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This topic is applicable only to the China (Beijing) region.

Prerequisites

You have read Dedicated Deployment Overview and Deploy Models Using APIs to understand how to use model deployment APIs and the basic steps for deploying models on Alibaba Cloud Model Studio.
You have configured your Model Studio API key. For more information, see Obtain an API Key.

Get a List of Deployable Models

GET https://dashscope.aliyuncs.com/api/v1/deployments/models

Request Example

Run the following command to list deployable models. Use version=v1.0 to retrieve a full response that includes deployment plans and templates.

curl "https://dashscope.aliyuncs.com/api/v1/deployments/models?page_no=1&page_size=100&version=v1.0&model_source=base" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json'

Query fine-tuned models:

curl "https://dashscope.aliyuncs.com/api/v1/deployments/models?page_no=1&page_size=100&version=v1.0&model_source=custom" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json'

Request Parameters

Parameter	Type	Passing Parameters	Required	Description
page_no	Number	query	No	Page number. Default is 1.
page_size	Number	query	No	Page size. Default is 50. Maximum is 100. Minimum is 1.
model_source	String	query	No	Model source. `base` means system models (default). `custom` means fine-tuned models.
version	String	query	No	API version. Use `v1.0`. When you use `v1.0`, the response includes full deployment plan and template information.

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

{
    "request_id": "f7da015c-ea90-4d96-af89-2f8d7604026a",
    "output": {
        "page_no": 1,
        "page_size": 100,
        "total": 5,
        "models": [
            {
                "model_name": "qwen3-8b",
                "plans": [
                    {
                        "plan": "mu",
                        "templates": [
                            {
                                "template_id": "MU1",
                                "template_name": "Single-Node Deployment – Standard Inference",
                                "template_type": "COUPLED",
                                "template_version": "v1",
                                "template_desc": "For standard inference scenarios",
                                "roles": {
                                    "unified": {
                                        "model_unit_spec": "MU1",
                                        "capacity_unit_per_instance": 4
                                    }
                                }
                            },
                            {
                                "template_id": "MU1-PD",
                                "template_name": "PD-Separated Deployment – Standard Inference",
                                "template_type": "SEPERATED",
                                "template_version": "v1",
                                "template_desc": "For PD-separated inference scenarios",
                                "roles": {
                                    "prefill": {
                                        "model_unit_spec": "MU1",
                                        "capacity_unit_per_instance": 4
                                    },
                                    "decode": {
                                        "model_unit_spec": "MU1",
                                        "capacity_unit_per_instance": 4
                                    }
                                }
                            }
                        ]
                    },
                    {
                        "plan": "lora"
                    }
                ]
            }
        ]
    }
}

Response Parameters

Parameter	Type	Description
models	Array	List of deployable models.
models[].model_name	String	Model name.
models[].plans	Array	List of supported deployment plans for this model. Returned when using `version=v1.0`.
models[].plans[].plan	String	Deployment plan type: `mu` (model unit), `cu` (compute unit), `ptu_v2` (pre-provisioned throughput v2), or `lora` (LoRA shared deployment).
models[].plans[].templates	Array	List of deployment templates. Returned when `plan=mu`.
page_no	Number	Page number of the query.
page_size	Number	Page size of the query.
total	Long	Total number of models that match the query criteria.

Template field description (templates)

Parameter	Type	Description
template_id	String	Template ID. Pass it as the `template_id` parameter in Create a Model Deployment Task.
template_name	String	Template display name.
template_type	String	Template type: `COUPLED` (non-PD-separated, uses the `capacity` parameter) or `SEPERATED` (PD-separated, uses `prefill_capacity` and `decode_capacity` parameters).
template_version	String	Template version.
template_desc	String	Template description.
roles	Object	Node role configuration. COUPLED mode has a `unified` node. SEPERATED mode has `prefill` and `decode` nodes.

Roles Node Fields

Parameter	Type	Description
model_unit_spec	String	Model unit specification.
capacity_unit_per_instance	Number	Capacity units per instance, also called base_capacity. When you create a deployment, `capacity` must be a multiple of this value.

Create a Model Deployment Task

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

Request Example

Example 1: Model Unit Deployment (COUPLED Mode)

Use template_id to specify MU1 and set capacity to the number of capacity units:

curl "https://dashscope.aliyuncs.com/api/v1/deployments" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model_name": "qwen3-8b",
    "plan": "mu",
    "template_id": "MU1",
    "capacity": 4
}'

Example 2: Model Unit Deployment (PD-Separated Mode)

Use the MU1-PD template. Set prefill_capacity and decode_capacity:

curl "https://dashscope.aliyuncs.com/api/v1/deployments" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model_name": "qwen3-8b",
    "plan": "mu",
    "template_id": "MU1-PD",
    "prefill_capacity": 4,
    "decode_capacity": 8
}'

Example 3: PTU v2 Deployment

Billed by token usage:

curl "https://dashscope.aliyuncs.com/api/v1/deployments" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model_name": "qwen3-8b",
    "plan": "ptu_v2"
}'

Example 4: LoRA Shared Deployment

Billed by token usage:

curl "https://dashscope.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"
}'

Request Parameters

Parameter	Type	Parameter passing	Required	Description
model_name	String	body	Yes	Name of the model to deploy.
plan	String	body	Yes	Deployment plan: `mu` (model unit), `cu` (compute unit), `ptu_v2` (pre-provisioned throughput v2), or `lora` (LoRA shared deployment).
template_id	String	body	This parameter is required.	Template ID. Must match the `template_id` returned by the Get Deployable Models API. Required when `plan` is `mu`. We recommend using this parameter to specify the model unit spec.
deploy_spec (deprecated)	String	body	No	Model unit spec. Deprecated.
capacity	Number	body	This parameter is required.	Target number of capacity units. Required for COUPLED mode (non-PD-separated). Must be a multiple of `capacity_unit_per_instance`. Ignored but required when billing by token usage (`plan` is `lora`).
prefill_capacity	Number	body	This parameter is required.	Prefill capacity. Required for PD-separated mode (`template_type` is `SEPERATED`).
decode_capacity	Number	body	This parameter is required.	Decode capacity. Required for PD-separated mode (`template_type` is `SEPERATED`).
name	String	body	No	Service display name.
suffix	String	body	No	When you deploy a model, a new model name is generated. The suffix sets the suffix for the new model name. Max length is 8 characters. Must be globally unique. You can omit the suffix for the first deployment of a model. You must set it for later deployments of the same model.
charge_type	String	body	No	Billing method: `post_paid` (pay-as-you-go, default) or `pre_paid` (subscription).
pre_paid_info	Object	body	This parameter is required.	Subscription info. Required when `charge_type` is `pre_paid`. Includes: `auto_renewal` (Boolean, enable auto-renewal), `duration` (Number, subscription duration in months), and `auto_renewal_duration` (Number, auto-renewal duration in months).
pre_paid_info.auto_renewal	Boolean	body	Yes	Enable auto-renewal.
pre_paid_info.duration	Integer	body	Yes	Subscription duration in months.
pre_paid_info.auto_renewal_duration	Integer	body	Conditionally required	Auto-renewal duration in months. Required when autoRenewal=true.
enable_thinking	Boolean	body	No	Enable thinking mode. Supported by some models.
max_context_length	Number	body	No	Maximum context length. Supported by some models.
quantization_precision	String	body	No	Quantization precision.
qpm_limit	Number	body	No	QPM rate limit. Requests per minute. Supported only by some models with `plan` = `mu`.
tpm_limit	Number	body	No	TPM rate limit. Tokens per minute. Supported only by some models with `plan` = `mu`.

Supported Models

Model Unit deployment supports features such as rate limiting and inference acceleration. This table shows which features are supported.

Text generation
Multimodal
Speech synthesis

Qwen
GLM
DeepSeek
More models

Model name	Model code	Model unit specification	Hourly unit price (CNY) Minimum billing: minute	Monthly unit price (CNY) Minimum billing: day
Qwen3.6-35B-A3B	qwen3.6-35b-a3b	MU1 x 8	¥432	¥208,944
		MU2 x 8	¥504	¥240,288
		MU3 x 8	¥1,096	¥527,752
		MU8 x 1	¥47	¥22,400
		MU9 x 1	¥51	¥24,600
Qwen3.6-27B	qwen3.6-27b	MU9 x 1	¥51	¥24,600
Qwen3.6-Flash-2026-04-16	qwen3.6-flash-2026-04-16	MU1 x 2	¥108	¥52,236
Qwen3.6-Flash-2026-04-16	qwen3.6-flash-2026-04-16	MU3 x 8	¥1,096	¥527,752
Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	MU1 x 8 MU1 x 16 (PD separation mode)	¥432 PD separation mode: ¥864	¥208,944 PD separation mode: ¥417,888

Qwen3.5-397B-A17B	qwen3.5-397b-a17b	MU3 x 8 MU3 x 16 (PD separation mode)	¥1,096 PD separation mode: ¥2,192	¥527,752 PD separation mode: ¥1,055,504
Qwen3.5-397B-A17B	qwen3.5-397b-a17b	MU6 x 16	¥400	¥193,424
Qwen3.5-122B-A10B	qwen3.5-122b-a10b	MU1 x 4	¥216	¥104,472
Qwen3.5-122B-A10B	qwen3.5-122b-a10b	MU6 x 16	¥400	¥193,424
Qwen3.5-35B-A3B	qwen3.5-35b-a3b	MU1 x 2	¥108	¥52,236
		MU2 x 8	¥504	¥240,288
		MU3 x 8	¥1,096	¥527,752
		MU9 x 1	¥51	¥24,600
Qwen3.5-27B	qwen3.5-27b	MU2 x 8	¥504	¥240,288
		MU3 x 8	¥1,096	¥527,752
		MU8 x 1	¥47	¥22,400
		MU9 x 1	¥51	¥24,600
Qwen3.5-9B	qwen3.5-9b	MU1 x 2	¥108	¥52,236
Qwen3.5-9B	qwen3.5-9b	MU2 x 8	¥504	¥240,288
Qwen3.5-Flash-2026-02-23	qwen3.5-flash-2026-02-23	MU1 x 2	¥108	¥52,236
Qwen3.5-Plus-2026-02-15	qwen3.5-plus-2026-02-15	MU1 x 8 MU1 x 16 (PD separation mode)	¥432 PD separation mode: ¥864	¥208,944 PD separation mode: ¥417,888
		MU2 x 8	¥504	¥240,288
		MU3 x 8 MU3 x 16 (PD separation mode)	¥1,096 PD separation mode: ¥2,192	¥527,752 PD separation mode: ¥1,055,504

Qwen3-235B-A22B-Instruct-2507	qwen3-235b-a22b-instruct-2507	MU1 x 4	¥216	¥104,472
		MU2 x 8	¥504	¥240,288
		MU3 x 8	¥1,096	¥527,752
Qwen3-32B	qwen3-32b	MU6 x 16	¥400	¥193,424
Qwen3-30B-A3B-Thinking-2507	qwen3-30b-a3b-thinking-2507	MU1 x 2	¥108	¥52,236
Qwen3-8B	qwen3-8b	MU1 x 2	¥108	¥52,236
Qwen3-8B	qwen3-8b	MU2 x 2	¥126	¥60,072
Qwen3-4B	qwen3-4b	MU1 x 2	¥108	¥52,236
Qwen3-4B	qwen3-4b	MU5 x 1	¥21	¥10,139
Qwen3-Embedding-0.6B	qwen3-embedding-0.6b	MU5 x 1	¥21	¥10,139
Qwen3-Embedding-0.6B	qwen3-embedding-0.6b	MU6 x 1	¥25	¥12,089
Qwen3-MoE-Rerank-0.6B	qwen3-moe-rerank-0.6b	MU5 x 1	¥21	¥10,139
Qwen3-Rerank-0.6B	qwen3-rerank-0.6b	MU5 x 1	¥21	¥10,139
Qwen3-Rerank-0.6B	qwen3-rerank-0.6b	MU6 x 1	¥25	¥12,089
Qwen3-Max-2025-09-23	qwen3-max-2025-09-23	MU2 x 8	¥504	¥240,288
Qwen3-Max-2025-09-23	qwen3-max-2025-09-23	MU3 x 8	¥1,096	¥527,752
Qwen3-Rerank	qwen3-rerank	MU5 x 1	¥21	¥10,139

Qwen2.5-72B (Open Source)	qwen2.5-72b-instruct	MU1 x 8	¥432	¥208,944
Qwen2.5-14B (Open Source)	qwen2.5-14b-instruct	MU1 x 2	¥108	¥52,236
Qwen2.5-7B (Open Source)	qwen2.5-7b-instruct	MU1 x 2	¥108	¥52,236
Qwen2.5-7B (Open Source)	qwen2.5-7b-instruct	MU5 x 1	¥21	¥10,139

Qwen-Plus-2025-07-28	qwen-plus-2025-07-28	MU1 x 4 MU1 x 16 (PD separation mode)	¥216 PD separation mode: ¥864	¥104,472 PD separation mode: ¥417,888
Qwen-Plus-2025-12-01	qwen-plus-2025-12-01	MU1 x 4	¥216	¥104,472
Qwen-Plus-Character-2025-11-06	qwen-plus-character-2025-11-06	MU1 x 4	¥216	¥104,472

Model name	Model code	Model unit specification	Hourly unit price (CNY) Minimum billing: minute	Monthly unit price (CNY) Minimum billing: day
GLM-5.1	glm-5.1	MU2 x 8	¥504	¥240,288
		MU3 x 16 (PD separation mode)	PD separation mode: ¥2,192	PD separation mode: ¥1,055,504
		MU6 x 16	¥400	¥193,424
GLM-5	glm-5	MU3 x 16 (PD separation mode)	PD separation mode: ¥2,192	PD separation mode: ¥1,055,504
GLM-4.7	glm-4.7	MU6 x 32 (PD separation mode)	PD separation mode: ¥800	PD separation mode: ¥386,848

Model name	Model code	Model unit specification	Hourly unit price (CNY) Minimum billing: minute	Monthly unit price (CNY) Minimum billing: day
DeepSeek-v4-Flash	deepseek-v4-flash	MU1 x 8	¥432	¥208,944
MU3 x 8	¥1,096	¥527,752
DeepSeek-v3.2	deepseek-v3.2	MU2 x 16 (PD separation mode)	PD separation mode: ¥1,008	PD separation mode: ¥480,576

Model name

Model code

Model unit specification

Hourly unit price (CNY)

Minimum billing: minute

Monthly unit price (CNY)

Minimum billing: day

DeepSeek-v4-Flash

deepseek-v4-flash

MU1 x 8

¥432

¥208,944

MU3 x 8

¥1,096

¥527,752

DeepSeek-v3.2

deepseek-v3.2

MU2 x 16 (PD separation mode)

PD separation mode: ¥1,008

PD separation mode: ¥480,576

Model name	Model code	Model unit specification	Hourly unit price (CNY) Minimum billing: minute	Monthly unit price (CNY) Minimum billing: day
Kimi-K2.5	kimi-k2.5	MU2 x 8	¥504	¥240,288

Model type:

Instruct - After deployment, the model performs inference in non-thinking mode.
Thinking - After deployment, the model performs inference in thinking mode.

Model deployment type:

PD separation mode - Reduces first-token latency and increases throughput. For models deployed in this mode, during inference the first-token computation (Prefill) and subsequent-token computation (Decode) — two computation phases — are split onto different compute nodes.

Qwen-VL
Qwen Omni

Model name	Model code	Model unit specification	Hourly unit price (CNY) Minimum billing: minute	Monthly unit price (CNY) Minimum billing: day
Qwen3-VL-235B-A22B-Thinking	qwen3-vl-235b-a22b-thinking	MU1 x 8	¥432	¥208,944
		MU2 x 8	¥504	¥240,288
		MU3 x 8	¥1,096	¥527,752
Qwen3-VL-32B-Instruct	qwen3-vl-32b-instruct	MU2 x 8	¥504	¥240,288
Qwen3-VL-32B-Instruct	qwen3-vl-32b-instruct	MU3 x 8	¥1,096	¥527,752
Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	MU1 x 2	¥108	¥52,236
Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	MU5 x 1	¥21	¥10,139
Qwen3-VL-4B-Instruct	qwen3-vl-4b-instruct	MU1 x 2	¥108	¥52,236
Qwen3-VL-2B-Instruct	qwen3-vl-2b-instruct	MU5 x 1	¥21	¥10,139
Qwen3-VL-Embedding-2B	qwen3-vl-embedding-2b	MU5 x 1	¥21	¥10,139
Qwen3-VL-Flash-2025-10-15	qwen3-vl-flash-2025-10-15	MU1 x 4	¥216	¥104,472
Qwen3-VL-Plus-2025-09-23	qwen3-vl-plus-2025-09-23	MU1 x 4	¥216	¥104,472

Qwen-VL-Max-2025-08-13	qwen-vl-max-2025-08-13	MU6 x 4	¥100	¥48,356

Model name	Model code	Model unit specification	Hourly unit price (CNY) Minimum billing: minute	Monthly unit price (CNY) Minimum billing: day
Qwen3.5-Omni-Flash	qwen3.5-omni-flash	MU8 x 1	¥47	¥22,400
MU9 x 1	¥51	¥24,600

Model name

Model code

Model unit specification

Hourly unit price (CNY)

Minimum billing: minute

Monthly unit price (CNY)

Minimum billing: day

Qwen3.5-Omni-Flash

qwen3.5-omni-flash

MU8 x 1

¥47

¥22,400

MU9 x 1

¥51

¥24,600

Model type:

Instruct - After model deployment, inference is performed in non-thinking mode.
Thinking - After model deployment, inference is performed in thinking mode.
Instruct/Thinking - You can choose whether to enable thinking mode during model deployment.

Model name	Model code	Model unit specification	Hourly unit price (CNY)	Monthly unit price (CNY)
cosyvoice-v3-flash	cosyvoice-v3-flash	MU5	¥21	¥10,139

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

{
    "request_id": "f2ae64f7-83cc-410c-bc0b-840443f7eb86",
    "output": {
        "deployed_model": "qwen3-8b-20260115-abcd",
        "name": "My Model Service",
        "model_name": "qwen3-8b",
        "base_model": "qwen3-8b",
        "status": "PENDING",
        "capacity": 4,
        "ready_capacity": 0,
        "base_capacity": 4,
        "workspace_id": "llm-8v53e*******",
        "charge_type": "post_paid",
        "plan": "mu",
        "model_unit_spec": "MU1",
        "creator": "16542902******",
        "modifier": "16542902******",
        "qpm_limit": 100000000,
        "tpm_limit": 3600000,
        "mu_capacity": {
            "unified": {
                "base_capacity": 4,
                "model_unit_spec": "MU1",
                "ready_capacity": 0,
                "capacity": 4
            }
        },
        "gmt_create": "2026-01-15T10:00:00",
        "gmt_modified": "2026-01-15T10:00:00"
    }
}

Parameter	Type	Description
request_id	String	ID of this request.
output	Object	Detailed information about this deployment task.
deployed_model	String	Unique identifier for the new model. Pass it in SDK parameters when you call the model.
name	String	Service display name.
model_name	String	Model name used for this deployment task.
base_model	String	Base model ID for the model used in this deployment task.
status	String	Status of the deployment task. PENDING — Creating the deployment task. DEPLOYING — Deploying. RUNNING — Running and ready to process requests. SCALING — Scaling. UPDATING — Updating the deployment task. UPDATING_PAUSED — Update paused. SUSPENDING — Suspending (due to overdue payment). SUSPENDED — Suspended (due to overdue payment). STOPPING — Stopping. STOPPED — Stopped. No longer billed. STARTING — Starting (from STOPPED or FAILED state). FAILED — Failed to create or update the deployment task. DELETING — Deleting the deployment task.
capacity	Number	Target number of capacity units for this deployment task.
ready_capacity	Number	Number of capacity units that are ready and can immediately process requests.
base_capacity	Number	Base capacity per instance.
workspace_id	String	ID of the workspace where this deployment task belongs.
charge_type	String	`post_paid`: pay-as-you-go. `pre_paid`: subscription.
plan	String	Billing mode for this deployment task.
model_unit_spec	String	Model unit specification.
gmt_create	String	Time when the deployment task was created.
gmt_modified	String	You can modify the deployment task time.
creator	String	UID of the user who created this deployment task.
modifier	String	UID of the account that last performed an operation on this deployment task.
fail_reason	String	Failure reason. Returned only when status is FAILED.
enable_thinking	Boolean	Enable thinking mode. Supported by some models.
max_context_length	Number	Maximum context length limit.
qpm_limit	Number	QPM rate limit. Requests per minute.
tpm_limit	Number	TPM rate limit. Tokens per minute.
quantization_precision	String	Quantization precision.
Returned only for model unit (mu) deployments.
mu_capacity	Object	MU capacity details. COUPLED mode has a `unified` node. SEPERATED mode has `prefill` and `decode` nodes. Each node includes: base_capacity, model_unit_spec, ready_capacity, and capacity.
pre_paid_info	Object	Subscription information.
pre_paid_info.auto_renewal	Boolean	Enable auto-renewal.
pre_paid_info.duration	Integer	Subscription duration in months.
pre_paid_info.auto_renewal_duration	Integer	Auto-renewal duration in months.
pre_paid_instance_id	String	Subscription instance ID.
pre_paid_gmt_expired	String	Subscription expiration time.
Returned only for pre-provisioned throughput v2 (ptu_v2) deployments.
ptu_capacity	Object	PTU v2 capacity info. Includes: `input_tpm_quota` (Number, input TPM quota) `output_tpm_quota` (Number, output TPM quota)
pre_paid_info	Object	Subscription information.
pre_paid_info.auto_renewal	Boolean	Enable auto-renewal.
pre_paid_info.duration	Integer	Subscription duration in months.
pre_paid_info.auto_renewal_duration	Integer	Auto-renewal duration in months.
pre_paid_instance_id	String	Subscription instance ID.
pre_paid_gmt_expired	String	Subscription expiration time.

Query a Model Deployment Task

GET https://dashscope.aliyuncs.com/api/v1/deployments/{deployed_model}

Request Example

curl "https://dashscope.aliyuncs.com/api/v1/deployments/qwen3-8b-20260115-abcd" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json'

Request Parameters

Parameter	Type	Passing Parameters	Required	Description
deployed_model	String	path	Yes	Unique identifier for the deployed model. Get it from Create a Model Deployment Task or List Model Deployment Tasks.

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

{
    "request_id": "d8b8c47b-ae32-4c41-b9f4-9a1e2b3c4d5e",
    "output": {
        "deployed_model": "qwen3-8b-20260115-abcd",
        "name": "My Model Service",
        "model_name": "qwen3-8b",
        "base_model": "qwen3-8b",
        "status": "RUNNING",
        "capacity": 4,
        "ready_capacity": 4,
        "base_capacity": 4,
        "workspace_id": "llm-8v53e*******",
        "charge_type": "post_paid",
        "plan": "mu",
        "model_unit_spec": "MU1",
        "creator": "16542902******",
        "modifier": "16542902******",
        "qpm_limit": 100000000,
        "tpm_limit": 3600000,
        "mu_capacity": {
            "unified": {
                "base_capacity": 4,
                "model_unit_spec": "MU1",
                "ready_capacity": 4,
                "capacity": 4
            }
        },
        "gmt_create": "2026-01-15T10:00:00",
        "gmt_modified": "2026-01-15T10:30:00"
    }
}

Response Parameters

The response parameters are the same as those for creating a model deployment task. For more information, see Response Parameters for Create a Model Deployment Task.

List Model Deployment Tasks

GET https://dashscope.aliyuncs.com/api/v1/deployments

Request Example

curl "https://dashscope.aliyuncs.com/api/v1/deployments?page_no=1&page_size=10" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json'

Request Parameters

Parameter	Type	Parameter passing	Required	Description
Age	Number	query	No	Page number. Default is 1.
page_size	Number	query	No	Page size. Default is 10. Maximum is 100.

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

{
    "request_id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "output": {
        "page_no": 1,
        "page_size": 10,
        "total": 2,
        "deployments": [
            {
                "deployed_model": "qwen3-8b-20260115-abcd",
                "name": "My Model Service",
                "model_name": "qwen3-8b",
                "base_model": "qwen3-8b",
                "status": "RUNNING",
                "capacity": 4,
                "ready_capacity": 4,
                "base_capacity": 4,
                "workspace_id": "llm-8v53e*******",
                "charge_type": "post_paid",
                "plan": "mu",
                "model_unit_spec": "MU1",
                "creator": "16542902******",
                "modifier": "16542902******",
                "qpm_limit": 100000000,
                "tpm_limit": 3600000,
                "mu_capacity": {
                    "unified": {
                        "base_capacity": 4,
                        "model_unit_spec": "MU1",
                        "ready_capacity": 4,
                        "capacity": 4
                    }
                },
                "gmt_create": "2026-01-15T10:00:00",
                "gmt_modified": "2026-01-15T10:30:00"
            }
        ]
    }
}

Response Parameters

Parameter	Type	Description
page_no	Number	Page number of the query.
page_size	Number	Page size of the query.
total	Long	Total number of deployment tasks that match the query criteria.
deployments	Array	List of deployment tasks. The fields for each element match the response parameters for Create a Model Deployment Task. For details, see the response parameters for Create a Model Deployment Task.

Update a Model Deployment Task

Updating a model deployment task is equivalent to scaling the deployment service. You can call this API only when the service status is RUNNING or SCALING. If you call this API when the service is in another state, an OperationDenied error is returned.

PUT https://dashscope.aliyuncs.com/api/v1/deployments/{deployed_model}/scale

Request Example

Scale in COUPLED mode:

curl -X PUT "https://dashscope.aliyuncs.com/api/v1/deployments/qwen3-8b-20260115-abcd/scale" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json' \
    --data '{
    "capacity": 8
}'

Scale in PD-separated mode:

curl -X PUT "https://dashscope.aliyuncs.com/api/v1/deployments/qwen3-8b-20260115-abcd/scale" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json' \
    --data '{
    "prefill_capacity": 4,
    "decode_capacity": 8
}'

Request Parameters

Parameter	Type	Passing parameters	Required	Description
deployed_model	String	path	Yes	Unique identifier for the deployed model.
capacity	Number	body	Conditionally required	Target number of capacity units for scaling. Required for COUPLED mode (non-PD-separated). Must be a multiple of `base_capacity`.
prefill_capacity	Number	body	Conditionally required	Target prefill capacity. Required for PD-separated mode.
decode_capacity	Number	body	A condition is required.	Target decode capacity. Required for PD-separated mode.
ptu_capacity	Object	body	Conditionally required	PTU v2 capacity info. Includes: `input_tpm_quota` (Number, input TPM quota) `output_tpm_quota` (Number, output TPM quota)

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

{
    "request_id": "e5f6a7b8-c9d0-1234-5678-abcdef012345",
    "output": {
        "deployed_model": "qwen3-8b-20260115-abcd",
        "name": "My Model Service",
        "model_name": "qwen3-8b",
        "base_model": "qwen3-8b",
        "status": "SCALING",
        "capacity": 8,
        "ready_capacity": 4,
        "base_capacity": 4,
        "workspace_id": "llm-8v53e*******",
        "charge_type": "post_paid",
        "plan": "mu",
        "model_unit_spec": "MU1",
        "creator": "16542902******",
        "modifier": "16542902******",
        "qpm_limit": 100000000,
        "tpm_limit": 3600000,
        "mu_capacity": {
            "unified": {
                "base_capacity": 4,
                "model_unit_spec": "MU1",
                "ready_capacity": 4,
                "capacity": 8
            }
        },
        "gmt_create": "2026-01-15T10:00:00",
        "gmt_modified": "2026-01-15T11:00:00"
    }
}

Response Parameters

The response parameters are the same as those for creating a model deployment task. For more information, see the response parameters for Create a Model Deployment Task.

Stop a Deployed Model

Only model unit (mu) deployments support stopping the service. You can call this API only when the service status is RUNNING or SCALING. If you call this API for cu, ptu_v2, or lora deployments, an UnsupportedOperation error is returned. After the service is stopped, it is no longer billed. You can restart the service using the API Details API.

POST https://dashscope.aliyuncs.com/api/v1/deployments/{deployed_model}/stop

Request Example

curl -X POST "https://dashscope.aliyuncs.com/api/v1/deployments/qwen3-8b-20260115-abcd/stop" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json'

Request Parameters

Parameter	Type	Passing parameters	Required	Description
deployed_model	String	path	Yes	Unique identifier for the deployed model.

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

{
    "request_id": "f1a2b3c4-d5e6-7890-abcd-ef1234567890",
    "output": {
        "deployed_model": "qwen3-8b-20260115-abcd",
        "name": "My Model Service",
        "model_name": "qwen3-8b",
        "base_model": "qwen3-8b",
        "status": "STOPPING",
        "capacity": 4,
        "ready_capacity": 4,
        "base_capacity": 4,
        "workspace_id": "llm-8v53e*******",
        "charge_type": "post_paid",
        "plan": "mu",
        "model_unit_spec": "MU1",
        "creator": "16542902******",
        "modifier": "16542902******",
        "qpm_limit": 100000000,
        "tpm_limit": 3600000,
        "mu_capacity": {
            "unified": {
                "base_capacity": 4,
                "model_unit_spec": "MU1",
                "ready_capacity": 4,
                "capacity": 4
            }
        },
        "gmt_create": "2026-01-15T10:00:00",
        "gmt_modified": "2026-01-15T12:00:00"
    }
}

Response Parameters

The response parameters are the same as those for creating a model deployment task. For more information, see the response parameters for Create a Model Deployment Task.

Restart a Deployed Model

POST https://dashscope.aliyuncs.com/api/v1/deployments/{deployed_model}/start

Request Example

curl -X POST "https://dashscope.aliyuncs.com/api/v1/deployments/qwen3-8b-20260115-abcd/start" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json'

Request Parameters

Parameter	Type	Passing parameters	Required	Description
deployed_model	String	path	Yes	Unique identifier for the deployed model. Get it from Create a Model Deployment Task or List Model Deployment Tasks.

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

After the service starts, the status is STARTING and then changes to RUNNING

{
  "request_id": "xxx-xxx-xxx",
  "output": {
    "deployed_model": "qwen-7b-chat-ft-20240101-abcd",
    "model_name": "qwen-7b-chat-ft",
    "base_model": "qwen-7b-chat",
    "status": "STARTING",
    "capacity": 1,
    "ready_capacity": 0,
    "base_capacity": 1,
    "plan": "mu",
    "model_unit_spec": "MU5",
    "workspace_id": "workspace-xxx",
    "charge_type": "post_paid",
    "creator": "user123",
    "modifier": "user123",
    "qpm_limit": 100000000,
    "tpm_limit": 3600000,
    "mu_capacity": {
      "unified": {
        "base_capacity": 1,
        "model_unit_spec": "",
        "ready_capacity": 0,
        "capacity": 1
      }
    },
    "gmt_create": "2024-01-01T10:00:00",
    "gmt_modified": "2024-01-01T13:00:00"
  }
}

Response Parameters

The response parameters are the same as those for creating a model deployment task. For more information, see the response parameters for Create a Model Deployment Task.

Delete a Model Deployment Task

You can delete a service only when its status is STOPPED or FAILED. For services in the RUNNING state, you must first call the API Details API to stop them.

DELETE https://dashscope.aliyuncs.com/api/v1/deployments/{deployed_model}

Request Example

curl -X DELETE "https://dashscope.aliyuncs.com/api/v1/deployments/qwen3-8b-20260115-abcd" \
    --header "Authorization: Bearer ${DASHSCOPE_API_KEY}" \
    --header 'Content-Type: application/json'

Request Parameters

Parameter	Type	Parameter passing	Required	Description
deployed_model	String	path	Yes	Unique identifier for the deployed model.

Response Example and Parameters

Click to view the details.

After you run the command, the following result is returned:

{
    "request_id": "g1h2i3j4-k5l6-7890-mnop-qr1234567890",
    "output": {
        "deployed_model": "qwen3-8b-20260115-abcd",
        "name": "My Model Service",
        "model_name": "qwen3-8b",
        "base_model": "qwen3-8b",
        "status": "DELETING",
        "capacity": 4,
        "ready_capacity": 0,
        "base_capacity": 4,
        "workspace_id": "llm-8v53e*******",
        "charge_type": "post_paid",
        "plan": "mu",
        "model_unit_spec": "MU1",
        "creator": "16542902******",
        "modifier": "16542902******",
        "gmt_create": "2026-01-15T10:00:00",
        "gmt_modified": "2026-01-15T14:00:00"
    }
}

Response Parameters

The response parameters are the same as those for creating a model deployment task. For more information, see the response parameters for Create a Model Deployment Task.

Abnormal Response

{
    "request_id": "6fec0a3f-a1df-4f89-8c8f-33cb0db9f5b0",
    "code": "InvalidParameter",
    "message": "capacity is required when template_type is COUPLED"
}

Response Parameters

Parameter	Type	Description
request_id	String	System-generated ID for this request.
code	String	Error code that identifies the error type.
message	String	Error details for troubleshooting.

Common Errors

Error Reason	Description
`InvalidParameter`	Parameter error. For example, a required parameter is missing, a parameter value is invalid, or template_id and deploy_spec are passed at the same time.
`AccessDenied`	Insufficient permissions or resource does not exist.
`OperationDenied`	The operation is not allowed in the current state. For example, scaling a service that is not in the RUNNING state, or deleting a service that is not in the STOPPED or FAILED state.
`UnsupportedOperation`	The current deployment plan does not support this operation. For example, cu deployments do not support stopping the service.
`StockLimit`	Insufficient resource stock. Cannot complete scaling or deployment.
`InternalError`	Internal error.
`NotFound`	The specified deployment task does not exist.
`Conflict`	Operation conflict. For example, the service is performing another operation.

​Prerequisites

​Get a List of Deployable Models

​Request Example

​Request Parameters

​Response Example and Parameters

Response Parameters

Template field description (templates)

Roles Node Fields

​Create a Model Deployment Task

​Request Example

​Example 1: Model Unit Deployment (COUPLED Mode)

​Example 2: Model Unit Deployment (PD-Separated Mode)

​Example 3: PTU v2 Deployment

​Example 4: LoRA Shared Deployment

​Request Parameters

​Supported Models

​Response Example and Parameters

​Query a Model Deployment Task

​Request Example

​Request Parameters

​Response Example and Parameters

Response Parameters

​List Model Deployment Tasks

​Request Example

​Request Parameters

​Response Example and Parameters

Response Parameters

​Update a Model Deployment Task

​Request Example

​Request Parameters

​Response Example and Parameters

Response Parameters

​Stop a Deployed Model

​Request Example

​Request Parameters

​Response Example and Parameters

Response Parameters

​Restart a Deployed Model

​Request Example

​Request Parameters

​Response Example and Parameters

Response Parameters

​Delete a Model Deployment Task

​Request Example

​Request Parameters

​Response Example and Parameters

Response Parameters

​Abnormal Response

​Response Parameters

​Common Errors

Prerequisites

Get a List of Deployable Models

Request Example

Request Parameters

Response Example and Parameters

Create a Model Deployment Task

Request Example

Example 1: Model Unit Deployment (COUPLED Mode)

Example 2: Model Unit Deployment (PD-Separated Mode)

Example 3: PTU v2 Deployment

Example 4: LoRA Shared Deployment

Request Parameters

Supported Models

Response Example and Parameters

Query a Model Deployment Task

Request Example

Request Parameters

Response Example and Parameters

List Model Deployment Tasks

Request Example

Request Parameters

Response Example and Parameters

Update a Model Deployment Task

Request Example

Request Parameters

Response Example and Parameters

Stop a Deployed Model

Request Example

Request Parameters

Response Example and Parameters

Restart a Deployed Model

Request Example

Request Parameters

Response Example and Parameters

Delete a Model Deployment Task

Request Example

Request Parameters

Response Example and Parameters

Abnormal Response

Response Parameters

Common Errors