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4.7 out of 5 stars. Excellent.
4.7(3420)

DeepSeek V4

Open-source 685B parameter mixture-of-experts model with exceptional coding capabilities and 128K context window.

Free·Best for ·1 min
Updated April 4, 2026Certified
Open SourceFree Tier
1

What is DeepSeek V4?

DeepSeek V4 is an open-source large language model featuring 685 billion parameters with Mixture-of-Experts architecture. Launched in March 2026, it excels at code generation, mathematical reasoning, and multilingual tasks. The model activates only 37B parameters per token, making it highly efficient while delivering competitive performance with proprietary models. Features 128K token context window, Apache 2.0 license, and strong performance on coding benchmarks.

Best for: Open-source requirements · Self-hosted deployment · Coding tasks

2

Developer Stack Fit

Engineering evaluation

Quick read on where DeepSeek V4 fits in a software team's AI stack. Validate final fit against your codebase, data policy, and deployment model.

Methodology
Stack layer
Self-Hosted
Deployment model
Self-hosted or local option
Open-source status
Yes or source-available
API support
Not a primary API tool
MCP support
No MCP signal found
Security posture
Stronger controls worth validating
Best use case
Open-source requirements
3

Key Features

  1. 01

    685B total parameters (MoE)

    Open-source with Apache 2.0 license

  2. 02

    37B active parameters per token

    Highly efficient MoE architecture

  3. 03

    128K token context window

    Excellent coding capabilities

  4. 04

    Apache 2.0 open-source license

    A core development capability that teams use daily.

  5. 05

    Excellent code generation

    A core development capability that teams use daily.

  6. 06

    Strong mathematical reasoning

    A core development capability that teams use daily.

  7. 07

    Multilingual support (100+ languages)

    A core development capability that teams use daily.

  8. 08

    Self-hosted deployment

    A core development capability that teams use daily.

  9. 09

    Commercial usage rights

    A core development capability that teams use daily.

  10. 10

    Active community support

    A core development capability that teams use daily.

4

Pros & Cons

What stands out

  • Completely free and open source
  • Strong coding and math performance
  • Efficient inference (5.4% activation)
  • Commercial-friendly license
  • Active development community

Watch outs

  • Requires significant hardware for local use
  • Less polished than commercial alternatives
  • Setup complexity for self-hosting
  • Smaller ecosystem than proprietary models
5

Pricing Plans

DeepSeek V4 Pricing

Choose the perfect plan for your needs. All plans include our core features with different usage limits and advanced capabilities.

Most Popular

Open Source

Free
Apache 2.0 license
685B total parameters
37B active per token
128K context window
Full commercial rights
Local deployment
Model weights available
Get Started Free

Need a Custom Solution?

Looking for enterprise features or custom pricing? Contact DeepSeek V4 directly for tailored solutions.

Contact Sales

Most teams land on the Open Source plan.

6

Alternatives

ToolRatingPrice
DeepSeek V44.7Freecurrent
DeerFlow4.7Freeview →
Cursor4.8Freemiumview →
Entire Checkpoints4.3Freeview →
OpenCode4.6Freemiumview →
DiffSense4.4Freeview →
7

FAQ

What is DeepSeek V4 and how does it work?

DeepSeek V4 is a development tool that open-source 685b parameter mixture-of-experts model with exceptional coding capabilities and 128k context window.. It uses AI to help users improve productivity through analyzing input and generating relevant output.

Is DeepSeek V4 free to use?

DeepSeek V4 offers a completely free plan. You can get started without paying anything.

Is there a free plan or trial?

DeepSeek V4 doesn't offer a traditional free trial, but provides a money-back guarantee on paid plans.

What can DeepSeek V4 do?

Code generation and review
Research and experimentation
On-premise AI deployments
Mathematical problem solving
Multilingual content creation

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