AI inference fees - MaxCompute - Alibaba Cloud Documentation Center

The MaxCompute AI inference is a new, out-of-the-box, pay-as-you-go feature that lets you use large models for data processing or offline inference. This topic describes the billing rules for the AI inference.

Overview

The MaxCompute AI inference service provides large model inference, letting you call out-of-the-box models directly from SQL and MaxFrame jobs using a built-in AI function. You are billed on a pay-as-you-go basis according to the total number of input and output tokens.

Supported regions: The model inference service is available only in the following regions.
- Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), and China (Ulanqab)
- International: Singapore

Supported models: To use the following models, you must first enable the model inference service in the target region, such as China (Beijing).

Model	Type	Description
`qwen3.8-max`	Supports multimodal data input	A flagship Mixture of Experts (MoE) model from the Qwen 3.8 series with 2.4 trillion parameters. It features significantly enhanced programming and office productivity capabilities, and can autonomously program for over ten days to deliver complete projects. This model is ideal for highly complex scenarios such as autonomous programming, advanced office automation, scientific research, and long-duration tasks.
`qwen3.7-max`	Text input only	A flagship model from the Qwen 3.7 series, featuring comprehensive upgrades in inference, code generation, and multilingual understanding. It is suitable for highly complex tasks.
`qwen3.7-plus`	Supports multimodal data input	A balanced model from the Qwen 3.7 series that offers a good trade-off between performance and cost. It is suitable for enterprise scenarios such as long-text analysis and multi-turn conversations.
`qwen3.7-flash`	Supports multimodal data input	A lightweight, high-speed, native vision-language model from the Qwen 3.7 series. It features enhanced multimodal understanding and agent execution capabilities, making it ideal for high-concurrency, low-latency online services and lightweight multimodal tasks.
`qwen3.7-text-embedding`	Text input only	This unified multilingual text vector model, trained on Qwen 3.7, offers significant performance improvements in text retrieval, clustering, and classification compared to the text-embedding-v4 version.
`qwen3-vl-embedding`	Supports multimodal data input	A Qwen multimodal vector embedding model that supports vector representations for mixed image and text inputs. It is suitable for cross-modal retrieval and image-text matching scenarios.
`text-embedding-v4`	Text input only	A high-precision text vector embedding model suitable for semantic search, clustering, and similarity calculation.
`qwen3.6-plus`	Supports multimodal data input	A balanced model from the Qwen 3.6 series that offers a good trade-off between performance and cost. It is suitable for general business scenarios such as dialogue, summarization, and analysis.
`qwen3.6-flash`	Supports multimodal data input	A lightweight, high-speed model from the Qwen 3.6 series. It provides fast responses at a low cost, making it ideal for high-concurrency, low-latency online services.
`deepseek-v4-pro`	Text input only	The fourth-generation flagship inference model from DeepSeek. It excels at high-difficulty tasks such as mathematics, coding, and complex logical reasoning.
`deepseek-v4-flash`	Text input only	The fourth-generation lightweight model from DeepSeek. It offers fast inference and is highly cost-effective, making it suitable for daily conversations and lightweight inference tasks.
`qwen3.5-397b-a17b`	Supports multimodal data input	A Mixture of Experts (MoE) model from the Qwen 3.5 series. It features efficient parameter activation, a vast knowledge base, and multi-step reasoning capabilities. This model is designed for high-difficulty logical deduction, full-stack code generation, and in-depth knowledge Q&A.
`qwen3.5-omni-plus`	Supports multimodal data input	Qwen3.5-Omni is Qwen's latest omni-modal large model. It is suitable for scenarios such as text creation, voice assistants, and multimedia analysis, providing a natural and smooth multimodal understanding and interaction experience.
`qwen3-asr-flash`	Supports multimodal data input	A lightweight speech recognition model from the Qwen 3 series. It provides real-time transcription with low latency and high concurrency, making it suitable for real-time audio processing scenarios such as generating meeting minutes, live-streaming subtitles, and recognizing voice commands.
`tongyi-embedding-vision-plus`	Supports multimodal data input	Tongyi-Embedding-Vision is a visual multimodal representation model built on a large language model (LLM). It is suitable for a variety of downstream tasks, including image-to-image search, text-to-image search, text-to-video search, video-to-video search, text-to-text search, and text-to-image-and-text search.
`qwen3-max` (Sunsetting soon)	Text input only	A high-performance large language model from the Qwen series, suitable for complex inference and content generation. Important The `qwen3-max` model is sunsetting soon. To ensure service continuity, migrate your related services to a new model as soon as possible. For more information, see Model Decommissioning Policy.

Note

You incur model inference service fees only when you use the public models listed above in MaxFrame Overview and SQL jobs using an AI function. You are charged only for successful jobs; failed jobs do not incur fees.

Billing rules

The model inference service is billed based on token usage. The billing dimensions include:

Region
Model type
Token type: Distinguishes between input and output tokens and indicates the usage-based pricing tier.

Pricing

A single SQL or MaxFrame job can involve multiple model invocations. For models with pricing tiers, the system calculates the input token count for each model invocation separately to determine the pricing tier (token type). The system then meters and bills usage for each token type separately.

Important

When deploying services in China regions, model inference compute resources are restricted to the Chinese mainland, and static data is stored in the selected region.
When deploying services in international regions, model inference compute resources are dynamically scheduled globally (excluding the Chinese mainland), and static data is stored in the selected region.

qwen3.7-max

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Input tokens	Usage scenario	Type	Unit price (per 1 million tokens)
0 < tokens ≤ 1,048,576	Model input	`input_token_tier1`	USD 1.98
	Model input (implicit cache hit)	`input_token_tier1_cached`	USD 0.396
	Model input (explicit cache hit)	`input_token_tier1_cached_explicit`	USD 0.198
	Model input (create explicit cache)	`input_token_tier1_create_cache`	USD 2.475
	Model output (non-thinking)	`output_token_tier1`	USD 5.9412
	Model output (thinking mode)	`output_token_tier1_thinking`	USD 5.9412

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported regions: Singapore

Input tokens	Usage scenario	Type	Unit price (per 1 million tokens)
0 < tokens ≤ 1,048,576	Model input	`input_token_tier1`	USD 3
	Model input (implicit cache hit)	`input_token_tier1_cached`	USD 0.6
	Model input (explicit cache hit)	`input_token_tier1_cached_explicit`	USD 0.3
	Model input (create explicit cache)	`input_token_tier1_create_cache`	USD 3.75
	Model output (non-thinking)	`output_token_tier1`	USD 9
	Model output (thinking mode)	`output_token_tier1_thinking`	USD 9

qwen3.7-plus

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Input tokens	Usage scenario	Token type	Price (per 1 million tokens)
0 < tokens ≤ 262,144	model input	`input_token_tier1`	USD 0.3312
	model input (implicit cache hit)	`input_token_tier1_cached`	USD 0.06624
	model input (explicit cache hit)	`input_token_tier1_cached_explicit`	USD 0.03312
	model input (create explicit cache)	`input_token_tier1_create_cache`	USD 0.414
	model output (non-thinking)	`output_token_tier1`	USD 1.3212
	model output (thinking mode)	`output_token_tier1_thinking`	USD 1.3212
262,144 < tokens ≤ 1,048,576	model input	`input_token_tier2`	USD 0.9912
	model input (implicit cache hit)	`input_token_tier2_cached`	USD 0.19824
	model input (explicit cache hit)	`input_token_tier2_cached_explicit`	USD 0.09912
	model input (create explicit cache)	`input_token_tier2_create_cache`	USD 1.239
	model output (non-thinking)	`output_token_tier2`	USD 3.9612
	model output (thinking mode)	`output_token_tier2_thinking`	USD 3.9612

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported regions: Singapore

Input tokens	Usage scenario	Token type	Price (per 1 million tokens)
0 < tokens ≤ 262,144	model input	`input_token_tier1`	USD 0.48
	model input (implicit cache hit)	`input_token_tier1_cached`	USD 0.096
	model input (explicit cache hit)	`input_token_tier1_cached_explicit`	USD 0.048
	model input (create explicit cache)	`input_token_tier1_create_cache`	USD 0.6
	model output (non-thinking)	`output_token_tier1`	USD 1.92
	model output (thinking mode)	`output_token_tier1_thinking`	USD 1.92
262,144 < tokens ≤ 1,048,576	model input	`input_token_tier2`	USD 1.44
	model input (implicit cache hit)	`input_token_tier2_cached`	USD 0.288
	model input (explicit cache hit)	`input_token_tier2_cached_explicit`	USD 0.144
	model input (create explicit cache)	`input_token_tier2_create_cache`	USD 1.8
	model output (non-thinking)	`output_token_tier2`	USD 5.76
	model output (thinking mode)	`output_token_tier2_thinking`	USD 5.76

qwen3-vl-embedding

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Tier	Use case	Token type	Unit price
Text	Model input	`input_token_tier1_text`	0.12 USD
Image & video	Model input	`input_token_tier1_image`	0.3096 USD

text-embedding-v4

The text-embedding-v4 model is billed for model input tokens only. There are no fees for model output and no tiers. All usage is billed as input_token_tier1.

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Tier	Use case	Token type	Unit price (per million tokens)
No tiers	model input	`input_token_tier1`	0.0864 USD

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported regions: Singapore

Tier	Use case	Token type	Unit price (per million tokens)
No tiers	model input	`input_token_tier1`	0.084 USD

qwen3.6-plus

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Input token count	Usage scenario	Token type	Price
0 < tokens ≤ 262,144	Model input	`input_token_tier1`	0.3312 USD
	Model input (implicit cache hit)	`input_token_tier1_cached`	0.06624 USD
	Model input (explicit cache hit)	`input_token_tier1_cached_explicit`	0.03312 USD
	Model input (create explicit cache)	`input_token_tier1_create_cache`	0.414 USD
	Model output (non-thinking)	`output_token_tier1`	1.9812 USD
	Model output (thinking mode)	`output_token_tier1_thinking`	1.9812 USD
262,144 < tokens ≤ 1,048,576	Model input	`input_token_tier2`	1.3212 USD
	Model input (implicit cache hit)	`input_token_tier2_cached`	0.26424 USD
	Model input (explicit cache hit)	`input_token_tier2_cached_explicit`	0.13212 USD
	Model input (create explicit cache)	`input_token_tier2_create_cache`	1.6515 USD
	Model output (non-thinking)	`output_token_tier2`	7.9224 USD
	Model output (thinking mode)	`output_token_tier2_thinking`	7.9224 USD

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported regions: Singapore

Input token count	Usage scenario	Token type	Price
0 < tokens ≤ 262,144	Model input	`input_token_tier1`	0.6 USD
	Model input (implicit cache hit)	`input_token_tier1_cached`	0.12 USD
	Model input (explicit cache hit)	`input_token_tier1_cached_explicit`	0.06 USD
	Model input (create explicit cache)	`input_token_tier1_create_cache`	0.75 USD
	Model output (non-thinking)	`output_token_tier1`	3.6 USD
	Model output (thinking mode)	`output_token_tier1_thinking`	3.6 USD
262,144 < tokens ≤ 1,048,576	Model input	`input_token_tier2`	2.4 USD
	Model input (implicit cache hit)	`input_token_tier2_cached`	0.48 USD
	Model input (explicit cache hit)	`input_token_tier2_cached_explicit`	0.24 USD
	Model input (create explicit cache)	`input_token_tier2_create_cache`	3 USD
	Model output (non-thinking)	`output_token_tier2`	7.2 USD
	Model output (thinking mode)	`output_token_tier2_thinking`	7.2 USD

qwen3.6-flash

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Tokens per inference	Scenario	Type	Price
0 < tokens ≤ 262,144	Model input	`input_token_tier1`	USD 0.198
	Model input (Implicit cache hit)	`input_token_tier1_cached`	USD 0.0396
	Model input (Explicit cache hit)	`input_token_tier1_cached_explicit`	USD 0.0198
	Model input (Create explicit cache)	`input_token_tier1_create_cache`	USD 0.2475
	Model output (Non-thinking)	`output_token_tier1`	USD 1.188
	Model output (Thinking mode)	`output_token_tier1_thinking`	USD 1.188
262,144 < tokens ≤ 1,048,576	Model input	`input_token_tier2`	USD 0.792
	Model input (Implicit cache hit)	`input_token_tier2_cached`	USD 0.1584
	Model input (Explicit cache hit)	`input_token_tier2_cached_explicit`	USD 0.0792
	Model input (Create explicit cache)	`input_token_tier2_create_cache`	USD 0.99
	Model output (Non-thinking)	`output_token_tier2`	USD 4.7532
	Model output (Thinking mode)	`output_token_tier2_thinking`	USD 4.7532

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported region: Singapore

Tokens per inference	Scenario	Type	Price
0 < tokens ≤ 262,144	Model input	`input_token_tier1`	USD 0.3
	Model input (Implicit cache hit)	`input_token_tier1_cached`	USD 0.06
	Model input (Explicit cache hit)	`input_token_tier1_cached_explicit`	USD 0.03
	Model input (Create explicit cache)	`input_token_tier1_create_cache`	USD 0.375
	Model output (Non-thinking)	`output_token_tier1`	USD 1.8
	Model output (Thinking mode)	`output_token_tier1_thinking`	USD 1.8
262,144 < tokens ≤ 1,048,576	Model input	`input_token_tier2`	USD 1.2
	Model input (Implicit cache hit)	`input_token_tier2_cached`	USD 0.24
	Model input (Explicit cache hit)	`input_token_tier2_cached_explicit`	USD 0.12
	Model input (Create explicit cache)	`input_token_tier2_create_cache`	USD 1.5
	Model output (Non-thinking)	`output_token_tier2`	USD 4.8
	Model output (Thinking mode)	`output_token_tier2_thinking`	USD 4.8

deepseek-v4-pro

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Tier	Usage scenario	Token type	Price (per million tokens)
No tiers	model input	`input_token_tier1`	1.98 USD
	model input (hit implicit cache)	`input_token_tier1_cached`	0.396 USD
	model input (hit explicit cache)	`input_token_tier1_cached_explicit`	0.198 USD
	model input (create explicit cache)	`input_token_tier1_create_cache`	2.475 USD
	model output (non-thinking)	`output_token_tier1`	3.9612 USD
	model output (thinking mode)	`output_token_tier1_thinking`	3.9612 USD

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported region: Singapore

Input tokens	Usage scenario	Token type	Price (per million tokens)
0 < Tokens ≤ 1,048,576	model input	`input_token_tier1`	2.88 USD
	model input (hit implicit cache)	`input_token_tier1_cached`	0.576 USD
	model input (hit explicit cache)	`input_token_tier1_cached_explicit`	0.288 USD
	model input (create explicit cache)	`input_token_tier1_create_cache`	3.6 USD
	model output (non-thinking)	`output_token_tier1`	5.76 USD
	model output (thinking mode)	`output_token_tier1_thinking`	5.76 USD

deepseek-v4-flash

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Pricing tier	Scenario	Token type	Unit price (per million tokens)
No tiers	model input	`input_token_tier1`	0.1656 USD
	model input (implicit cache hit) (implicit cache hit)	`input_token_tier1_cached`	0.03312 USD
	model input (explicit cache hit) (Explicit cache hit)	`input_token_tier1_cached_explicit`	0.01656 USD
	model input (explicit cache creation) (explicit cache creation)	`input_token_tier1_create_cache`	0.207 USD
	model output (non-thinking)	`output_token_tier1`	0.33 USD
	model output (thinking mode)	`output_token_tier1_thinking`	0.33 USD

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported region: Singapore

Pricing tier	Scenario	Token type	Unit price (per million tokens)
0 < tokens ≤ 1,048,576	model input	`input_token_tier1`	0.24 USD
	model input (implicit cache hit) (implicit cache hit)	`input_token_tier1_cached`	0.048 USD
	model input (explicit cache hit) (explicit cache hit)	`input_token_tier1_cached_explicit`	0.024 USD
	model input (explicit cache creation) (Create explicit cache)	`input_token_tier1_create_cache`	0.3 USD
	model output (non-thinking)	`output_token_tier1`	0.48 USD
	model output (thinking mode)	`output_token_tier1_thinking`	0.48 USD

qwen3.5-397b-a17b

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Input tokens	Use case	Token type	Unit price
0 < tokens ≤ 131,072	model input	`input_token_tier1`	0.2064 USD
	model input (implicit cache hit)	`input_token_tier1_cached`	0.04128 USD
	model input (explicit cache hit)	`input_token_tier1_cached_explicit`	0.02064 USD
	model input (create explicit cache)	`input_token_tier1_create_cache`	0.258 USD
	model output (non-thinking)	`output_token_tier1`	1.2384 USD
	model output (thinking mode)	`output_token_tier1_thinking`	1.2384 USD
131,072 < tokens ≤ 262,144	model input	`input_token_tier2`	0.516 USD
	model input (implicit cache hit)	`input_token_tier2_cached`	0.1032 USD
	model input (explicit cache hit)	`input_token_tier2_cached_explicit`	0.0516 USD
	model input (create explicit cache)	`input_token_tier2_create_cache`	0.645 USD
	model output (non-thinking)	`output_token_tier2`	3.096 USD
	model output (thinking mode)	`output_token_tier2_thinking`	3.096 USD

qwen3-asr-flash

qwen3-asr-flash is billed for model input tokens only. There are no charges for model output or pricing tiers. All usage is billed as input_token_tier1.

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Pricing tier	Use case	Token type	Price (per million tokens)
No tiers	model input	`input_token_tier1`	1.536 USD

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported regions: Singapore

Pricing tier	Use case	Token type	Price (per million tokens)
No tiers	model input	`input_token_tier1`	1.68 USD

qwen3-max (sunsetting soon)

Chinese mainland

For deployments in China regions, compute resources for model inference are limited to the Chinese mainland, and static data is stored in the selected region.

Supported regions:

Chinese mainland: China (Beijing), China (Shanghai), China (Hangzhou), China (Shenzhen), China (Ulanqab)

Input tokens per inference	Scenario	Token type	Price (per million tokens)
0 < Token ≤ 32,768	model input	`input_token_tier1`	0.4308 USD
	model input (implicit cache hit)	`input_token_tier1_cached`	0.08616 USD
	model input (explicit cache hit)	`input_token_tier1_cached_explicit`	0.04308 USD
	model input (create explicit cache)	`input_token_tier1_create_cache`	0.5385 USD
	model output (non-thinking)	`output_token_tier1`	1.7208 USD
	model output (thinking mode)	`output_token_tier1_thinking`	1.7208 USD
32,768 < Token ≤ 131,072	model input	`input_token_tier2`	0.6888 USD
	model input (implicit cache hit)	`input_token_tier2_cached`	0.13776 USD
	model input (explicit cache hit)	`input_token_tier2_cached_explicit`	0.06888 USD
	model input (create explicit cache)	`input_token_tier2_create_cache`	0.861 USD
	model output (non-thinking)	`output_token_tier2`	2.7528 USD
	model output (thinking mode)	`output_token_tier2_thinking`	2.7528 USD
131,072 < Token ≤ 258,048	model input	`input_token_tier3`	1.2048 USD
	model input (implicit cache hit)	`input_token_tier3_cached`	0.24096 USD
	model input (explicit cache hit)	`input_token_tier3_cached_explicit`	0.12048 USD
	model input (create explicit cache)	`input_token_tier3_create_cache`	1.506 USD
	model output (non-thinking)	`output_token_tier3`	4.8168 USD
	model output (thinking mode)	`output_token_tier3_thinking`	4.8168 USD

International

For deployments in International regions, compute resources for model inference are dynamically scheduled worldwide (excluding the Chinese mainland), and static data is stored in the selected region.

Supported region: Singapore

Input tokens per inference	Scenario	Token type	Price (per million tokens)
0 < Token ≤ 32,768	model input	`input_token_tier1`	1.44 USD
	model input (implicit cache hit)	`input_token_tier1_cached`	0.288 USD
	model input (explicit cache hit)	`input_token_tier1_cached_explicit`	0.144 USD
	model input (create explicit cache)	`input_token_tier1_create_cache`	1.8 USD
	model output (non-thinking)	`output_token_tier1`	7.2 USD
	model output (thinking mode)	`output_token_tier1_thinking`	7.2 USD
32,768 < Token ≤ 131,072	model input	`input_token_tier2`	2.88 USD
	model input (implicit cache hit)	`input_token_tier2_cached`	0.576 USD
	model input (explicit cache hit)	`input_token_tier2_cached_explicit`	0.288 USD
	model input (create explicit cache)	`input_token_tier2_create_cache`	3.6 USD
	model output (non-thinking)	`output_token_tier2`	14.4 USD
	model output (thinking mode)	`output_token_tier2_thinking`	14.4 USD
131,072 < Token ≤ 258,048	model input	`input_token_tier3`	3.6 USD
	model input (implicit cache hit)	`input_token_tier3_cached`	0.72 USD
	model input (explicit cache hit)	`input_token_tier3_cached_explicit`	0.36 USD
	model input (create explicit cache)	`input_token_tier3_create_cache`	4.5 USD
	model output (non-thinking)	`output_token_tier3`	18 USD
	model output (thinking mode)	`output_token_tier3_thinking`	18 USD

Billing

Billing frequency: Billed hourly.
Due to data aggregation delays, inference fees may take several hours to appear on your bill after a job is complete. The information in Alibaba Cloud Billing Management is final.
View your bills
1. Log on to the Alibaba Cloud Billing Management console.
2. In the left navigation pane, choose Billing > Bill Details.
3. On the Bill Details page, set Product Name to MaxCompute and Product Name to MaxCompute model computing service.

FAQ

Q: How do I estimate inference costs?
A: You can estimate costs based on the pricing tables and your expected input and output token lengths. For example, a job with 1,000 inference calls using the qwen3-max model, where each call averages 2,000 input and 1,000 output tokens, costs approximately CNY 18 for the model compute service.
Q: Is a free tier or trial available?
A: The model compute service is offered only on a pay-as-you-go basis and does not have a free tier. We recommend testing with a small dataset first to validate performance and estimate costs.
Q: Can I set a spending limit to prevent overages?
A: No, the service does not support spending or usage limits. To control costs, monitor your usage by reviewing your bills.

MaxCompute:AI inference fees

Overview

Billing rules

Pricing

qwen3.7-max

Chinese mainland

International

qwen3.7-plus

Chinese mainland

International

qwen3-vl-embedding

text-embedding-v4

Chinese mainland

International

qwen3.6-plus

Chinese mainland

International

qwen3.6-flash

Chinese mainland

International

deepseek-v4-pro

Chinese mainland

International

deepseek-v4-flash

Chinese mainland

International

qwen3.5-397b-a17b

qwen3-asr-flash

Chinese mainland

International

qwen3-max (sunsetting soon)

Chinese mainland

International

Billing

FAQ

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