DeepSeek
Featured tool What is DeepSeek?
DeepSeek is an AI company offering a consumer chat service, a developer API, and released model weights. It is worth considering when you want capable Chinese and English output, reasoning or coding help, and a lower token bill than many premium hosted models. Its product surfaces are separate: the chat website and mobile app are for interactive use, the API is metered, and downloading weights creates an infrastructure project rather than a free hosted service.
That distinction matters. “Open weight” does not mean every deployment is easy, private, or costless. Large models need enough accelerator memory, a serving stack, monitoring, and a license review. The hosted API removes that operational work, but adds normal vendor, availability, data-handling, and rate-limit considerations.
What DeepSeek is useful for
- Reasoning and coding: break down algorithms, explain unfamiliar code, draft tests, review patches, and work through structured problems.
- Cost-aware applications: prototype chat, extraction, classification, or agent steps where token volume matters and an OpenAI-compatible API is useful.
- Chinese and multilingual workflows: evaluate it on the language mix, terminology, and documents your users actually have, rather than relying only on an aggregate benchmark.
- Research and controlled deployment: assess released V3 or R1 weights when a team can operate the required hardware and wants more control over serving.
API pricing and free chat access
DeepSeek’s official pricing page lists prices per 1 million tokens. Checked in September 2026, deepseek-flash, which serves DeepSeek-V4.1-Flash, costs $0.003 cached-input, $0.15 uncached-input, and $0.60 output tokens off peak; peak rates are $0.006, $0.30, and $1.20. deepseek-v4-pro, listed as DeepSeek-V4-Pro-0813, is $0.022 cached-input, $0.66 uncached-input, and $1.98 output off peak; peak rates are $0.044, $1.32, and $3.96. The documentation defines peak as 01:00-04:00 and 06:00-10:00 UTC on weekdays, excluding Chinese public holidays. Prices can change, so confirm the official pricing page before forecasting spend.
For individuals, DeepSeek’s official App announcement says the app is free to use, with no ads or in-app purchases; the official chat site is the browser counterpart. Treat that as a consumer-product statement, not an API allowance or an uptime guarantee. Access can still require an account, and available features, capacity, regions, and usage controls may change. The API instead deducts usage from a topped-up or granted balance.
Open models and licenses
The official GitHub projects make the licensing distinction explicit. DeepSeek-V3 publishes V3-Base and V3 weights: the repository code is MIT, while the Base and Chat models use DeepSeek’s separate Model License and support commercial use. That model license includes use-based restrictions, so it is more accurate to call the weights openly released or open-weight than to assume an unrestricted permissive model license.
DeepSeek-R1 publishes R1-Zero, R1, and distilled 1.5B, 7B, 8B, 14B, 32B, and 70B checkpoints. Its repository states that its code and weights are MIT and that commercial use, modification, derivatives, and distillation are allowed. However, the Qwen-based distills originate under Apache 2.0, while the Llama-based 8B and 70B distills retain their respective Llama licenses. Check the exact checkpoint before redistributing or building a commercial service.
Limits and practical trade-offs
DeepSeek is not automatically the best choice because it is inexpensive. Compare it with Claude, ChatGPT, and Kimi on your own prompts. At a lower token price, DeepSeek is a credible option for high-volume reasoning, coding, extraction, and bilingual experiments. Higher-priced alternatives may be preferable when a team values a particular tool ecosystem, enterprise controls, established support arrangements, or better results on its specific long-document and tool-use tests.
Run a small evaluation set before switching. Include a hard task, an answer with known ground truth, a long-context request, JSON or tool-call output, and a safety-sensitive refusal. Record token cost, latency, retry rate, malformed structured output, and human correction time. For code, request a plan and tests before a patch; keep deployment behind CI and human review. Self-hosting should start with a supported, bounded configuration and concurrency limits rather than a full production commitment.
Who should use DeepSeek?
DeepSeek suits developers and product teams that can benchmark models, have meaningful token volume, and want an economical OpenAI-compatible API. It also fits Chinese-first or bilingual teams, researchers studying released weights, and technically capable organizations that have a real reason to self-host. It is less suitable as an unreviewed source of truth, a substitute for security review, or a “free” solution for teams that cannot carry GPU and operations costs. Start in the free chat interface for task fit, then test the paid API with a capped budget and representative traffic.