DeepSeek V4 Network
Unified access to the DeepSeek model lineup. Run production workloads on V3.1, R1, Math-7B, Janus-Pro-7B, and VL2 today, and stay ready for V4.
Unified API surface - V4 launch intelligence - transparent pricing
Signal stream
The themes we track daily to anticipate V4 readiness.
Where teams apply DeepSeek V4
High-impact workflows
Use cases where long context, reasoning depth, and multimodal inputs make the biggest impact.
Code generation and refactoring
Generate modules, migrate frameworks, and fix bugs faster with structured reasoning.
Math and scientific reasoning
Solve GSM8K-style problems, technical derivations, and verification tasks.
Multimodal analysis
Combine text and image understanding for documents, charts, and OCR-heavy workflows.
Knowledge-base QA
Query large internal docs with long-context retrieval and structured answers.
Research synthesis
Summarize papers, compare methods, and extract evidence with citations.
Enterprise copilots
Deploy assistant workflows with guardrails, usage caps, and cost controls.
DeepSeek V4: architecture and launch signals
DeepSeek V4 is widely discussed as a next-generation Mixture-of-Experts system. Our research brief aggregates public analysis describing a trillion-scale parameter budget with sparse activation per token, a shared expert plus routed experts, and top-k routing to keep inference practical. Those notes also highlight long-context ambitions (100K-class windows are frequently mentioned) for large documents, codebases, and multi-stage reasoning.
Training discussions emphasize bigger and cleaner corpora, heavier math and code weighting, and improved routing balance. Reported benchmark references include MMLU, HumanEval, GSM8K, and MATH, but we treat these figures as directional until verified by official releases or third-party evaluations. The same notes point to multimodal expansion: strong image understanding today and video generation on the roadmap.
While V4 remains pre-launch, the current DeepSeek lineup is production-ready. V3.1 handles general chat and long context, R1 focuses on structured reasoning, Math-7B offers cost-efficient numerical accuracy, Janus-Pro-7B targets multimodal generation, and VL2 excels at OCR and document analysis. We keep these models accessible through a unified API surface and prepare the waitlist for V4 access.
- Release timing and whether the schedule shifts again.
- Multimodal depth: image quality now, video generation later.
- Benchmark verification from official or third parties.
- Open-source and self-hosting expectations plus chip optimization signals.
- V4 access model, pricing mechanics, and rollout pace.
At-a-glance V4 signals
Reported scale and context
Key reported signals we track while waiting for official specifications.
Total parameters (reported)
Active parameters per token (reported)
Context window (reported)
Built for teams shipping DeepSeek today
The network blends real-time launch intelligence with production tooling, so you can ship against V3.1 and R1 now while preparing for V4. Each block below focuses on a decision: what to build today, what to monitor next, and how to scale when access opens.
Unified API surface
Keep one integration for text, reasoning, math, and vision. Toggle models without rewriting your stack.
V4 signal watch
Daily tracking for benchmarks, timing shifts, and multimodal clues with source-backed notes.
Playground-ready comparisons
Compare outputs across V3.1, R1, Math-7B, Janus-Pro-7B, and VL2 in seconds.
Clear pricing and governance
Simple billing, 30-day free legacy access, and a documented handoff into V4 pricing.
Documentation and migration notes
Launch checklists, rate-limit guidance, and migration playbooks for V4 readiness.
Model lineup
Production-ready models today, with V4 on deck.
Signals from builders
What teams are watching
Jonathan Yombo
ML EngineerThe MoE breakdown makes the trillion-scale claims feel practical for inference.
Yves Kalume
Product LeadHaving V3.1 and R1 behind one endpoint lets us ship now and upgrade later.
Yucel Faruksahan
ResearcherLong-context signals are exactly what we need for paper and dataset synthesis.
Anonymous author
Full-stack DeveloperBenchmark tracking with sources keeps the hype in check.
Shekinah Tshiokufila
AI EngineerThe multimodal roadmap is clear: images today, video next.
Oketa Fred
Data ScientistMath and code performance are front-and-center instead of buried in marketing.
Zeki
Infra LeadI appreciate the self-hosting and domestic-chip discussion - it matters for deployment.
Joseph Kitheka
Startup FounderThe waitlist flow is simple and keeps our team informed.
Khatab Wedaa
Solutions ArchitectUnified API plus usage caps make budgeting predictable.
Rodrigo Aguilar
Developer AdvocateThe docs focus on real workflows - code, math, and knowledge bases.
Eric Ampire
Research EngineerReported MMLU and HumanEval gains align with what we see internally.
Roland Tubonge
CTOIt is the best balance of community signal and verified data I have seen.
Built for developers and teams
Ship faster with clean docs, transparent pricing, and production-ready tooling for the DeepSeek ecosystem. The goal is straightforward: keep legacy models affordable, expose the same API surface across text, reasoning, math, and vision, and make the V4 rollout predictable through a public waitlist and update cadence.
The product direction mirrors the PRD focus: a single unified endpoint, a clear trial period for legacy models, and a V4 access path that scales from early credits to full launch pricing. If you are evaluating for teams, the Playground is the fastest way to compare outputs, then lock in a plan once you see which model behaves best for your workload.
Simple, transparent access
Legacy models start with a 30-day free window, then 9.9 / 29.9 / 59.9 monthly tiers. V4 pricing is announced at launch.
- 30 days free access to legacy models
- Unified API surface
- Usage caps and rate limits apply
- Community support
- No SLA
- PricePlans.free.limits.limit-2
- PricePlans.free.limits.limit-3
- 10M tokens per month
- 200 images included
- 2 requests per second
- 1 API key
- Email support
- Overages billed pay-as-you-go
- 40M tokens per month
- 800 images included
- 5 requests per second
- 3 team seats
- Priority support
- Overages billed pay-as-you-go
- 120M tokens per month
- 2,500 images included
- 8 requests per second
- 5 team seats
- Priority support
- Overages billed pay-as-you-go
FAQ
Release, access, and benchmarks
Be ready for V4 without waiting
Join the waitlist for launch access, then use V3.1, R1, VL2, Janus-Pro-7B, and Math-7B today with the same API surface.