# DeepSeek vs Dilog

DeepSeek records 372,761,591 monthly visits with +4.3% month-over-month growth and Freemium pricing. Dilog records 341 monthly visits with 0% growth and Free Trial, Paid, Contact for Pricing pricing.

| Metric | [DeepSeek](https://openaitools.app/tool/deepseek) | [Dilog](https://openaitools.app/tool/dilog) |
| :--- | :--- | :--- |
| Website URL | https://www.deepseek.com | https://dilog.ai |
| Categories | Large Language Models (LLMs), Open Source AI Models, AI API, AI Chatbot | AI Research Tool, AI Marketing, AI Predictions |
| Pricing Model | Freemium | Free Trial, Paid, Contact for Pricing |
| Monthly Visits | 372,761,591 | 341 |
| MoM Growth Rate | +4.3% | 0% |
| Primary Market | China | India |
| Direct Visits | 291,585,405 | 122 |
| Review Score | 4.8 | 4.1 |
| 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)

## Dilog

Dilog 是一个客户模拟平台，而且它从真人开始。它不做样本问卷，而是与你的真实客户进行 2～3 小时的深度访谈，再把这些对话转化为它所说的「匿名反思画像」（ARP）——按照这些具体个人的思维方式、情感反应与决策逻辑构建的数字版本。结果就是一个你的整个团队随时可以提问的私密面板，用来测试文案、营销活动、设计方案与产品创意，几分钟就能拿到答案，而不是等上几周。

针对「为什么不直接用通用大模型提问」，Dilog 的核心论点是保真度。原始 LLM 会回归统计均值：它是所有人的平均，因而不代表任何具体的人。Dilog 的画像是从数百小时的长访谈中构建的，因而保留了深度、矛盾、非理性的品牌忠诚，以及只有在对话中才会暴露的意外底线。Dilog 公布与真人直接回答的匹配度约为 86%，并每季度与面板背后的真人重新校准，因此这项资产会不断复利累积，而不像一次性研究那样到期失效。

价格覆盖个人到企业。个人方案为每月 50 澳元约 7 次对话（350 积分），Researcher 75 澳元，Pro 125 澳元；另有从 12 澳元起含 24 积分的按量付费选项，并提供 14 天免费试用。组织方案包含基于你自己客户访谈定制的面板——构建周期 6～12 周、单独议价——起步为 Team 每月 1,000 澳元（不含 GST）、Growth 3,000 澳元、Enterprise 5,000 澳元，均含不限人数团队成员与滚动三个月积分余额。

**Pricing & Plans:** 提供免费试用，并有订阅与按量付费两种模式。个人方案：Starter 每月 50 澳元（350 积分，约 7 次对话）、Researcher 75 澳元、Pro 125 澳元。按量付费 12 澳元起含 24 积分。组织方案起步为每月 1,000 澳元（不含 GST，Team，15,000 积分）、Growth 3,000 澳元、Enterprise 5,000 澳元，定制面板的搭建费用单独议价。

- **基于访谈的画像:** 面板由与真实客户的 2～3 小时访谈构建而成，因此每个回答都能追溯到真人的原话，而非统计平均值。
- **7×24 随取随用的洞察:** 可以在早上 9 点开董事会前、前一晚 11 点提问。无需等待招募、排期或激励发放。
- **给出决策动因，而非只有答案:** 不仅看到客户选哪个，还能看到背后的动机、犹豫与决策触发点。
- **季度重新校准:** 每季度都会重新访谈面板背后的真人，画像因此持续演化，而不像一次性研究那样过期作废。
- **默认隐私与安全:** 默认匿名化，交互仅限本组织可见，提交的问题永不用于训练模型。

**Strengths:** 回答可追溯到真实访谈证据，而不是合成推测; 彻底省去招募与排期环节，决策前一夜也能提问; 能捕捉选择背后的原因，包括非理性忠诚与意外底线; 面板每季度重新访谈而持续改进，而非一次性研究后失效

**Limitations:** 组织级面板需要 6～12 周的构建周期才能上线; 价格以澳元计价，定位偏向常年做调研的团队; 个人通用面板的语境针对性弱于企业定制面板

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

## Frequently Asked Questions

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

DeepSeek has 372,761,591 monthly visits, while Dilog has 341. 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%; Dilog has 0%.

### 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). Dilog: Free Trial, Paid, Contact for Pricing. 提供免费试用，并有订阅与按量付费两种模式。个人方案：Starter 每月 50 澳元（350 积分，约 7 次对话）、Researcher 75 澳元、Pro 125 澳元。按量付费 12 澳元起含 24 积分。组织方案起步为每月 1,000 澳元（不含 GST，Team，15,000 积分）、Growth 3,000 澳元、Enterprise 5,000 澳元，定制面板的搭建费用单独议价。

## 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 | [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) |
| 6 | [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) |
| 7 | [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) |
| 8 | [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) |
| 9 | [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) |
| 10 | [Branded](https://openaitools.app/tool/gobranded-com) | 3,704,728 | +6.6% | Contact for Pricing | Targeted research audiences with AI-verified data quality | [.md](https://openaitools.app/tool/gobranded-com.md) |

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

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)
