deepseek-v4.1-flash

Updated at:

DeepSeek-V4.1-Flash is the lightweight flagship of DeepSeek's new architecture family, packing 552B total MoE parameters to deliver flagship-surpassing intelligence across key benchmarks, including out-performing DeepSeek-V4-Pro. It adopts a Causal Encoder-Decoder asymmetric design with 8B active parameters for input and 16B for output, and offers native multimodal visual understanding. KV Cache usage is cut to one-quarter of the previous generation's HBM and one-eighth of its SSD storage, dramatically lowering costs for long-context and agentic workloads. With a 1M-token context window and up to 384K-token maximum output, it balances high throughput, low latency, and exceptional cost efficiency.

Inference Service Provider

The inference service provider for deepseek-v4.1-flash is Alibaba Cloud Model Studio.

Model Capabilities

China (Beijing)

CapabilitySupportCapabilitySupport

Input Modality

Text, Image

Output Modality

Text

Model Experience

Supported

Function Calling

Supported

Structured Outputs

Supported (JSON Object only)

Web Search

Supported

Prefix Completion

Unsupported

Context Caching

Supported

Batch Inference

Unsupported

Fine-tuning

Unsupported

Singapore

Scope: International

CapabilitySupportCapabilitySupport

Input Modality

Text, Image

Output Modality

Text

Model Experience

Supported

Function Calling

Supported

Structured Outputs

Supported (JSON Object only)

Web Search

Supported

Prefix Completion

Unsupported

Context Caching

Supported

Batch Inference

Unsupported

Fine-tuning

Unsupported

Germany (Frankfurt)

Scope: Global

CapabilitySupportCapabilitySupport

Input Modality

Text, Image

Output Modality

Text

Model Experience

Supported

Function Calling

Supported

Structured Outputs

Supported (JSON Object only)

Web Search

Unsupported

Prefix Completion

Unsupported

Context Caching

Supported

Batch Inference

Unsupported

Fine-tuning

Unsupported

US (Virginia)

Scope: Global

CapabilitySupportCapabilitySupport

Input Modality

Text, Image

Output Modality

Text

Model Experience

Supported

Function Calling

Supported

Structured Outputs

Supported (JSON Object only)

Web Search

Unsupported

Prefix Completion

Unsupported

Context Caching

Supported

Batch Inference

Unsupported

Fine-tuning

Unsupported

Japan (Tokyo)

Scope: Global

CapabilitySupportCapabilitySupport

Input Modality

Text, Image

Output Modality

Text

Model Experience

Supported

Function Calling

Supported

Structured Outputs

Supported (JSON Object only)

Web Search

Unsupported

Prefix Completion

Unsupported

Context Caching

Supported

Batch Inference

Unsupported

Fine-tuning

Unsupported

Context Limits

ParameterValueParameterValue

Max Input Length

1000000

Max Output Length

393216

Context Window

1000000

Max Input Length (Thinking Mode)

1000000

Max Output Length (Thinking Mode)

393216

Max Chain-of-Thought Length

393216

Pricing

This page only shows the original pricing for model API calls, excluding any limited-time promotions. Visit Model Studio Console for promotional offers.

Idle hours are 22:00–08:00 the next day (UTC+8); all other times are busy hours.

China (Beijing)

Billing ItemPrice (CNY)Unit

Input (Idle hours)

1

Per 1M tokens

Input (Busy hours)

2

Per 1M tokens

Output (Idle hours)

4

Per 1M tokens

Output (Busy hours)

8

Per 1M tokens

Input(Implicit Cache, Idle hours)

0.02

Per 1M tokens

Input(Implicit Cache, Busy hours)

0.04

Per 1M tokens

Singapore

Scope: International

Billing ItemPrice (CNY)Unit

Input (Idle hours)

1.094

Per 1M tokens

Input (Busy hours)

2.188

Per 1M tokens

Output (Idle hours)

4.375

Per 1M tokens

Output (Busy hours)

8.75

Per 1M tokens

Input(Implicit Cache, Idle hours)

0.022

Per 1M tokens

Input(Implicit Cache, Busy hours)

0.044

Per 1M tokens

Germany (Frankfurt)

Scope: Global

Billing ItemPrice (CNY)Unit

Input (Idle hours)

1

Per 1M tokens

Input (Busy hours)

2

Per 1M tokens

Output (Idle hours)

4

Per 1M tokens

Output (Busy hours)

8

Per 1M tokens

Input(Implicit Cache, Idle hours)

0.02

Per 1M tokens

Input(Implicit Cache, Busy hours)

0.04

Per 1M tokens

US (Virginia)

Scope: Global

Billing ItemPrice (CNY)Unit

Input (Idle hours)

1

Per 1M tokens

Input (Busy hours)

2

Per 1M tokens

Output (Idle hours)

4

Per 1M tokens

Output (Busy hours)

8

Per 1M tokens

Input(Implicit Cache, Idle hours)

0.02

Per 1M tokens

Input(Implicit Cache, Busy hours)

0.04

Per 1M tokens

Japan (Tokyo)

Scope: Global

Billing ItemPrice (CNY)Unit

Input (Idle hours)

1

Per 1M tokens

Input (Busy hours)

2

Per 1M tokens

Output (Idle hours)

4

Per 1M tokens

Output (Busy hours)

8

Per 1M tokens

Input(Implicit Cache, Idle hours)

0.02

Per 1M tokens

Input(Implicit Cache, Busy hours)

0.04

Per 1M tokens

Rate Limits

China (Beijing)

ParameterValue

RPM (Requests Per Minute)

15000

TPM (Tokens Per Minute)

1,200,000

Singapore

Scope: International

ParameterValue

RPM (Requests Per Minute)

10000

TPM (Tokens Per Minute)

1,200,000

Germany (Frankfurt)

Scope: Global

ParameterValue

RPM (Requests Per Minute)

15000

TPM (Tokens Per Minute)

1,200,000

US (Virginia)

Scope: Global

ParameterValue

RPM (Requests Per Minute)

15000

TPM (Tokens Per Minute)

1,200,000

Japan (Tokyo)

Scope: Global

ParameterValue

RPM (Requests Per Minute)

15000

TPM (Tokens Per Minute)

1,200,000

Hong Kong (China)

Scope: Global

ParameterValue

RPM (Requests Per Minute)

15000

TPM (Tokens Per Minute)

1,200,000

Snapshot Versions

deepseek-v4.1-flash-1017

DeepSeek-V4.1-Flash-1017 is the latest iteration of V4.1-Flash, trained with self-feedback-based reinforcement learning to deliver substantial gains over its predecessor across benchmarks such as Terminal-Bench 4.0, DeepSWE v1.1, and ProgramBench, while shortening task runtime and output length to reach a new performance–cost Pareto optimum across multiple harnesses. Its ability to build complete projects from scratch is further strengthened, enabling "wish-based" programming tasks such as game development and 3D modeling, while retaining the same 552B-parameter MoE, native multimodal visual understanding, 1M-token context window, and 384K-token maximum output.

Inference Service Provider

The inference service provider for deepseek-v4.1-flash-1017 is Alibaba Cloud Model Studio.

Model Capabilities

The following capabilities apply to China (Beijing), Singapore, Germany (Frankfurt), US (Virginia), Japan (Tokyo), and Hong Kong (China).

CapabilitySupport
Input ModalityText, Image
Output ModalityText
Model ExperienceSupported
ThinkingSupported
Function CallingSupported
Structured Outputs (JSON Object)Supported
Implicit Context CachingSupported
Web SearchSupported
Prefix CompletionUnsupported
Batch InferenceUnsupported
Fine-tuningUnsupported
Chat CompletionsSupported
Responses APISupported
Anthropic APISupported

The Responses API supports the built-in tools web_search, web_extractor, and code_interpreter. The Anthropic API supports the built-in tools web_search and web_fetch.

For Chat Completions, tool_choice supports auto, none, required, and specifying a named function.

Context Limits

All values are in tokens.

ParameterValue
Max Input Length1000000
Max Output Length393216
Context Window1000000
Max Input Length (Thinking Mode)1000000
Max Output Length (Thinking Mode)393216
Max Chain-of-Thought Length393216

Pricing

This page only shows the original pricing for model API calls, excluding any limited-time promotions. Visit Model Studio Console for promotional offers.

Idle hours are 22:00–08:00 the next day (UTC+8); all other times are busy hours.

China (Beijing)

Billing ItemPrice (CNY)Unit
Input (Idle hours)1Per 1M tokens
Input (Busy hours)2Per 1M tokens
Output (Idle hours)4Per 1M tokens
Output (Busy hours)8Per 1M tokens
Input (Implicit Cache Hit, Idle hours)0.02Per 1M tokens
Input (Implicit Cache Hit, Busy hours)0.04Per 1M tokens

Singapore

Scope: International

Billing ItemPrice (CNY)Unit
Input (Idle hours)1.094Per 1M tokens
Input (Busy hours)2.188Per 1M tokens
Output (Idle hours)4.375Per 1M tokens
Output (Busy hours)8.75Per 1M tokens
Input (Implicit Cache Hit, Idle hours)0.022Per 1M tokens
Input (Implicit Cache Hit, Busy hours)0.044Per 1M tokens

Germany (Frankfurt)

Scope: Global

Billing ItemPrice (CNY)Unit
Input (Idle hours)1Per 1M tokens
Input (Busy hours)2Per 1M tokens
Output (Idle hours)4Per 1M tokens
Output (Busy hours)8Per 1M tokens
Input (Implicit Cache Hit, Idle hours)0.02Per 1M tokens
Input (Implicit Cache Hit, Busy hours)0.04Per 1M tokens

US (Virginia)

Scope: Global

Billing ItemPrice (CNY)Unit
Input (Idle hours)1Per 1M tokens
Input (Busy hours)2Per 1M tokens
Output (Idle hours)4Per 1M tokens
Output (Busy hours)8Per 1M tokens
Input (Implicit Cache Hit, Idle hours)0.02Per 1M tokens
Input (Implicit Cache Hit, Busy hours)0.04Per 1M tokens

Japan (Tokyo)

Scope: Global

Billing ItemPrice (CNY)Unit
Input (Idle hours)1Per 1M tokens
Input (Busy hours)2Per 1M tokens
Output (Idle hours)4Per 1M tokens
Output (Busy hours)8Per 1M tokens
Input (Implicit Cache Hit, Idle hours)0.02Per 1M tokens
Input (Implicit Cache Hit, Busy hours)0.04Per 1M tokens

Hong Kong (China)

Scope: Global

Billing ItemPrice (CNY)Unit
Input (Idle hours)1Per 1M tokens
Input (Busy hours)2Per 1M tokens
Output (Idle hours)4Per 1M tokens
Output (Busy hours)8Per 1M tokens
Input (Implicit Cache Hit, Idle hours)0.02Per 1M tokens
Input (Implicit Cache Hit, Busy hours)0.04Per 1M tokens

Rate Limits

China (Beijing)

ParameterValue
RPM (Requests Per Minute)15000
TPM (Tokens Per Minute)1200000

Singapore

Scope: International

ParameterValue
RPM (Requests Per Minute)10000
TPM (Tokens Per Minute)1200000

Germany (Frankfurt)

Scope: Global

ParameterValue
RPM (Requests Per Minute)15000
TPM (Tokens Per Minute)1200000

US (Virginia)

Scope: Global

ParameterValue
RPM (Requests Per Minute)15000
TPM (Tokens Per Minute)1200000

Japan (Tokyo)

Scope: Global

ParameterValue
RPM (Requests Per Minute)15000
TPM (Tokens Per Minute)1200000

Hong Kong (China)

Scope: Global

ParameterValue
RPM (Requests Per Minute)15000
TPM (Tokens Per Minute)1200000

Calling Methods

Set the model field to deepseek-v4.1-flash-1017 when calling the snapshot version. For calling instructions, see: