DeepSeek V4 Pro

deepseek-v4-pro

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model launched by DeepSeek, with 1.6T total parameters, 49B activated parameters, and a 1M-token context window. It is specifically designed for advanced reasoning, coding, and long-horizon agentic workflows, delivering strong performance on knowledge, math, and software engineering benchmarks. It adopts the same architecture as DeepSeek V4 Flash and introduces a hybrid attention system that enables efficient long-context processing, along with support for multiple reasoning modes to balance speed and depth according to the task. It is ideal for complex workloads such as full codebase analysis, multi-step automation, and large-scale information synthesis, where both capability and efficiency are critical.

Context window1.0M

ProviderDeepSeek

Released2026/04/25

Playground

Pricing

The same model is available through multiple service channels — choose based on latency, reliability and cost.

Prices in $ / 1M tokens

To pick a channel, add a provider field to the request body, for example "provider": { "channel": "direct" }. Valid values are direct / stable / economical; omit it to use the default channel.

Direct

Direct upstream connection — best when you need native behavior and the full context window.

Input	Output	Cache read
1.32/M	3.96/M	0.04/M

Overview

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Output

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DeepSeek V4 Pro API: The 1.6-Trillion-Parameter Open-Source Agentic Coding Flagship

DeepSeek V4 Pro is a large-scale Mixture-of-Experts (MoE) model released by DeepSeek in April 2026, with 1.6 trillion total parameters, 49B active parameters, and a 1 million token context window. It is designed for advanced reasoning, coding, and long-horizon agentic workflows, delivering strong performance on knowledge, mathematics, and software engineering benchmarks.

In Agentic Coding evaluations, DeepSeek V4 Pro has achieved the best level among current open-source models and has become the daily agentic coding model used by DeepSeek's internal employees — the official description states that its user experience is better than Sonnet 4.5, and its delivery quality is close to Opus 4.6's non-thinking mode.

SeaWhale AI provides DeepSeek V4 Pro through an OpenAI-compatible interface, supporting tool calling, streaming output, and long-context processing.

Get API Key · Model ID: deepseek-v4-pro

Why Choose DeepSeek V4 Pro

Best-in-class open-source Agentic Coding — Ranked first among open-source models in agentic coding evaluations
1.6 trillion total parameters / 49B active — Large-scale sparse MoE with a high capability ceiling and controllable inference cost
1 million token context — Fits an entire codebase and long document sets in one go
Architectural innovation — Hybrid attention, manifold-constrained hyperconnection (mHC), Muon optimizer
384K max output — Generate ultra-long code and documents in a single pass
Open source and controllable — Public weights allow private deployment

Core Capabilities

01 Agentic Coding

This is DeepSeek V4 Pro's most standout capability. It has reached the best level among open-source models in Agentic Coding evaluations, and its real-world usage experience is officially described as better than Sonnet 4.5, with delivery quality close to Opus 4.6's non-thinking mode.

Repository-level issue localization and fixing
Multi-file feature implementation
Tool calling and result verification

02 Advanced Reasoning and World Knowledge

Performs strongly on knowledge, mathematics, and software engineering benchmarks; the knowledge coverage enabled by 1.6 trillion parameters is a core advantage at this tier.

Challenging mathematical reasoning
Broad world knowledge coverage
Complex logical problem solving

03 1 Million Token Long Context

Combined with the hybrid attention architecture, the 1 million token context is truly usable in long-document and large-repository scenarios, not just a paper specification.

Complete code repository analysis
Cross-document reasoning over long documents
Up to 384K output tokens

04 Architectural Innovation

The V4 series introduces several key upgrades in architecture and optimization: the hybrid attention architecture improves long-context efficiency, while manifold-constrained hyperconnection (mHC) and the Muon optimizer improve training stability and final quality.

Hybrid attention's long-context efficiency
mHC improves representational capacity
Muon optimizer improves training results

Best Use Cases

Scenario	Description
Agentic coding	Repository-level issue fixing and end-to-end feature development
Long-context analysis	Large-project understanding within a 1 million token window
Math and reasoning	Challenging math and logic problems
Long-form content generation	384K output limit supports ultra-long document production
Domestic substitution	A flagship open-source solution when self-reliant, controllable AI is required
Private deployment	Public weights allow local deployment

Differences Between DeepSeek V4 Pro and V4 Flash

Capability	DeepSeek V4 Pro	DeepSeek V4 Flash
Model ID	`deepseek-v4-pro`	`deepseek-v4-flash`
Total parameters	1.6 trillion	284 billion
Active parameters	49B	13B
Context window	1 million tokens	1 million tokens
Max output	384K tokens	384K tokens
World knowledge	Stronger	Slightly weaker
Reasoning ability	Frontier	Close to Pro
Simple task performance	Excellent	On par with Pro
Challenging tasks	Significantly stronger	Noticeable gap

For specific billing, refer to the real-time price card at the top of the page.

How to Use the DeepSeek V4 Pro API

1. Create a SeaWhale AI API key Generate a key in the console and top up your balance.

2. Try Flash first V4 Flash is on par with Pro on simple tasks but costs much less. We recommend running through your workflow with Flash first, and only upgrading to Pro for the challenging tasks Flash can't handle well.

3. Call the API

curl -X POST https://api.seawhaleai.com/v1/chat/completions \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "deepseek-v4-pro",
    "messages": [
      {"role": "user", "content": "Read this repository, find and fix the code path causing the memory leak, and add regression tests."}
    ],
    "stream": true
  }'

FAQ

When was DeepSeek V4 released? It was released in April 2026 in two versions: Pro (1.6 trillion parameters) and Flash (284 billion parameters). Both versions support a 1 million token context.

What level is its coding capability? It has reached the best level among open-source models in Agentic Coding evaluations. The official description states that the user experience is better than Sonnet 4.5, with delivery quality close to Opus 4.6's non-thinking mode.

Will 1.6 trillion parameters be expensive? No. It uses a sparse MoE architecture with only 49B active parameters, so inference costs are far lower than a dense model with the same total parameter count.

How should I choose between Pro and Flash? On simple tasks, the two are on par, so Flash is more cost-effective; choose Pro for challenging tasks and scenarios that require broad world knowledge.

What are the context and output limits? 1 million token context and a maximum output of 384,000 tokens — the output ceiling is quite outstanding among comparable models.

What's special about the architecture? It introduces a hybrid attention architecture (improving long-context efficiency), the manifold-constrained hyperconnection mHC, and the Muon optimizer.

Why Use the DeepSeek V4 Pro API with SeaWhale AI

No need to build your own cluster — No need to provide your own GPU resources for a trillion-parameter model
OpenAI-compatible interface — Integrate by changing two lines of existing code
Flexible Pro / Flash switching — Route by task difficulty for optimal cost
RMB settlement — Domestic models are billed in RMB, keeping accounting clear

API

API integration

Model IDUse this value as the model in inference requests

deepseek-v4-pro

API KeyBearer token used to authenticate inference requests

Manage API keys

Base URLOpenAI compatible · /chat/completions

https://api.seawhaleai.com/v2/

provider OptionalSelects a service channel; omit it and the system picks the default

"provider": { "channel": "direct" }

deepseek-v4-pro usage examples

SeaWhale AI is compatible with the OpenAI API protocol, so you can call it with the OpenAI SDK or plain HTTP requests. Streaming is enabled by default.

About the provider parameter (optional, a SeaWhale AI extension): most models are served over several channels that differ slightly in price and reliability. Add a provider field to the request body to pick one; omit it and the system selects the default channel — normal calls are unaffected.

provider is not part of the official OpenAI protocol — it is a SeaWhale AI extension that only takes effect on this platform. The OpenAI SDK allows custom fields like this to pass through; see the examples below.

Value	Channel	Best for
`direct`	Direct	The official upstream link, for native behavior and the full context window
`stable`	Preferred	Balanced availability and speed — a good default for production traffic
`economical`	Economy	Cost first, well suited to batch processing and price-sensitive workloads

Available channels and their prices are listed under "Pricing" above (channels vary by model). Additional notes:

Syntax: "provider": { "channel": "direct" }.
If the requested channel is not enabled for that model, the request automatically falls back to the default channel and returns normally — it does not error.
With the official SDKs: in Python pass it via extra_body; in Node.js put it directly on the request object and it passes through. In TypeScript projects, add a // @ts-expect-error line to skip the type check.

cURLPythonNode.js

curl https://api.seawhaleai.com/v2/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <API_KEY>" \
  -d '{
    "model": "deepseek-v4-pro",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello!"}
    ],
    "provider": { "channel": "direct" },
    "stream": true
  }'
# provider is optional — remove this line to use the default channel

from openai import OpenAI

client = OpenAI(
    base_url="https://api.seawhaleai.com/v2",
    api_key="<API_KEY>",
)

stream = client.chat.completions.create(
    model="deepseek-v4-pro",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"},
    ],
    stream=True,
    # Optional: pick a service channel; omit to use the default
    extra_body={"provider": {"channel": "direct"}},
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

import OpenAI from 'openai'

const client = new OpenAI({
  baseURL: 'https://api.seawhaleai.com/v2',
  apiKey: '<API_KEY>',
})

const stream = await client.chat.completions.create({
  model: 'deepseek-v4-pro',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Hello!' },
  ],
  stream: true,
  // Optional: pick a service channel; omit to use the default
  // @ts-expect-error provider is a SeaWhale AI extension, not in the OpenAI SDK types
  provider: { channel: 'direct' },
})

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? '')
}