- Developers testing open models for coding, reasoning, and agent workflows
- Teams comparing V4-Pro quality against lower-cost V4-Flash throughput
- Builders who need long-context model options with official API and open-weight reference links
Models
DeepSeek V4
Open DeepSeek V4 model family for million-token context, coding, reasoning, and agent workflows.
MIT License
Open sourceLocal firstSelf-hostedAPI
About
DeepSeek V4 overview
DeepSeek V4 is DeepSeek's current open model family, with V4-Pro and V4-Flash variants surfaced through DeepSeek's official API docs and DeepSeek AI's Hugging Face release pages.
Two-model V4 family
DeepSeek's official V4 preview describes V4-Pro as the stronger variant and V4-Flash as the faster, more economical option.
Agent builders can route easier executor tasks to Flash and reserve Pro for higher-value reasoning or coding work.Million-token context direction
The official V4 release and pricing pages position V4 around very long context, thinking and non-thinking modes, JSON output, and tool calls.
Long-context reliability matters for agents that read large repositories, documents, logs, or task histories.Official API plus open-weight references
DeepSeek points readers to official API model IDs and a Hugging Face collection for the V4 open-weight release path.
Teams can compare hosted API behavior with model-card and open-weight constraints before building production routing. Use cases
When to use DeepSeek V4
Coding agent model routing
Test V4-Flash for cheaper planning and executor steps, then escalate to V4-Pro when deeper reasoning or code review quality is required.
Long-context research and analysis
Evaluate how V4 handles large documents, repository context, meeting archives, or task traces before trusting million-token claims.
Open-model comparison baseline
Compare DeepSeek V4 against Qwen, Kimi, GLM, Mistral, Gemma, and DeepSeek-R1 with the same prompts, latency budget, and license review.
Compare
How it compares
Choose DeepSeek V4 when you need the current DeepSeek family vs DeepSeek-R1
R1 remains useful as a reasoning baseline, but V4 is the newer DeepSeek family to test for long context, coding, tool calls, and current API behavior.
Use V4-Flash before V4-Pro when cost and throughput matter vs V4-Pro-only routing
Flash should be evaluated first for simpler agent steps; Pro is more appropriate when quality gains justify the higher-cost path.
Do not rank it from benchmark headlines alone vs generic leaderboard selection
Run your own coding traces, tool-call prompts, retrieval context, and safety checks before putting V4 into a product loop.
FAQ
Questions
What should I check before using DeepSeek V4?
Run DeepSeek V4 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it.
Is DeepSeek V4 open source?
DeepSeek V4 is listed with MIT based on the official source links in this profile. Re-check the repository, model card, or docs before production use.
Who should evaluate DeepSeek V4?
DeepSeek V4 is most worth evaluating for developers testing open models for coding, reasoning, and agent workflows.
Is DeepSeek V4 newer than DeepSeek-R1?
Yes. This page treats DeepSeek-R1 as an older reasoning baseline and DeepSeek V4 as the current DeepSeek model family to evaluate for coding, long context, tool calls, and agent workflows.
Tags
Capabilities
Decision brief
JSON
Should you use DeepSeek V4?
- Teams that need a simple consumer chatbot with no model or provider evaluation
- Builders who cannot review model cards, license terms, safety behavior, and serving cost before adoption
- Use cases that require verified image input support rather than text, tool calls, JSON output, and long-context reasoning
- Verified 2026-06-02
- License: MIT
- No GitHub repo recorded
- Open-source signal
Deployment
local, self hosted, cloud
Permission surface
shell/files, memory, messages, external services
Decision signals
Local first, Self-hostable, API
Agent packet
Structured decision data for DeepSeek V4
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
local inference, tool calling
Constraints
open source, self hosted, local first, open weights
Deployment
local, self hosted, cloud
Permission surface
shell/files, memory, messages, external services
Recommended workflows
Evaluation and observability, Local or private AI stack
Overview
What DeepSeek V4 does
What it is
DeepSeek V4 is an open model resource to evaluate by workload, serving path, context behavior, license terms, and how reliably it supports the agent or local AI tasks you actually plan to run.
Why it matters
Model pages get stale quickly. DeepSeek-R1 was a major open reasoning baseline, but teams choosing models in mid-2026 should also test V4 because it targets long context, coding, tool calls, JSON output, and agentic workflows that sit closer to real production use.
How to evaluate it
Run DeepSeek V4 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type model
Category Models
Maturity active
Difficulty Unknown
License MIT
Pricing open source
Verified 2026-06-02
Source confidence medium
Risk level elevated
Fit matrix
Where DeepSeek V4 fits in an agent stack
strong
Evaluation and observability
DeepSeek V4 has multiple signals for evaluation and observability, including matching tags, capabilities, category, or positioning.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong
Local or private AI stack
DeepSeek V4 has multiple signals for local or private ai stack, including matching tags, capabilities, category, or positioning.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Coding agent workflow
DeepSeek V4 has at least one signal for coding agent workflow, but should be checked against a real task before adoption.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Connector or protocol layer
DeepSeek V4 has at least one signal for connector or protocol layer, but should be checked against a real task before adoption.
- Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Memory or RAG workflow
DeepSeek V4 has at least one signal for memory or rag workflow, but should be checked against a real task before adoption.
- Create, update, retrieve, correct, and delete memory or retrieval objects with real data.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Reusable skill workflow
DeepSeek V4 has at least one signal for reusable skill workflow, but should be checked against a real task before adoption.
- Run one skill end to end and check whether it produces evidence or structured output.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Repositories, files, issues, terminal output, and test results
- Tool schemas, API requests, service resources, and auth scopes
- Prompts, messages, documents, images, or model inputs
- Official setup instructions and a small real workflow
Likely outputs
- Diffs, commits, explanations, test results, or review notes
- Scores, traces, regression results, dashboards, or failure cases
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
Homepage homepage
Official or project-controlled source for this resource profile.
Docs docsDocumentation source for setup, API shape, and operational behavior.
Demo huggingfaceOfficial or project-controlled source for this resource profile.
Source homepageOfficial or project-controlled source for this resource profile.
Source homepageOfficial or project-controlled source for this resource profile.
Source huggingfaceOfficial or project-controlled source for this resource profile.
Source huggingfaceOfficial or project-controlled source for this resource profile.
DeepSeek V4 is listed as open source.
License metadata: MITDeepSeek V4 supports these recorded deployment modes: local, self hosted, cloud.
OpenAgent decision signal metadata.DeepSeek V4 is tagged with local inference, tool calling capabilities.
OpenAgent capability taxonomy.- GitHub repository has not been recorded.
- Repository freshness has not been recorded.
Next action
How to start evaluating DeepSeek V4
Open Homepage
Start from the official source before adopting third-party instructions.
Open sourceRead setup docs
Use docs as the source of truth for installation and supported interfaces.
Open sourceOpen Demo
Start from the official source before adopting third-party instructions.
Open sourceUse the official API model IDs
Keep your existing DeepSeek API base URL and change the model ID for a controlled V4 evaluation.
model="deepseek-v4-flash" # or "deepseek-v4-pro" Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about DeepSeek V4
What should I check before using DeepSeek V4?
Run DeepSeek V4 on a fixed prompt set from your own workflow. Compare quality, latency, context handling, retry behavior, deployment path, and license fit against nearby open models before adopting it.
Is DeepSeek V4 open source?
DeepSeek V4 is listed with MIT based on the official source links in this profile. Re-check the repository, model card, or docs before production use.
Who should evaluate DeepSeek V4?
DeepSeek V4 is most worth evaluating for developers testing open models for coding, reasoning, and agent workflows.
Is DeepSeek V4 newer than DeepSeek-R1?
Yes. This page treats DeepSeek-R1 as an older reasoning baseline and DeepSeek V4 as the current DeepSeek model family to evaluate for coding, long context, tool calls, and agent workflows.
Should I use V4-Pro or V4-Flash first?
Start with V4-Flash for cost-sensitive or high-throughput tasks, then test V4-Pro on harder coding and reasoning prompts where quality gains might justify the cost.
Is DeepSeek V4 suitable for image input?
Verify the current official docs before relying on image input. This profile focuses on the official text, long-context, JSON output, and tool-call signals surfaced in DeepSeek's V4 docs.