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

This topic describes the billing rules and pricing for model training and model deployment on Alibaba Cloud Model Studio.

Training billing

Text generation models – Qwen

NoteFor 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

Model service	Model code	Price
Qwen3.8-27B	qwen3.8-27b	¥0.05/1K tokens

Qwen3.7-Plus-2026-05-26	qwen3.7-plus-2026-05-26	¥0.35/1K tokens

Qwen3.6-Flash-2026-04-16	qwen3.6-flash-2026-04-16	¥0.05/1K tokens
Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	¥0.3/1K tokens

Qwen3.5-27B	qwen3.5-27b	¥0.05/1K tokens
Qwen3.5-9B	qwen3.5-9b	¥0.02/1K tokens
Qwen3.5-4B	qwen3.5-4b	¥0.015/1K tokens
Qwen3.5-Flash-2026-02-23	qwen3.5-flash-2026-02-23	¥0.05/1K tokens
Qwen3.5-Plus-2026-02-15	qwen3.5-plus-2026-02-15	¥0.3/1K tokens

Qwen3-32B	qwen3-32b	¥0.04/1K tokens
Qwen3-30B-A3B-Instruct-2507	qwen3-30b-a3b-instruct-2507	¥0.03/1K tokens
Qwen3-14B	qwen3-14b	¥0.03/1K tokens
Qwen3-8B	qwen3-8b	¥0.006/1K tokens
Qwen3-4B-Instruct-2507	qwen3-4b-instruct-2507	¥0.006/1K tokens
Qwen3-1.7B	qwen3-1.7b	¥0.0045/1K tokens
Qwen3-0.6B	qwen3-0.6b	¥0.003/1K tokens

Qwen2.5-72B-Instruct	qwen2.5-72b-instruct	¥0.15/1K tokens
Qwen2.5-32B-Instruct	qwen2.5-32b-instruct	¥0.03/1K tokens
Qwen2.5-14B-Instruct	qwen2.5-14b-instruct	¥0.03/1K tokens
Qwen2.5-7B-Instruct	qwen2.5-7b-instruct	¥0.006/1K tokens

Qwen-Plus-Character-2025-11-06	qwen-plus-character-2025-11-06	¥0.15/1K tokens

Qwen-VL

Model service	Model code	Price
Qwen3-VL-8B-Instruct	qwen3-vl-8b-instruct	¥0.012/1K tokens
Qwen3-VL-8B-Thinking	qwen3-vl-8b-thinking	¥0.012/1K tokens
Qwen3-VL-4B-Instruct	qwen3-vl-4b-instruct	¥0.006/1K tokens

Qwen2.5-VL-72B-Instruct	qwen2.5-vl-72b-instruct	¥0.05/1K tokens
Qwen2.5-VL-32B-Instruct	qwen2.5-vl-32b-instruct	¥0.02/1K tokens
Qwen2.5-VL-7B-Instruct	qwen2.5-vl-7b-instruct	¥0.01/1K tokens

Image generation models – Wan

NoteFor 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

Training Tokens Total ≈ max_steps × L_step

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_step = ∑_i∈batch L_item(i) ≤ L_max

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

NoteThe 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

Image generation models – Qwen

NoteFor 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

Total training tokens = n_epochs × N × (max_pixels / Compression ratio) × GPU coefficient

Where:

n_epochs: A hyperparameter specified during training, representing the number of training epochs (configured when creating a fine-tuning job).
N: The total number of images in the training set.
max_pixels: A hyperparameter specified during training, representing the maximum number of pixels per image (configured when creating a fine-tuning job). Valid values are 1k (1024×1024) and 2k (2048×2048).
Compression ratio: The fixed VAE compression ratio, which is 1024 (32×32).
GPU coefficient: A resource scheduling coefficient that is dynamically adjusted based on job scheduling.

Model	Code	Training price (per 1K tokens)
Qwen image generation	qwen-image-2.0	$0.003

Billing example

Suppose you fine-tune the qwen-image-2.0 model with a training set of 1 image. The parameters are: n_epochs = 1000, max_pixels = "1k", the training price is $0.003 per 1,000 tokens, and the GPU coefficient is 8:

Tokens per image = max_pixels / Compression ratio = 1024×1024 / 1024 = 1024
Total training tokens = 1000 × 1 × 1024 × 8 = 8192000 = 8192 thousand tokens
Model training fee = 8192 × 0.003 = $24.576

The following table estimates token consumption and fees per training image, assuming a GPU coefficient of 8. For a training set of N images, multiply the values by N.

max_pixels	n_epochs	Estimated tokens	Estimated fee (USD)
1k	800	6,553,600	19.66
1k	1,000	8,192,000	24.58
1k	2,000	16,384,000	49.15
2k	800	26,214,400	78.64
2k	1,000	32,768,000	98.30
2k	2,000	65,536,000	196.61

Note

The GPU coefficient is dynamically adjusted based on job scheduling. The value 8 in the example and the table above is used only to illustrate the calculation. For actual token consumption, see the usage field returned by the Query a fine-tuning job operation. Your bill is the final authority on fees.
batch_size does not affect billing or the total training tokens.

Video generation models – Wan

NoteFor 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

Training Tokens Total = (∑_i=1^N billing duration of video_i) × (max_pixels / 1024) × n_epochs

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)	wan2.7-i2v	$0.3
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

Usage duration billing (Provisioned Throughput)

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 support early termination; the used portion is settled at a 1.2x coefficient for refund. For details, see Refund rules for configuration downgrades.
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.

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

Singapore

Qwen

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-Flash-2026-07-15 Contact your account manager to enable	qwen3.7-flash-2026-07-15	128K	$0.072	$0.031	$0.864	$0.374
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

DeepSeek

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-Flash-0731	deepseek-v4-flash-0731	64K	$1.44	$0.288	$17.28	$3.456
DeepSeek-v4-Pro	deepseek-v4-pro	256K	$0.96	$1.728	$103.68	$20.736

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-Flash-0731

deepseek-v4-flash-0731

64K

$1.44

$0.288

$17.28

$3.456

DeepSeek-v4-Pro

deepseek-v4-pro

256K

$0.96

$1.728

$103.68

$20.736

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-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

GLM

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

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

North China 2 (Beijing)

Qwen

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	$3.96	$1.188	$47.53	$14.258

Qwen3.7-Flash-2026-07-15 Contact your account manager to enable	qwen3.7-flash-2026-07-15	128K	$0.066	$0.026	$0.792	$0.317
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

DeepSeek

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	$0.5	$0.099	$5.94	$1.188
DeepSeek-v4-Flash-0731	deepseek-v4-flash-0731	64K	$0.99	$0.198	$11.88	$2.376
DeepSeek-v4-Pro	deepseek-v4-pro	256K	$5.94	$1.188	$71.3	$14.26
DeepSeek-v3	deepseek-v3	64K	$0.99	$0.396	$11.9	$4.75

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-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

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

$0.35

$4.2

GLM

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	$3.96	$1.386	$47.53	$16.635

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

$3.96

$1.386

$47.53

$16.635

Usage duration billing (Dedicated Throughput)

Prepaid orders support early termination; the used portion is settled at a 1.2x coefficient for refund. For details, see Refund rules for configuration downgrades.

Singapore

Model	Baseline input (TPM)	Baseline output (TPM)	Input unit price (USD/kTPM·month)	Output unit price (USD/kTPM·month)	Monthly total price (USD)
qwen3.7-plus-2026-05-26	1,192,000	148,000	37	295	87,764
	1,372,000	170,000	32	257	87,594
	660,000	124,000	66	352	87,208
	704,000	132,000	62	331	87,340

Model	Input length	Output length	First token latency (ms)	Per-token latency (ms)
qwen3.7-plus-2026-05-26	16,000	2,000	888	10
	16,000	2,000	2,418	15
	2,600	500	819	14
	2,600	500	970	13

By model Token usage

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

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

Beijing

Base model	Model code	Input $/million tokens	Output $/million tokens
Qwen3.8-27B	qwen3.8-27b	$0.424	$1.696

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

Billing by usage duration (model unit)

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)

NoteCompute 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

Text generation

Model name	Model code	Model unit spec	Hourly unit price ($) Minimum billing: minute	Monthly unit price ($) Minimum billing: day
Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	MU1 x 8	$88	$41,832
Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	MU2 x 8	$112	$52,392

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

Multimodal

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

Model name

Model code

Model unit spec

Hourly unit price ($)

Minimum billing: minute

Monthly unit price ($)

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.

North China 2 (Beijing)

Text generation

Qwen

Model name	Model code	Model unit spec	Hourly unit price ($) Minimum billing: minute	Monthly unit price ($) Minimum billing: day
Qwen3.8-27B	qwen3.8-27b	MU9 x 4	$28.056	$13,532.096

Qwen3.7-Plus-2026-05-26	qwen3.7-plus-2026-05-26	MU2 x 8	$69.312	$33,044.72
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	MU1 x 8	$59.408	$28,734.256
		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
Qwen3.6-27B	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
Qwen3.6-Plus-2026-04-02	qwen3.6-plus-2026-04-02	MU2 x 8	$69.312	$33,044.72

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	MU1 x 2	$14.852	$7,183.564
Qwen3.5-9B	qwen3.5-9b	MU2 x 8	$69.312	$33,044.72
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
Qwen3-4B	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	$29.704	$14,367.128
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 spec	Hourly unit price ($) Minimum billing: minute	Monthly unit price ($) 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 spec	Hourly unit price ($) Minimum billing: minute	Monthly unit price ($) 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 spec

Hourly unit price ($)

Minimum billing: minute

Monthly unit price ($)

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

Other models

Model name	Model code	Model unit spec	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

Model name

Model code

Model unit spec

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

Multimodal

Qwen-VL

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

Model name

Model code

Model unit spec

Hourly unit price ($)

Minimum billing: minute

Monthly unit price ($)

Minimum billing: day

Qwen3.5-Omni-Flash

qwen3.5-omni-flash

MU8 x 1

$6.464

$3,080.477

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.

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

Image generation models – Qwen

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

Model ID	LoRA Deployment & Invocation Price
qwen-image-2.0	$0.035/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.