# DeepSeek vs Labnote

DeepSeek records 372,761,591 monthly visits with +4.3% month-over-month growth and Freemium pricing. Labnote records 676 monthly visits with -91.4% growth and Contact for Pricing pricing.

| Metric | [DeepSeek](https://openaitools.app/tool/deepseek) | [Labnote](https://openaitools.app/tool/labnote) |
| :--- | :--- | :--- |
| Website URL | https://www.deepseek.com | https://www.labnote.co |
| Categories | Large Language Models (LLMs), Open Source AI Models, AI API, AI Chatbot | AI Assistant, AI Research Tool, AI Knowledge Management, AI Documents Generator |
| Pricing Model | Freemium | Contact for Pricing |
| Monthly Visits | 372,761,591 | 676 |
| MoM Growth Rate | +4.3% | -91.4% |
| Primary Market | China | South Korea |
| Direct Visits | 291,585,405 | 584 |
| Review Score | 4.8 | 4.3 |
| Saved Count | 44 | 0 |
| Supported Platforms | Website | Website |

## DeepSeek

DeepSeek (Hangzhou DeepSeek Artificial Intelligence Co., Ltd.) is a frontier AI research organization that disrupted the global LLM market by pairing open-weight transparency with breakthrough Mixture-of-Experts (MoE) and reinforcement-learning reasoning efficiency. Following the landmark releases of DeepSeek-V3 and the peer-reviewed DeepSeek-R1 reasoning model, DeepSeek introduced the DeepSeek-V4 generation in 2026—featuring a hybrid attention architecture and a native 1-million-token context window across DeepSeek-V4-Pro (1.6T total parameters, 49B active per token) and DeepSeek-V4.1-Flash (284B total parameters, 13B active per token).

Users can interact with DeepSeek in three ways: completely free through the consumer web portal (chat.deepseek.com) and mobile apps with one-click toggles for deep thinking and live web search; via DeepSeek's hosted, OpenAI-compatible developer API; or by self-hosting DeepSeek's open-weight checkpoints (including V3, R1, Prover-V2, and distilled Qwen/Llama variants) on private infrastructure. The models excel at competitive mathematics, algorithm design, repository-level software engineering, and structured data extraction, with automatic context caching on the API that slashes repeated prompt costs by over 95%.

In late 2026, DeepSeek remains the price-performance benchmark for developers and automation workflows. While the consumer chat interface remains free without a mandatory $20/month subscription tier, the developer API transitioned in late 2026 to two primary endpoints—`deepseek-flash` and `deepseek-v4-pro`—with time-of-day pricing. Off-peak API calls cost just $0.15 per million input tokens ($0.003 on cache hits) and $0.60 per million output tokens on Flash, and $0.66 input / $1.98 output on V4-Pro, making it a fraction of the cost of comparable Western frontier models.

**Pricing & Plans:** Free web and mobile chat app at chat.deepseek.com; pay-as-you-go OpenAI-compatible API with off-peak rates at $0.15/1M input ($0.003 cache hit) and $0.60/1M output for deepseek-flash (V4.1-Flash), and $0.66/1M input ($0.022 cache hit) and $1.98/1M output for deepseek-v4-pro (peak weekday UTC hours bill at 2x).

- **DeepSeek-V4 Hybrid Attention & 1M Context:** Leverages a sparse Mixture-of-Experts architecture (49B active parameters out of 1.6T on V4-Pro) to process up to 1 million tokens with minimal latency and memory overhead.
- **Transparent Chain-of-Thought Reasoning:** Pioneered by DeepSeek-R1 and integrated into V3.2 and V4 thinking modes, exposing step-by-step self-verification for complex math, logic, and code debugging.
- **Automatic Context Caching & Off-Peak API Pricing:** Drops input token costs to $0.003/1M on Flash and $0.022/1M on V4-Pro for cache hits, with 50% lower rates during off-peak UTC hours.
- **Free Consumer Web & Mobile Assistant:** Provides free access at chat.deepseek.com and on iOS/Android with document uploads, reasoning mode, and web search without paywalling core models.
- **Open-Weight Ecosystem & Self-Hosting Freedom:** Offers open weights for DeepSeek-V3, R1, Distill variants, and Prover models on Hugging Face and GitHub so enterprises can deploy within air-gapped environments.

**Strengths:** Completely free consumer web and mobile app with deep reasoning and web search included; Ultra-low API token rates ($0.15/$0.60 on Flash, $0.66/$1.98 on V4-Pro off-peak) with up to 98% savings on cached inputs; Drop-in OpenAI API compatibility makes switching or routing between models effortless; Strong open-weight lineage allows teams to self-host or fine-tune models without vendor lock-in

**Limitations:** Hosted API and web app store data on servers in China, prompting compliance restrictions for some Western enterprises and government agencies; Peak-hour API pricing (01:00–04:00 and 06:00–10:00 UTC on weekdays) doubles per-token costs compared to off-peak rates; Lacks native voice mode, video generation, and productivity suite integrations offered by ChatGPT and Google Gemini

[Profile (Markdown)](https://openaitools.app/tool/deepseek.md)

## Labnote

Labnote Scholar is a bio and chemistry-specialised research platform rather than a general-purpose AI assistant. Its organising argument is quantitative: researchers spend a small fraction of their time actually running experiments and the large majority on data and documentation work. Labnote aims to flip that ratio by automating the structuring, retrieval and write-up stages so scientific time goes to science.

The feature set follows the research lifecycle. Experiments are captured into a structured electronic lab notebook with audit trails; AI is applied to experimental design and outcome prediction with confidence estimates to cut wasted iterations; reagents and MSDS records are managed in the same system; retrieval-augmented generation answers questions over the organisation's own papers and past reports rather than the open web; and reports are generated automatically from captured data. New researchers can query institutional memory directly, which addresses the common problem of teams repeating experiments that were already run years earlier.

Commercially, Labnote sells to organisations rather than individuals. It positions on GLP/GMP compliance, enterprise security and bio/chem domain specificity, and cites adoption across global R&D organisations. Onboarding is deliberately hands-off for the research team: a dedicated Product Specialist is assigned to handle data migration, configuration and optimisation, followed by regular reviews. Pricing is not published and is arranged per engagement, which fits enterprise procurement cycles but means individual researchers cannot simply sign up and try it.

**Pricing & Plans:** Contact for pricing. Labnote is sold as an organisation-level platform with per-company configuration and a dedicated Product Specialist; no public self-serve tiers or list prices are published.

- **Structured experimental data capture:** Capture experiments in a structured electronic lab notebook with audit-trail support, so records satisfy regulatory documentation expectations rather than living in scattered files.
- **AI experiment prediction:** The platform applies AI to experimental design and outcome prediction, reducing trial-and-error cycles and cutting down duplicated experiments across a lab.
- **Reagent and MSDS management:** Track reagents and manage MSDS documentation in the same system as the experiment records that consume them.
- **Literature RAG over internal knowledge:** Retrieval-augmented search runs against the organisation's own papers, reports and prior experiments, so answers are grounded in internal knowledge rather than the open web.
- **Automatic report generation:** Reports are assembled automatically from captured data, collapsing the documentation time that normally sits between completing an experiment and submitting results.
- **Real-time team collaboration:** Research teams work on shared records in real time, with roles, access controls and enterprise security appropriate to regulated biotech and chemical environments.

**Strengths:** Purpose-built for bio and chemistry R&D rather than adapted from a generic notes product; GLP/GMP compliance support, enterprise security and audit-traceable records suit regulated environments; AI experiment prediction targets the highest-value saving: fewer unnecessary iterations; Literature RAG is grounded in internal papers and reports, so answers reflect the organisation's own history

**Limitations:** Enterprise-only motion — no self-serve signup or published list price, so evaluation starts with a sales conversation; Interface and marketing content are primarily Korean, which may slow adoption for non-Korean-speaking research teams; Value depends on instrument and workflow integrations being in place; a half-connected lab sees less benefit; Not aimed at non-clinical academic labs or individual researchers — it is priced and packaged for organisations

[Profile (Markdown)](https://openaitools.app/tool/labnote.md)

## Frequently Asked Questions

### How do DeepSeek and Labnote compare in monthly traffic?

DeepSeek has 372,761,591 monthly visits, while Labnote has 676. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

DeepSeek has a month-over-month growth rate of +4.3%; Labnote has -91.4%.

### How does pricing compare?

DeepSeek: Freemium. Free web and mobile chat app at chat.deepseek.com; pay-as-you-go OpenAI-compatible API with off-peak rates at $0.15/1M input ($0.003 cache hit) and $0.60/1M output for deepseek-flash (V4.1-Flash), and $0.66/1M input ($0.022 cache hit) and $1.98/1M output for deepseek-v4-pro (peak weekday UTC hours bill at 2x). Labnote: Contact for Pricing. Contact for pricing. Labnote is sold as an organisation-level platform with per-company configuration and a dedicated Product Specialist; no public self-serve tiers or list prices are published.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [ChatGPT](https://openaitools.app/tool/chatgpt-4) | 6,048,022,723 | +2.2% | Freemium | Provides stronger multi-modal reasoning and agentic tools, but lacks DeepSeek's ultra-low-cost API pricing. | [.md](https://openaitools.app/tool/chatgpt-4.md) |
| 2 | [Google Gemini](https://openaitools.app/tool/gemini-gemini-advanced) | 2,637,398,242 | -0.1% | Freemium | Offers an enormous context window and deep Google ecosystem integration, but feels less specialized for pure reasoning tasks. | [.md](https://openaitools.app/tool/gemini-gemini-advanced.md) |
| 3 | [Claude](https://openaitools.app/tool/claude-2) | 1,253,439,413 | +23.8% | Freemium | Delivers superior long-form coding artifacts and nuanced writing, but lacks DeepSeek's specialized open-weight reasoning models. | [.md](https://openaitools.app/tool/claude-2.md) |
| 4 | [Grok](https://openaitools.app/tool/grok) | 203,846,050 | -0.8% | Freemium | Features real-time X social data integration, but is less cost-effective for dedicated developer coding workflows. | [.md](https://openaitools.app/tool/grok.md) |
| 5 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 6 | [Perplexity](https://openaitools.app/tool/perplexity-ai) | 88,310,223 | -3.7% | Freemium | Real-time AI answer engine and research workspace combining live web citations with frontier reasoning models. | [.md](https://openaitools.app/tool/perplexity-ai.md) |
| 7 | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | 35,101,353 | -6.2% | Freemium | Provides comparable open-weight foundation models and multilingual performance, but requires self-hosting or third-party inference setup. | [.md](https://openaitools.app/tool/qwen-4.md) |
| 8 | [Cursor](https://openaitools.app/tool/cursor) | 23,297,751 | +8.4% | Freemium | The AI coding agent for building ambitious software | [.md](https://openaitools.app/tool/cursor.md) |
| 9 | [Kimi AI](https://openaitools.app/tool/kimi-chat) | 19,632,261 | -23.4% | Free | Excels at ultra-long document analysis and research, but lacks the same level of open-weight developer community support. | [.md](https://openaitools.app/tool/kimi-chat.md) |
| 10 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Enables running open-source models locally on consumer hardware, but lacks DeepSeek's cloud-scale hosted reasoning power. | [.md](https://openaitools.app/tool/ollama.md) |

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Source: https://openaitools.app/compare/deepseek-vs-labnote

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