a10b	MU6 x 16	$55.008	$26,599.92
Qwen3.5-35B-A3B	qwen3.5-35b-a3b	MU1 x 2	$14.852	$7,183.564
		MU2 x 8	$69.312	$33,044.72
		MU3 x 8	$150.72	$72,577.152
		MU9 x 1	$7.014	$3,383.024
Qwen3.5-27B	qwen3.5-27b	MU2 x 8	$69.312	$33,044.72
		MU3 x 8	$150.72	$72,577.152
		MU8 x 1	$6.464	$3,080.477
		MU9 x 1	$7.014	$3,383.024
Qwen3.5-9B	qwen3.5-9b	MU2 x 2	$17.328	$8,261.18
Qwen3.5-Flash-2026-02-23	qwen3.5-flash-2026-02-23	MU1 x 2	$14.852	$7,183.564
Qwen3.5-Plus-2026-02-15	qwen3.5-plus-2026-02-15	MU1 x 8 MU1 x 16(PD separation mode)	$59.408 PD separation mode:$118.816	$28,734.256 PD separation mode:$57,468.512
		MU2 x 8	$69.312	$33,044.72
		MU3 x 8 MU3 x 16(PD separation mode)	$150.72 PD separation mode:$301.44	$72,577.152 PD separation mode:$145,154.304

Qwen3-235B-A22B-Instruct-2507	qwen3-235b-a22b-instruct-2507	MU1 x 4	$29.704	$14,367.128
		MU2 x 8	$69.312	$33,044.72
		MU3 x 8	$150.72	$72,577.152
Qwen3-32B	qwen3-32b	MU6 x 16	$55.008	$26,599.92
Qwen3-30B-A3B-Thinking-2507	qwen3-30b-a3b-thinking-2507	MU1 x 2	$14.852	$7,183.564
Qwen3-8B	qwen3-8b	MU1 x 2	$14.852	$7,183.564
Qwen3-8B	qwen3-8b	MU2 x 2	$17.328	$8,261.18
Qwen3-4B	qwen3-4b	MU1 x 2	$14.852	$7,183.564
Qwen3-4B	qwen3-4b	MU5 x 1	$2.888	$1,394.329
Qwen3-Embedding-0.6B	qwen3-embedding-0.6b	MU5 x 1	$2.888	$1,394.329
Qwen3-Embedding-0.6B	qwen3-embedding-0.6b	MU6 x 1	$3.438	$1,662.495
Qwen3-MoE-Rerank-0.6B	qwen3-moe-rerank-0.6b	MU5 x 1	$2.888	$1,394.329
Qwen3-Rerank-0.6B	qwen3-rerank-0.6b	MU5 x 1	$2.888	$1,394.329
Qwen3-Rerank-0.6B	qwen3-rerank-0.6b	MU6 x 1	$3.438	$1,662.495
Qwen3-Max-2025-09-23	qwen3-max-2025-09-23	MU2 x 8	$69.312	$33,044.72
Qwen3-Max-2025-09-23	qwen3-max-2025-09-23	MU3 x 8	$150.72	$72,577.152
Qwen3-Rerank	qwen3-rerank	MU5 x 1	$2.888	$1,394.329

Qwen2.5-Open-Source-72B	qwen2.5-72b-instruct	MU1 x 8	$59.408	$28,734.256
Qwen2.5-Open-Source-14B	qwen2.5-14b-instruct	MU1 x 2	$14.852	$7,183.564
Qwen2.5-Open-Source-7B	qwen2.5-7b-instruct	MU1 x 2	$14.852	$7,183.564
Qwen2.5-Open-Source-7B	qwen2.5-7b-instruct	MU5 x 1	$2.888	$1,394.329

Qwen-Plus-2025-07-28	qwen-plus-2025-07-28	MU1 x 4 MU1 x 16(PD separation mode)	$29.704 PD separation mode:$118.816	$14,367.128 PD separation mode:$57,468.512
Qwen-Plus-2025-12-01	qwen-plus-2025-12-01	MU1 x 4	$29.704	$14,367.128
Qwen-Plus-Character-2025-11-06	qwen-plus-character-2025-11-06	MU1 x 4	$29.704	$14,367.128

GLM

Model name	Model code	Model unit specification	Hourly unit price (USD) Minimum billing: minute	Monthly unit price (USD) Minimum billing: day
GLM-5.1	glm-5.1	MU2 x 8	$69.312	$33,044.72
		MU3 x 16(PD separation mode)	PD separation mode:$301.44	PD separation mode:$145,154.304
		MU6 x 16	$55.008	$26,599.92
GLM-5	glm-5	MU3 x 16(PD separation mode)	PD separation mode:$301.44	PD separation mode:$145,154.304
GLM-4.7	glm-4.7	MU6 x 32(PD separation mode)	PD separation mode:$110.016	PD separation mode:$53,199.84

DeepSeek

Model name	Model code	Model unit specification	Hourly unit price (USD) Minimum billing: minute	Monthly unit price (USD) Minimum billing: day
DeepSeek-v4-Flash	deepseek-v4-flash	MU1 x 8	$59.408	$28,734.256
MU3 x 8	$150.72	$72,577.152
DeepSeek-v3.2	deepseek-v3.2	MU2 x 16 (PD separation mode)	PD separation mode: $138.624	PD separation mode: $66,089.44

Model name

Model code

Model unit specification

Hourly unit price (USD)

Minimum billing: minute

Monthly unit price (USD)

Minimum billing: day

DeepSeek-v4-Flash

deepseek-v4-flash

MU1 x 8

$59.408

$28,734.256

MU3 x 8

$150.72

$72,577.152

DeepSeek-v3.2

deepseek-v3.2

MU2 x 16 (PD separation mode)

PD separation mode: $138.624

PD separation mode: $66,089.44

Model name	Model code	Model unit specification	Hourly unit price ($) Minimum billing: minute	Monthly unit price ($) Minimum billing: day
Kimi-K2.5	kimi-k2.5	MU2 x 8	$69.312	$33,044.72

Qwen-VL

Model name	Model code	Model unit specification	Hourly unit price ($) Minimum billing: minute	Monthly unit price ($) Minimum billing: day
Qwen3-VL-235B-A22B-Thinking	qwen3-vl-235b-a22b-thinking	MU1 x 8	$59.408	$28,734.256
		MU2 x 8	$69.312	$33,044.72
		MU3 x 8	$150.72	$72,577.152
Qwen3-VL-32B-Instruct	qwen3-vl-32b-instruct	MU2 x 8	$69.312	$33,044.72
Qwen3-VL-32B-Instruct	qwen3-vl-32b-instruct	MU3 x 8	$150.72	$72,577.152
Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	MU1 x 2	$14.852	$7,183.564
Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	MU5 x 1	$2.888	$1,394.329
Qwen3-VL-4B-Instruct	qwen3-vl-4b-instruct	MU1 x 2	$14.852	$7,183.564
Qwen3-VL-2B-Instruct	qwen3-vl-2b-instruct	MU5 x 1	$2.888	$1,394.329
Qwen3-VL-Embedding-2B	qwen3-vl-embedding-2b	MU5 x 1	$2.888	$1,394.329
Qwen3-VL-Flash-2025-10-15	qwen3-vl-flash-2025-10-15	MU1 x 4	$29.704	$14,367.128
Qwen3-VL-Plus-2025-09-23	qwen3-vl-plus-2025-09-23	MU1 x 4	$29.704	$14,367.128

Qwen-VL-Max-2025-08-13	qwen-vl-max-2025-08-13	MU6 x 4	$13.752	$6,649.98

Qwen-Omni

Model name	Model code	Model unit specification	Hourly unit price ($) Minimum billing: minute	Monthly unit price ($) Minimum billing: day
Qwen3.5-Omni-Flash	qwen3.5-omni-flash	MU9 x 1	$7.014	$3,383.024

Model name

Model code

Model unit specification

Hourly unit price ($)

Minimum billing: minute

Monthly unit price ($)

Minimum billing: day

Qwen3.5-Omni-Flash

qwen3.5-omni-flash

MU9 x 1

$7.014

$3,383.024

Model types:

Instruct - The model performs inference in non-thinking mode after deployment.
Thinking - The model performs inference in thinking mode after deployment.

Fee = Model input token count × Model input unit price + Model output token count × Model output unit price (minimum billing unit: 1 token)

Billing by model Token usage is supported only after you complete SFT efficient training on the following base models and obtain a custom model.

Singapore
Beijing

Base model	Model code	Input $/million tokens	Output $/million tokens
Qwen3-14B	qwen3-14b	Non-thinking mode:$0.35 Thinking mode:$0.35	Non-thinking mode:$1.4 Thinking mode:$4.2

Base model

Model code

Input

$/million tokens

Output

$/million tokens

Qwen3-14B

qwen3-14b

Non-thinking mode:$0.35

Thinking mode:$0.35

Non-thinking mode:$1.4

Thinking mode:$4.2

Base model	Model code	Input $/million tokens	Output $/million tokens
Qwen3.5-27B	qwen3.5-27b	<128K $0.086 128K-256K $0.258	<128K $0.688 128K-256K $2.064

Qwen3-32B	qwen3-32b	Non-thinking mode:$0.287 Thinking mode:$0.287	Non-thinking mode:$1.147 Thinking mode:$2.868
Qwen3-14B	qwen3-14b	Non-thinking mode:$0.144 Thinking mode:$0.144	Non-thinking mode:$0.574 Thinking mode:$1.434
Qwen3-8B	qwen3-8b	Non-thinking mode:$0.072 Thinking mode:$0.072	Non-thinking mode:$0.287 Thinking mode:$0.717

Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	$0.072	$0.287

Response example

The command returns the following:

{
  "request_id": "f2ae64f7-83cc-410c-bc0b-840443f7eb86",
  "output": {
    "deployed_model": "emo-35b3f106-sample01",
    "gmt_create": "2025-06-17T11:00:38.68",
    "gmt_modified": "2025-06-17T11:00:38.68",
    "status": "PENDING",
    "model_name": "emo",
    "base_model": "emo",
    "base_capacity": 1,
    "capacity": 1,
    "ready_capacity": 0,
    "workspace_id": "llm-v71tlv3d***",
    "charge_type": "post_paid",
    "creator": "175805416***",
    "modifier": "175805416***"
  }
}

Response parameters

Parameter	Type	Description
request_id	String	The ID of the request.
output	Object	Details of the deployment task.
deployed_model	String	A unique identifier for the deployed model. This ID is used for API operations, such as querying deployment details, modifying deployment rate limiting, deployment scaling, and deleting deployments, and is also passed as an SDK parameter when you invoke the model.
gmt_create	String	The creation time of the deployment task.
gmt_modified	String	The last modification time of the deployment task.
status	String	The status of the deployment task. PENDING: The task is being created. UPDATING: The task is being updated. RUNNING: The deployment task is running, and the deployed model can process requests. STOPPED: The deployment task is stopped and is not billed. DELETING: The task is being deleted. FAILED: The creation or update of the task failed.
model_name	String	The name of the model used in the deployment task.
base_model	String	The ID of the base model used in the deployment task.
base_capacity	Number	The minimum number of resource units required to run the base model.
capacity	Number	The number of resource units used by the deployment task.
ready_capacity	Number	The number of resource units that are ready to process requests immediately. Resource initialization speed or hardware status can limit this value.
workspace_id	String	The ID of the deployment task's workspace.
charge_type	String	The billing method for the deployment task. `post_paid`: Post-paid.
creator	String	The UID of the user who created the deployment task.
modifier	String	The UID of the user who last modified the deployment task.
plan	String	The billing model for the deployment task. This parameter is not returned for some billing models.
Returned only for Model Unit deployments.
model_unit_spec	String	The model unit specification.
enable_thinking	Boolean	Specifies if Thinking mode is enabled. This feature is only available for certain models.
max_context_length	Number	The maximum context length.
rpm_limit	String	The maximum number of requests per minute (RPM).
tpm_limit	Number	The maximum number of tokens per minute (TPM).
Returned only for provisioned throughput (PTU) deployments.
ptu_capacity	Object	This parameter takes effect only when `"plan": "ptu"` is set. Example: `"ptu_capacity": { "input_tpm": 10000, "output_tpm": 1000 }`.
ptu_capacity.input_tpm	Number	The maximum number of input tokens per minute (TPM) for the deployed model. This feature is supported by all models.
ptu_capacity.output_tpm	Number	The maximum number of output tokens per minute (TPM) for the deployed model. This feature is supported by all models.
ptu_capacity.thinking_output_tpm	Number	The maximum number of thinking output tokens per minute (TPM) for the deployed model. This feature is only available for certain models.

Error response

Response example

{
    "request_id": "ca218d57-b91b-46b2-bd35-c41c6287bcf4",
    "message": "Model: qwen-plus-20230703-cx7f not found!",
    "code": "NotFound"
}

Response parameters

Parameter	Type	Description
request_id	String	The unique ID of the request.
code	String	The error code.
message	String	The error message.

The following errors can occur when a request fails:

Error code	Error message	Reason
NotFound	Model: xxx not found!	You are creating a deployment task with a model that does not exist. You are querying, updating, or deleting a deployment task with a model that does not exist.
Conflict	Deployed model xxx already exists, please specify a suffix.	You are creating a deployment task with a suffix that is already in use.
InvalidParameter	Invalid capacity (xx), capacity must be larger than or equal to 0 and multiples of 1 and less than 1000!	You are creating or updating a deployment task with an invalid number of capacity units.

​Prerequisites

​Model deployment

​Endpoint

​Request examples

​Request parameters

​Supported models

​Response example

​Response parameters

​Error response

​Response example

​Response parameters

Prerequisites

Model deployment

Endpoint

Request examples

Request parameters

Supported models

Response example

Response parameters

Error response

Response example

Response parameters