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  4. /deepseek-flash
DeepSeek
DeepSeek Flash
$ 
Call DeepSeek's current Flash model with the deepseek-flash model string on GPTProto. Access the same underlying DeepSeek V4.1 Flash model for text, coding, vision, and agent workflows while sharing one API key and balance across 200+ models.

模態

輸入: 文字輸入: 圖像
輸出: 文字

/

DeepSeek Flash pricing

Estimate a request with real work scenarios using current GPTProto rates.

用量數量單價小計
tokens
$0.3/1M$0.0004
tokens
$1.2/1M$0.0009
tokens
$0.006/1M$0.0001
單次請求費用$0.0015
請求次數
儲值金額

儲值 $100 你將獲得:

1、

儲值額度永久有效。你總共會收到 $100.00。

2、

一把金鑰暢用 200+ 全球前沿 AI 模型。新模型上線當天即可使用。

相關模型
所有模型
DeepSeek Flash
目前
$ 
byDeepSeek$0.3/M input$1.2/M output
Hy4 Preview
$ 
byHunyuan$0.7923/M input$2.376/M output
GPT 6 Astra
$ 
byOpenAI1.05M context$8/M input$40/M output
Gemini 3.8 Flash
$ 
byGoogle1.05M context$0.9/M input$4.5/M output
Claude Fable 5.1
$ 
byClaude1M context$9/M input$45/M output
Qwen3.8 Max 0902
$ 
byQwen1M context$1.8/M input$5.4/M output
GLM 5.3 Flash
$ 
byZ-AI1.31M context$0.15/M input$0.5/M output
DeepSeek v4 Flash Vision Exp
$ 
byDeepSeek1.05M context$0.3/M input$1.2/M output
GLM 5.3
$ 
byZ-AI1.31M context$1.26/M input$3.96/M output
Gemini 3.7 Flash
$ 
byGoogle1.05M context$0.9/M input$4.5/M output
Grok 4.6
$ 
byGrok500K context$1.2/M input$3.6/M output
Qwen3.8 Max
$ 
byQwen1M context$1.8/M input$5.4/M output
Claude Opus 5
$ 
byClaude1M context$4.5/M input$22.5/M output
Gemini 3.6 Flash
$ 
byGoogle1.05M context$0.9/M input$4.5/M output
Kimi K3
$ 
byMoonshotAI1.05M context$2.7/M input$13.5/M output
GPT 5.6 Luna
$ 
byOpenAI1.05M context$0.16/M input$0.96/M output
GPT 5.6 Terra
$ 
byOpenAI1.05M context$1.6/M input$9.6/M output
Grok 4.5
$ 
byGrok500K context$1.2/M input$3.6/M output
Claude Sonnet 5
$ 
byClaude1M context$1.8/M input$9/M output
MiniMax M3
$ 
byMiniMax1.05M context$0.48/M input$0.96/M output
GLM 5.2
$ 
byZ-AI1.05M context$1.26/M input$3.96/M output
Qwen3.7 Max
$ 
byQwen1M context$0.36/M input$1.44/M output
DeepSeek v4 Flash
$ 
byDeepSeek1.05M context$0.3/M input$1.2/M output
DeepSeek v4 Pro
$ 
byDeepSeek1.05M context$1.122/M input$3.366/M output
Grok 4.3
$ 
byGrok1M context$0.75/M input$1.5/M output
Kimi K2.6
$ 
byMoonshotAI262K context$0.855/M input$3.6/M output
DeepSeek v3.2
$ 
byDeepSeek164K context$0.168/M input$0.252/M output
MiniMax M2.5
$ 
byMiniMax205K context$0.24/M input$0.96/M output
Kimi K2.5
$ 
byMoonshotAI262K context$0.54/M input$2.7/M output
DeepSeek v3
$ 
byDeepSeek$0.1622/M input$0.6487/M output
DeepSeek R1
$ 
byDeepSeek64K context$0.33/M input$1.3135/M output
Doubao Seed 1.6 Thinking (Build 250715)
$ 
byBytedance262K context$0.0971/M input$0.9714/M output
Doubao Seed 1.6 Thinking (Build 250615)
$ 
byBytedance262K context$0.0971/M input$0.9714/M output
Doubao Seed 1.6 Flash (Build 250615)
$ 
byBytedance262K context$0.0182/M input$0.1821/M output
模型輸入 → 輸出
DeepSeek Flash目前
$ 
——$0.30 / $1.20 每 1M— / $0.006 每 1M
輸入: 文字輸入: 圖像
輸出: 文字
Hy4 Preview
$ 
—$0.79 / $2.38 每 1M— / $0.04 每 1M
輸入: 文字
輸出: 文字
GPT 6 Astra
$ 
1.05M$8.00 / $40.00 每 1M$10.00 / $0.80 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Gemini 3.8 Flash
$ 
1.05M$0.90 / $4.50 每 1M$0.60 / $0.09 每 1M
輸入: 文字輸入: 圖像輸入: 影片輸入: 文件輸入: 音訊
輸出: 文字
Claude Fable 5.1
$ 
1M$9.00 / $45.00 每 1M$11.25 / $0.23 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Qwen3.8 Max 0902
$ 
1M$1.80 / $5.40 每 1M$2.25 / $0.23 每 1M
輸入: 文字輸入: 圖像輸入: 影片輸入: 文件輸入: 音訊
輸出: 文字
GLM 5.3 Flash
$ 
—1.31M$0.15 / $0.50 每 1M— / $0.03 每 1M
輸入: 文字輸入: 圖像輸入: 影片輸入: 文件
輸出: 文字
DeepSeek v4 Flash Vision Exp
$ 
—1.05M$0.30 / $1.20 每 1M— / $0.006 每 1M
輸入: 文字輸入: 圖像
輸出: 文字
GLM 5.3
$ 
1.31M$1.26 / $3.96 每 1M— / $0.23 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Gemini 3.7 Flash
$ 
1.05M$0.90 / $4.50 每 1M$0.60 / $0.09 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Grok 4.6
$ 
500K$1.20 / $3.60 每 1M— / $0.30 每 1M
輸入: 文字輸入: 圖像
輸出: 文字
Qwen3.8 Max
$ 
1M$1.80 / $5.40 每 1M$2.25 / $0.23 每 1M
輸入: 文字輸入: 圖像輸入: 影片輸入: 文件
輸出: 文字
Claude Opus 5
$ 
1M$4.50 / $22.50 每 1M$5.63 / $0.45 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Gemini 3.6 Flash
$ 
1.05M$0.90 / $4.50 每 1M$0.60 / $0.09 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Kimi K3
$ 
1.05M$2.70 / $13.50 每 1M$0.27 / $0.27 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
GPT 5.6 Luna
$ 
1.05M$0.16 / $0.96 每 1M$0.20 / $0.02 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
GPT 5.6 Terra
$ 
1.05M$1.60 / $9.60 每 1M$2.00 / $0.16 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Grok 4.5
$ 
500K$1.20 / $3.60 每 1M$0.30 / $0.30 每 1M
輸入: 文字輸入: 圖像
輸出: 文字
Claude Sonnet 5
$ 
1M$1.80 / $9.00 每 1M$2.25 / $0.18 每 1M
輸入: 文字輸入: 文件
輸出: 文字
MiniMax M3
$ 
1.05M$0.48 / $0.96 每 1M$0.10 / $0.10 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
GLM 5.2
$ 
1.05M$1.26 / $3.96 每 1M$0.23 / $0.23 每 1M
輸入: 文字輸入: 圖像輸入: 文件
輸出: 文字
Qwen3.7 Max
$ 
1M$0.36 / $1.44 每 1M$0.07 / $0.07 每 1M
輸入: 文字輸入: 文件
輸出: 文字
DeepSeek v4 Flash
$ 
—1.05M$0.30 / $1.20 每 1M— / $0.006 每 1M
輸入: 文字
輸出: 文字
DeepSeek v4 Pro
$ 
1.05M$1.12 / $3.37 每 1M— / $0.04 每 1M
輸入: 文字
輸出: 文字
Grok 4.3
$ 
1M$0.75 / $1.50 每 1M$0.12 / $0.12 每 1M
輸入: 文字輸入: 圖像
輸出: 文字
Kimi K2.6
$ 
262K$0.85 / $3.60 每 1M$0.14 / $0.14 每 1M
輸入: 文字輸入: 文件
輸出: 文字
DeepSeek v3.2
$ 
164K$0.17 / $0.25 每 1M$0.02 / $0.02 每 1M
輸入: 文字
輸出: 文字
MiniMax M2.5
$ 
205K$0.24 / $0.96 每 1M$0.30 / $0.02 每 1M
輸入: 文字輸入: 文件
輸出: 文字
Kimi K2.5
$ 
262K$0.54 / $2.70 每 1M$0.09 / $0.09 每 1M
輸入: 文字輸入: 文件
輸出: 文字
DeepSeek v3
$ 
—$0.16 / $0.65 每 1M—
輸入: 文字
輸出: 文字
DeepSeek R1
$ 
64K$0.33 / $1.31 每 1M—
輸入: 文字
輸出: 文字
Doubao Seed 1.6 Thinking (Build 250715)
$ 
262K$0.10 / $0.97 每 1M—
輸入: 文字輸入: 圖像
輸出: 文字
Doubao Seed 1.6 Thinking (Build 250615)
$ 
262K$0.10 / $0.97 每 1M—
輸入: 文字輸入: 圖像
輸出: 文字
Doubao Seed 1.6 Flash (Build 250615)
$ 
262K$0.02 / $0.18 每 1M—
輸入: 文字輸入: 圖像
輸出: 文字

DeepSeek Flash API with the deepseek-flash Model String

Use DeepSeek Flash for long-context reasoning, code analysis, structured output, tool calls, and native image understanding. The current deepseek-flash route points to DeepSeek V4.1 Flash, with support for up to 1M tokens of context and 384K output. For a task-focused visual workflow, open the DeepSeek Flash Image-to-Text API.

Current Flash Model Alias

Use the concise deepseek-flash model string to access the current DeepSeek Flash route on GPTProto. It presently points to the same underlying model as DeepSeek V4.1 Flash.

Native Text and Image Input

Send text, screenshots, charts, diagrams, or scanned pages and receive text output. Use the dedicated Image-to-Text page for image-focused prompts and examples.

1M Context and 384K Output

Process large repositories, lengthy documents, conversation histories, and detailed tool results within a context window of up to one million tokens.

One Key Across 200+ Models

Use one GPTProto key and shared balance to test DeepSeek Flash, compare alternative models, and configure workload-specific fallbacks without opening a separate provider account.

What Is the DeepSeek Flash API?

The DeepSeek Flash API is the general GPTProto access page for the deepseek-flash model string. At the time of publication, this route points to DeepSeek V4.1 Flash, the multimodal Mixture-of-Experts model released by DeepSeek on September 10, 2026. It accepts text and images as input and returns text.

The short model name and the formal V4.1 name describe the same current inference model, but they serve different integration and search needs. Use this page when you want the exact deepseek-flash identifier, API-key access, playground testing, or a route that includes the Image-to-Text task entry. Visit the DeepSeek V4.1 Flash API page when you need version-specific architecture, release details, and comparisons with V4 Pro.

Through GPTProto, the same API key can be used for DeepSeek Flash and other supported language, image, and video models. GPTProto lists this model at its standard rate, so the value of this route is consolidated access and model switching rather than a lower-than-official price claim.

Specification DeepSeek Flash on GPTProto
GPTProto model string deepseek-flash
Current underlying model DeepSeek V4.1 Flash
Input and output Text and images to text
Context window Up to 1M tokens
Maximum output Up to 384K tokens
Reasoning Thinking and non-thinking modes
Developer features Tool calls, JSON output, and streaming
Image-specific route DeepSeek Flash Image-to-Text API
Pricing position Standard model rate; no GPTProto discount claim

DeepSeek Flash vs DeepSeek V4.1 Flash: Are They the Same Model?

Yes. On GPTProto, deepseek-flash and deepseek-v4.1-flash currently point to the same DeepSeek V4.1 Flash model. The difference is the identifier and the purpose of each landing page, not a claimed difference in intelligence, speed, context size, or training.

Decision point DeepSeek Flash DeepSeek V4.1 Flash
Primary search intent Exact API alias and model string Formal version name and release research
Model identifier deepseek-flash deepseek-v4.1-flash
Underlying model DeepSeek V4.1 Flash DeepSeek V4.1 Flash
Main-page focus API access, alias behavior, use cases, and task routing Architecture, specifications, benchmark context, and V4 Pro comparison
Image-to-Text entry Dedicated task page linked from this route Mentioned as a capability, not the main keyword target
Recommended use General access and image-aware workflows Version-pinned evaluation and release-specific documentation

Choose the model string that matches your integration and reporting needs. If production logs, dashboards, or evaluations must preserve the formal release name, use the versioned identifier. If your workflow uses the short DeepSeek Flash route or needs its Image-to-Text task page, use deepseek-flash. Because routing behavior may change with future DeepSeek releases, record the resolved model version in your evaluation notes.

DeepSeek Flash API Applications

  • Coding and repository analysis: Supply relevant files, issue context, logs, and test results for code explanation, dependency tracing, refactoring plans, debugging, and review. Keep the prompt focused even when the full context window is available.

  • Long-document processing: Analyze technical specifications, contracts, reports, transcripts, and support histories without forcing every task through a small retrieval window. Set a realistic output limit so the model returns the required result rather than an unnecessarily long response.

  • Agent and tool workflows: Use tool calls, structured output, and streaming for agents that inspect data, call application functions, evaluate returned results, and continue across multiple steps. Your application remains responsible for executing tools, validating arguments, and enforcing permissions.

  • Image-aware tasks: The model can read screenshots, charts, diagrams, and scanned pages alongside text instructions. For dedicated extraction, description, visual question answering, and screenshot analysis, continue to the DeepSeek Flash Image-to-Text API instead of expanding those instructions on this main page.

Integration Notes for the deepseek-flash Model String

Treat deepseek-flash as a distinct model identifier in configuration, usage reports, and fallback rules even though it currently resolves to the same model as the V4.1 route. Do not silently replace one string with the other in production without a canary test. Confirm response parsing, reasoning fields, tool-call arguments, image payloads, latency, and token use with the exact route your application will call.

For thinking-mode tool workflows, retain any reasoning state required by the exposed API schema between turns. Also validate which sampling parameters take effect in thinking and non-thinking modes. A request accepted by another OpenAI-compatible model may still behave differently when parameters are ignored, constrained, or returned in model-specific fields.

The 1M-token context and 384K output ceiling are maximum capabilities, not recommended defaults. Limit prompts to relevant material, cap output according to the task, stream long responses, and set client-side step and timeout limits. These controls are especially important for background agents and batch jobs.

When Should You Choose DeepSeek Flash?

Choose DeepSeek Flash when you want the short deepseek-flash identifier, need native text-and-image understanding, or plan to connect the model to coding tools and long-running workflows. It is also the clearer parent page for the Image-to-Text task route because the corresponding functionality is exposed under this model string on GPTProto.

Choose the formal DeepSeek V4.1 Flash page when the reader is researching that exact release, architecture, benchmarks, or its relationship with DeepSeek V4 Pro. For short classification, extraction, or rewriting tasks that do not need vision or long context, compare a smaller GPTProto model before making DeepSeek Flash the default route.

DeepSeek Flash API: Frequently Asked Questions

What model string should I use for the DeepSeek Flash API?

Use deepseek-flash for this GPTProto model route. Keep the string in environment configuration rather than scattering it throughout application code, which makes later model changes and A/B tests easier to manage.

Are deepseek-flash and deepseek-v4.1-flash the same model?

They currently point to the same underlying DeepSeek V4.1 Flash model on GPTProto. The two identifiers have separate pages because users may search for the short API model string or the formal release name. Do not describe them as different capability tiers.

Does deepseek-flash support Image to Text?

Yes. This route supports image-and-text input with text output. Use the DeepSeek Flash Image-to-Text API page for image upload guidance, visual task examples, and prompts designed specifically for extraction, description, and screenshot analysis.

Can DeepSeek Flash generate images?

No. It analyzes images and returns text; it does not create image files. Use a GPTProto image-generation model when the desired output is an illustration, product image, poster, or edited picture.

How do I get a DeepSeek Flash API key?

Create a GPTProto account, add balance, and generate an API key from the dashboard. The same key can access deepseek-flash and other supported GPTProto models without separate credentials and balances for each provider.

What are the DeepSeek Flash context and output limits?

The current underlying model supports up to a 1M-token context window and up to 384K output tokens. Actual task quality and runtime depend on prompt structure, requested output length, tool activity, and the amount of relevant information in context.

Does the DeepSeek Flash API support agents and tool calls?

Yes. The model supports tool calls, structured JSON output, streaming, and reasoning modes. Your agent framework must still execute tools, preserve required conversation state, validate arguments, restrict permissions, and handle retries or failed steps.

How much does DeepSeek Flash cost on GPTProto?

GPTProto lists the model at its standard rate and does not claim a price discount. Use the pricing panel and calculator above for the current input, cached-input, and output rates. One GPTProto balance can also be used across 200+ other models.

Should I use deepseek-flash or deepseek-v4.1-flash in production?

Use the identifier that matches the route you have tested and the naming you need in logs. Choose deepseek-flash for the short general route and its Image-to-Text task entry; choose the versioned string when release-specific tracking matters. Run the same canary evaluation before switching either identifier.

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