How to check model training and deployment pricing - Alibaba Cloud Model Studio

Training billing

Text generation models – Qwen

Note

For the training workflow, see Fine-tune Qwen. After training completes, deploy the new model before evaluating or calling it.

Method

Billed by training tokens

Formula

Model training fee = (Total tokens in training data + Total tokens in mixed training data) × Number of epochs × Training unit price (Minimum billing unit: 1 token)

View the estimated training fee at the bottom of the model training console, and click Computing Details to view the total number of training tokens, number of epochs, and training unit price.

Unit price for training

The following table lists the unit prices for training pre-trained models. The unit price for training a custom model matches that of the corresponding pre-trained model.

Qwen

Service	Code	Price
Qwen3-32B	qwen3-32b	$0.008/1,000 tokens
Qwen3-14B	qwen3-14b	$0.0016/1,000 tokens

Qwen-VL

Service	Code	Price
Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	$0.002/1,000 tokens
Qwen3-VL-8B-Thinking	qwen3-vl-8b-thinking	$0.002/1,000 tokens

Image generation models – Wan

Note

For the training workflow, see Fine-tune image generation models. After training completes, deploy the new model before calling it.

Method	Billed by training tokens
Formula	Model training fee = Total training tokens × Training unit price (Billing unit: per 1,000 tokens)

Formula for total training tokens

$T r ainin g T o k e n s T o t a l \approx ma x_s t e p s \times L_{s t e p}$

Where:

max_steps: A hyperparameter specified during training, representing the maximum number of training steps (configured when creating a fine-tuning job).
L_step: The token consumption per step. The formula is:

$L_{s t e p} = i \in ba t c h \sum L_{i t e m}^{(i)} \leq L_{ma x}$

L_step is approximately equal to L_max. L_max is determined by the max_token_length and generation_type, as shown below:

generation_type	max_token_length	L_max
t2i (text-to-image)	1k	12,800
t2i (text-to-image)	2k	23,220
i2i (image-to-image)	1k	23,220
i2i (image-to-image)	2k	32,000

Note

The above formula provides an approximation. Actual billing is based on the usage field returned by the system.

Model	Code	Training price (per 1K tokens)
Wan image generation	wan2.7-image-pro	$0.015
Wan image generation	wan2.7-image	$0.015

Billing example

Suppose you fine-tune the wan2.7-image-pro model for t2i. The parameters are: max_steps = 200, max_token_length = "1k", and the training price is $0.015 per 1,000 tokens:

From the table: L_max = 12,800 (generation_type=t2i, max_token_length=1k), L_step ≈ L_max = 12,800
Total training tokens ≈ 200 × 12800 = 2560000 = 2560 thousand tokens
Model training fee ≈ 2560× 0.015 = $38.4

Video generation models – Wan

Note

For the training workflow, see Fine-tuning video generation models. After training completes, deploy the new model before calling it.

Method	Billed by training tokens
Formula	Model training fee = Total training tokens × Training unit price (Billing unit: per 1,000 tokens)

Formula for total training tokens

$T r ainin g T o k e n s T o t a l = (i = 1 \sum N billing duration of video_{i}) \times \frac{ma x _ p i x e l s}{1024} \times n_e p oc h s$

Where:

N: Total number of videos in the training set.
max_pixels: A hyperparameter specified during training, representing the maximum number of pixels for a video (configured when creating a fine-tuning job).
n_epochs: A hyperparameter specified during training, representing the number of loops (configured when creating a fine-tuning job).
- The conversion between n_epochs and steps is: steps = n_epochs × ⌈dataset_size / batch_size⌉, i.e., n_epochs = steps / ⌈dataset_size / batch_size⌉.
- When the dataset contains only 1 sample and batch_size = 1, n_epochs = steps. We recommend a total of at least 800 steps.
Billing duration calculation rule for a single video: First, round the original video duration (in seconds) to the nearest integer, then determine the final value based on model limits.
- wan2.7 model: Billing duration=min(10, rounded duration), meaning a single video is billed for a maximum of 10 seconds.
- wan2.6 model: Billing duration=min(10, rounded duration), meaning a single video is billed for a maximum of 10 seconds.
- wan2.5 model: Billing duration=min(10, rounded duration), meaning a single video is billed for a maximum of 10 seconds.
- wan2.2 model: Billing duration=min(5, rounded duration), meaning a single video is billed for a maximum of 5 seconds.

Model	Code	Training price (per 1K tokens)
Image-to-video (first frame)	wan2.7-i2v	$0.3
	wan2.6-i2v	$0.08
	wan2.5-i2v-preview	$0.05
	wan2.2-i2v-flash	$0.03
Image-to-video (first and last frames)	wan2.2-kf2v-flash	$0.03

Billing examples

wan2.7-i2v cost estimation (single data)

Assume a training set contains 1 video with a duration of 10 seconds. With batch_size = 1 (recommended), n_epochs = steps / ⌈1(dataset_size) / 1(batch_size)⌉ = steps.

Training unit price = $0.3/thousand tokens. Taking max_pixels = 36864 and n_epochs = 800 as an example:

Total training tokens = 10 × (36864 / 1024) × 800 = 288,000 = 288 thousand tokens
Model training fee = 288 × $0.3 = $86.4

max_pixels	Common steps	n_epochs	Estimated tokens	Estimated cost (USD)
36864	800	800	288,000	$86.4
	1,000	1,000	360,000	$108
	2,000	2,000	720,000	$216
65536	800	800	512,000	$153.6
	1,000	1,000	640,000	$192
	2,000	2,000	1,280,000	$384
102400	800	800	800,000	$240
	1,000	1,000	1,000,000	$300
	2,000	2,000	2,000,000	$600

wan2.7-i2v cost estimation (multiple data)

Assume a training set contains 2 videos with durations of 3.4 seconds and 11.5 seconds. Parameters: max_pixels = 36864, n_epochs = 800. Training unit price = $0.3/thousand tokens:

Duration calculation:
- Video 1: 3.4 seconds is rounded to 3. Billable duration = min(10, 3) = 3.
- Video 2: 11.5 seconds is rounded to 11. Billable duration = min(10, 11) = 10.
- Total billable duration = 3 + 10 = 13 seconds.
Total training tokens = 13 × (36864/1024) × 800 = 374,400 = 374.4 thousand tokens.
Model training fee = 374.4 × 0.3 = $112.32.

wan2.5-i2v-preview cost estimation (multiple data)

Suppose you fine-tune the wan2.5 model. The training set contains two videos: 3.4 seconds and 11.5 seconds. The parameters are max_pixels = 36864 and n_epochs = 400. The unit training price is $0.05 per 1,000 tokens.

Duration calculation:
- Video 1: 3.4 seconds is rounded to 3. Billable duration: min(10, 3) = 3 seconds.
- Video 2: 11.5 seconds is rounded to 11. Billable duration: min(10, 11) = 10 seconds.
- Total billable duration: 3 + 10 = 13 seconds.
Total training tokens = 13 × (36864 / 1024) × 400 = 187,200 = 187.2 thousand tokens.
Model training fee = 187.2 × 0.05 = $9.36.

Deployment billing

Text generation models: Qwen

Time-based billing (Provisioned Throughput)

Cost = Usage Duration × (Input TPM Unit Price × Input TPM + Output TPM Unit Price × Output TPM)

For the pay-as-you-go method, usage is billed hourly, and the unit price is based on the hourly rates in the table below. For the subscription method, usage is billed daily, and the unit price is based on the daily rates in the table below.

Subscription orders take effect immediately after payment. An N-day subscription is valid until 23:59 on the Nth day. If an order is placed after 22:00, the expiration date is automatically extended by one day.
After a subscription order expires, the service is stopped after a 2-hour grace period. After the service is stopped, the resources are retained for 14 hours and then released.
Subscription orders cannot be terminated early.
For the pay-as-you-go method, if your account has an overdue payment, the deployed resources are retained and continue to be billed for 24 hours, during which the service remains available. After 24 hours, the system stops billing, and the model deployment enters an overdue state. The underlying resources are deleted, but the model deployment task is retained. After you pay the overdue amount, the system reallocates resources, restores the service, and resumes billing. To stop incurring charges, you must delete the model deployment task. Billing stops after the task is successfully deleted.

If the model input exceeds the maximum input tokens or the purchased TPM, the call automatically switches to the pay-as-you-go mode for the current model. In this case, inference performance may decrease and will be subject to the public traffic control of the current snapshot model in the workspace. Costs are charged based on the model invocation (pay-as-you-go) standard.

In this case, the API call returns a header that contains x-dashscope-ptu-overflow:true.
To view TPM statistics, go to Model Monitoring.

For the specific refund rules for scale-in scenarios (downgrades), see Refund rules for downgrades.

Singapore

Qwen

Model name	Model code	Max input tokens	Pay-as-you-go input Per 10k TPM/hour	Pay-as-you-go output Per 1k TPM/hour	Subscription input Per 10k TPM/day	Subscription output Per 1k TPM/day
Qwen3.7-Max-2026-05-20	qwen3.7-max-2026-05-20	256K	$6	$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

DeepSeek

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

Qwen-VL

Model name

Model code

Max input tokens

Pay-as-you-go input

Per 10k TPM/hour

Pay-as-you-go 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

$0.48

$0.384

$5.76

$4.608

More models

Model name

Model code

Max input tokens

Pay-as-you-go input

Per 10k TPM/hour

Pay-as-you-go output

Per 1k TPM/hour

Subscription input

Per 10k TPM/day

Subscription output

Per 1k TPM/day

GLM-5.1

glm-5.1

64K

$5.04

$1.584

$64.8

$19.008

China (Beijing)

Qwen

Model name	Model code	Max input tokens	Pay-as-you-go input Per 10k TPM/hour	Pay-as-you-go output Per 1k TPM/hour	Subscription input Per 10k TPM/day	Subscription output Per 1k TPM/day
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	$0.397	$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 mode: $0.07 Thinking mode: $0.28	$3.36	Non-thinking mode: $0.84 Thinking mode: $3.36

DeepSeek

Model name	Model code	Max input tokens	Pay-as-you-go input Per 10k TPM/hour	Pay-as-you-go 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

Qwen-VL

Model name

Model code

Max input tokens

Pay-as-you-go input

Per 10k TPM/hour

Pay-as-you-go 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

More models

Model name

Model code

Max input tokens

Pay-as-you-go input

Per 10k TPM/hour

Pay-as-you-go output

Per 1k TPM/hour

Subscription input

Per 10k TPM/day

Subscription output

Per 1k TPM/day

GLM-5.1

glm-5.1

64K

$2.97

$1.19

$35.65

$14.26

Time-based billing (Model Unit)

Cost = Usage Duration (hours) × Number of Model Units × Model Unit Price

For the pay-as-you-go method, the "Model Unit Price" is the "Hourly Price" from the table below. For the monthly subscription method, the formula is: Number of Months × Number of Model Units × Monthly Price.

For subscriptions, if you unsubscribe within the first month, the daily unit price (≈ monthly unit price / 30) is charged at 1.2 times the standard rate. Usage for less than a day is billed as a full day.

Note

For the Model Unit pay-as-you-go method, computing power resources are allocated on a first-come, first-served basis. A full refund is issued if the purchase is unsuccessful.

Singapore

Text generation

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

Qwen3.5-39B-A17B	qwen3.5-397b-a17b	MU2 x 8	$112	$52,392
Qwen3.5-35B-A3B	qwen3.5-35b-a3b	MU2 x 8	$112	$52,392

Qwen3-32B	qwen3-32b	MU1 x 4	$44	$20,916
Qwen3-32B	qwen3-32b	MU2 x 8	$112	$52,392
Qwen3-14B	qwen3-14b	MU1 x 4	$44	$20,916

GLM-5.1	glm-5.1	MU2 x 8	$112	$52,392

DeepSeek-V4-Flash	deepseek-v4-flash	MU1 x 8	$88	$41,832

Multimodal

Model name

Model code

Model unit specification

Hourly price ($)

Minimum billing unit: minute

Monthly price ($)

Minimum billing unit: day

Qwen3-VL-32B-Instruct

qwen3-vl-32b-instruct

MU2 x 8

$112

$52,392

Qwen3-VL-8B-Instruct

qwen3-vl-8b-instruct

MU1 x 2

$22

$10,458

Model types:

Instruct - The deployed model performs inference in non-thinking mode.

China (Beijing)

Text generation

Qwen

Model name	Model code	Model unit specification	Hourly price ($) Minimum billing unit: minute	Monthly price ($) Minimum billing unit: day
Qwen3.7-Plus-2026-05-26	qwen3.7-plus-2026-05-26	MU3 x 8	$150.72	$72,577.152

Qwen3.6-35B-A3B	qwen3.6-35b-a3b	MU8 x 1	$6.464	$3,080.477
Qwen3.6-35B-A3B	qwen3.6-35b-a3b	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-Plus-2026-04-02	qwen3.6-plus-2026-04-02	MU1 x 8	$59.408	$28,734.256

Qwen3.5-397B-A17B	qwen3.5-397b-a17b	MU2 x 8	$69.312	$33,044.72
		MU3 x 8	$150.72	$72,577.152
		MU6 x 16	$55.008	$26,599.92
Qwen3.5-122B-A10B	qwen3.5-122b-a10b	MU1 x 4	$29.704	$14,367.128
		MU2 x 8	$69.312	$33,044.72
		MU6 x 16	$55.008	$26,599.92
		MU9 x 2	$14.028	$6,766.048
Qwen3.5-35B-A3B	qwen3.5-35b-a3b	MU1 x 2	$14.852	$7,183.564
		MU2 x 8	$69.312	$33,044.72
		MU8 x 1	$6.464	$3,080.477
		MU9 x 1	$7.014	$3,383.024
Qwen3.5-27B	qwen3.5-27b	MU9 x 1	$7.014	$3,383.024
Qwen3.5-9B	qwen3.5-9b	MU8 x 1	$6.464	$3,080.477
Qwen3.5-9B	qwen3.5-9b	MU9 x 1	$7.014	$3,383.024
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	$59.408	$28,734.256
Qwen3.5-Plus-2026-02-15	qwen3.5-plus-2026-02-15	MU3 x 8	$150.72	$72,577.152

Qwen3-235B-A22B-Instruct	qwen3-235b-a22b-instruct-2507	MU1 x 4	$29.704	$14,367.128
Qwen3-235B-A22B-Instruct	qwen3-235b-a22b-instruct-2507	MU2 x 8	$69.312	$33,044.72
Qwen3-Next-80B-A3B-Instruct	qwen3-next-80b-a3b-instruct	MU1 x 2	$14.852	$7,183.564
Qwen3-32B	qwen3-32b	MU1 x 4	$29.704	$14,367.128
Qwen3-32B	qwen3-32b	MU6 x 4	$13.752	$6,649.98
Qwen3-30B-A3B	qwen3-30b-a3b	MU9 x 2	$14.028	$6,766.048
Qwen3-30B-A3B-Instruct-2507	qwen3-30b-a3b-instruct-2507	MU1 x 4	$29.704	$14,367.128
Qwen3-30B-A3B-Instruct-2507	qwen3-30b-a3b-instruct-2507	MU2 x 8	$69.312	$33,044.72
Qwen3-8B	qwen3-8b	MU1 x 2	$14.852	$7,183.564
		MU2 x 2	$17.328	$8,261.18
		MU5 x 1	$2.888	$1,394.329
Qwen3-4B	qwen3-4b	MU1 x 2	$14.852	$7,183.564
Qwen3-4B	qwen3-4b	MU5 x 1	$2.888	$1,394.329
Qwen3-1.7B	qwen3-1.7b	MU1 x 2	$14.852	$7,183.564
Qwen3-1.7B	qwen3-1.7b	MU5 x 1	$2.888	$1,394.329
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

Qwen2.5-72B	qwen2.5-72b-instruct	MU1 x 4	$29.704	$14,367.128
Qwen2.5-32B	qwen2.5-32b-instruct	MU1 x 4	$29.704	$14,367.128
Qwen2.5-14B	qwen2.5-14b-instruct	MU1 x 2	$14.852	$7,183.564
Qwen2.5-7B	qwen2.5-7b-instruct	MU1 x 2	$14.852	$7,183.564
Qwen2.5-7B	qwen2.5-7b-instruct	MU5 x 1	$2.888	$1,394.329
Qwen2.5-3B-Instruct	qwen2.5-3b-instruct	MU5 x 1	$2.888	$1,394.329

Qwen-Flash-2025-07-28	qwen-flash-2025-07-28	MU1 x 4	$29.704	$14,367.128
Qwen-Plus-2025-07-28	qwen-plus-2025-07-28	MU1 x 4	$29.704	$14,367.128
Qwen-Plus-2025-12-01	qwen-plus-2025-12-01	MU1 x 4	$29.704	$14,367.128

GLM

Model name	Model code	Model unit specification	Hourly price ($) Minimum billing unit: minute	Monthly price ($) Minimum billing unit: day
GLM-5.1	glm-5.1	MU2 x 8	$69.312	$33,044.72
		MU3 x 8	$150.72	$72,577.152
		MU6 x 16	$55.008	$26,599.92
GLM-5	glm-5	MU3 x 8	$150.72	$72,577.152
GLM-4.7	glm-4.7	MU6 x 16	$55.008	$26,599.92

DeepSeek

Model name

Model code

Model unit specification

Hourly price ($)

Minimum billing unit: minute

Monthly price ($)

Minimum billing unit: day

DeepSeek-V4-Flash

deepseek-v4-flash

MU1 x 8

$59.408

$28,734.256

DeepSeek-V3.2

deepseek-v3.2

MU2 x 8

$69.312

$33,044.72

Other models

Model name	Model code	Model unit specification	Hourly price ($) Minimum billing unit: minute	Monthly price ($) Minimum billing unit: day
MiniMax-M2.5	MiniMax-M2.5	MU1 x 8	$59.408	$28,734.256

Kimi-K2.5	kimi-k2.5	MU2 x 8	$69.312	$33,044.72

Multimodal

Qwen-VL

Model name	Model code	Model unit specification	Hourly price ($) Minimum billing unit: minute	Monthly price ($) Minimum billing unit: day
Qwen3-VL-235B-A22B-Instruct	qwen3-vl-235b-a22b-instruct	MU1 x 4	$29.704	$14,367.128
Qwen3-VL-235B-A22B-Thinking	qwen3-vl-235b-a22b-thinking	MU1 x 4	$29.704	$14,367.128
Qwen3-VL-32B-Instruct	qwen3-vl-32b-instruct	MU2 x 8	$69.312	$33,044.72
Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	MU1 x 2	$14.852	$7,183.564
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-VL-OCR-2025-11-20	qwen-vl-ocr-2025-11-20	MU6 x 4	$13.752	$6,649.98

Qwen Omni

Model name	Model code	Model unit specification	Hourly price ($) Minimum billing unit: minute	Monthly price ($) Minimum billing unit: day
Qwen3.5-Omni-Flash	qwen3.5-omni-flash	MU8 x 1	$6.464	$3,080.477
Qwen3.5-Omni-Flash	qwen3.5-omni-flash	MU9 x 1	$7.014	$3,383.024
Qwen3.5-Omni-Plus	qwen3.5-omni-plus	MU9 x 8	$56.112	$27,064.192

Model types:

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

By model token usage

Cost = Number of Input Tokens × Input Unit Price + Number of Output Tokens × Output Unit Price (Minimum billing unit: 1 token)

Billing by model token usage is only supported after you have completed Supervised Fine-Tuning (SFT) for the following foundation models and you have obtained a custom model.

Singapore

Foundation model

Model code

Input

$/1k tokens

Output

$/1k tokens

Qwen3-14B

qwen3-14b

$0.00035

Non-thinking mode: $0.0014

Thinking mode: $0.0042

Image generation models – Wan

Deployment is free. Invocations are billed at the standard rate of the fine-tuned base model. For the training workflow, see Fine-tune image generation models.

Model ID	LoRA Deployment & Invocation Price
wan2.7-image-pro	$0.075/image
wan2.7-image	$0.03/image

FAQ

Q: When does billing for model deployment start?

A: Billing starts when the model status changes to Running. No charges apply during Deploying, Overdue Payment, or Deployment Failed.

Q: Am I charged if I cancel a training job?

A: Yes. If you cancel training manually, you are charged for all tokens processed before cancellation. Training jobs interrupted by system errors or other non-user causes are not charged.

Q: How do I view invocation statistics for a deployed model?

A: Visit the Model Monitoring (Singapore), Model Monitoring (Virginia), or Model Monitoring (Beijing) page.