DeepSeek has 1 model in The AI Leaderboard directory: DeepSeek V4. This provider hub compares their verified availability, licensing, context windows, pricing references and intended uses, with direct links to every model guide.

Quick answer: DeepSeek V4 is the first DeepSeek model to evaluate for its documented fit: low-cost long-context agents, coding, flexible reasoning and self-hosting experiments. The dedicated guide contains the full specification, evidence and deployment caveats.

DeepSeek model lineup at a glance

Metric

Current directory value

Models covered

1

Currently ranked

None in the current top eight

Open-weight models

1

Restricted models

0

Legacy or migration references

0

Highest-ranked model

No current Overall rank assigned

Last verified

September 2, 2026

Complete DeepSeek model directory

Model names in this table link directly to their complete guides. Status and pricing can change, so confirm the active endpoint and provider terms before procurement or migration.

Model

Status

License

Context

Best fit

DeepSeek V4

Available; V4 Pro and V4 Flash

Open weights for the preview family; API variants available

1 million tokens

low-cost long-context agents, coding, flexible reasoning and self-hosting experiments

How the DeepSeek models differ

Model

Directory role

Modalities

Maximum output

Access

DeepSeek V4

Open weights

Text input and text output; an experimental Flash Vision variant accepts images

384,000 tokens maximum

DeepSeek app, web, OpenAI-compatible API, Anthropic-compatible API and released weights

The labels above describe access and lifecycle, not a hidden capability ranking. Only models with a validated Overall record receive a rank on this site. Other guides remain unranked until comparable evidence is available.

DeepSeek model pricing

Model

Pricing reference

Cost caveat

DeepSeek V4

V4 Pro peak rates: $0.044 cached input, $1.32 uncached input and $3.96 output per million tokens; off-peak is half

Self-hosting still incurs infrastructure and operations costs

Token price is not cost per accepted result. Measure retries, tool calls, latency, infrastructure and reviewer time on the same task set.

Which DeepSeek model should you choose?

Requirement

Starting point

Why

Highest current rank

DeepSeek V4

No ranked model; start with the documented fit and test directly

Open weights or self-hosting

DeepSeek V4

Review the exact license, checkpoint and hardware needs

Restricted specialist work

No restricted model in this provider directory

Use generally available models and least-privilege controls

Migration or reproduction

DeepSeek V4

Compare current versions using pinned snapshots

Lowest operational cost

Measure two or three eligible models

Headline token prices omit retries, tools, caching and human review

DeepSeek models, explained

DeepSeek V4

DeepSeek V4 was released April 24, 2026 preview; V4 Pro GA August 13, 2026. It is listed as available; v4 pro and v4 flash with open weights for the preview family; api variants available. The documented context window is 1 million tokens, and the maximum output is 384,000 tokens maximum.

  • Best fit: low-cost long-context agents, coding, flexible reasoning and self-hosting experiments.
  • Modalities: Text input and text output; an experimental Flash Vision variant accepts images.
  • Access: DeepSeek app, web, OpenAI-compatible API, Anthropic-compatible API and released weights.
  • Pricing reference: V4 Pro peak rates: $0.044 cached input, $1.32 uncached input and $3.96 output per million tokens; off-peak is half.

Read the complete DeepSeek V4 guide for benchmarks, limitations, official sources and an evaluation framework.

How to evaluate DeepSeek models

Shortlist the DeepSeek models that meet your access, licensing and modality requirements. Freeze 20 to 50 representative tasks, then give each candidate the same prompts, tools, context, reasoning budget and retry limits. Record the exact model identifier because provider aliases can change.

Measure

Record

Decision use

Task completion

Pass rate and rubric score

Establish whether the model meets the acceptance threshold

Reliability

Repeated-run variance and recovery behavior

Avoid choosing from one lucky result

Quality

Factuality, instruction following and reviewer acceptance

Separate polished output from correct output

Tool use

Wrong calls, retries, permission errors and unsafe actions

Evaluate the model and agent harness together

Efficiency

Wall time, tokens, caching, tools and review labor

Calculate cost per accepted result

Governance

Retention, training, regional processing and audit logs

Confirm the deployment fits policy requirements

Availability, versions and lifecycle

DeepSeek may expose different snapshots, effort settings, products and partner integrations under similar labels. Treat every model name as incomplete without an exact endpoint or checkpoint. Re-run regression tests after any model, system prompt, retrieval, tool or permission change.

  • Available means a documented access route exists, not that every region or account has access.
  • Preview models can change behavior, price or retirement dates before general availability.
  • Open weights require an exact license and checkpoint review; “open” does not guarantee open training data or low operating cost.
  • Restricted models require separate eligibility, safeguards and data-handling review.
  • Legacy models remain useful for migration and reproduction but should not be the default for a new deployment.

Sources and update policy

Official DeepSeek model documentation is the provider-level starting point. Each linked model guide cites its own first-party launch page, model card, pricing reference and safety documentation.

Compare this provider with the complete Best AI Models directory.

Last verified September 2, 2026. The hub should be updated when the provider launches, retires, renames or reprices a model, changes context or output limits, alters licensing, or modifies regional availability.

Frequently asked questions

How many DeepSeek models are covered?

This hub covers 1: DeepSeek V4. Every model has a dedicated guide linked from the directory table and profile sections.

What is the best DeepSeek model?

DeepSeek does not have a model with a current Overall rank on this page. Start with DeepSeek V4 for its documented fit, then validate it against alternatives using the same task set.

Does DeepSeek offer open weights?

Yes. The directory identifies DeepSeek V4 as open-weight options. Review the exact license, downloadable artifact and serving requirements before deployment.

How current is the pricing?

Pricing references were verified September 2, 2026 from first-party documentation summarized in each model guide. Always recheck the provider before budgeting because cache, batch, long-context, tool and regional rates can change.

Should every DeepSeek model be tested?

No. Remove models that fail access, license, modality, context, latency or governance requirements first. Test the smallest credible shortlist on representative work.