# DeepSeek vs Mindgard

DeepSeek records 372,761,591 monthly visits with +4.3% month-over-month growth and Freemium pricing. Mindgard records 153,455 monthly visits with +1.3% growth and Contact for Pricing pricing.

| Metric | [DeepSeek](https://openaitools.app/tool/deepseek) | [Mindgard](https://openaitools.app/tool/mindgard) |
| :--- | :--- | :--- |
| Website URL | https://www.deepseek.com | https://mindgard.ai |
| Categories | Large Language Models (LLMs), Open Source AI Models, AI API, AI Chatbot | AI Testing, Large Language Models (LLMs), AI Developer Tools |
| Pricing Model | Freemium | Contact for Pricing |
| Monthly Visits | 372,761,591 | 153,455 |
| MoM Growth Rate | +4.3% | +1.3% |
| Primary Market | China | United States |
| Direct Visits | 291,585,405 | 21,556 |
| 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)

## Mindgard

Mindgard is an AI security platform that approaches protecting AI systems the way an attacker would. Instead of starting with a checklist of prompts, it begins with agent-native reconnaissance: profiling the models, agents, tools, instructions, permissions and behaviours that make up an AI system, so it can identify the attack paths most likely to cause real damage. That reconnaissance is fed by vulnerability intelligence drawn from the company's own published disclosures.

The platform spans the full security loop. Recon surfaces what an AI deployment can actually do; red teaming continuously tests agents and systems against evolving attacks; assessment validates which weaknesses are genuinely exploitable and quantifies their impact; runtime protection and remediation guidance help teams close gaps and verify that defences hold as the system changes. This matters because AI behaviour shifts with every model update, prompt change or new tool integration, which makes one-off testing insufficient.

Mindgard originated from more than a decade of AI security research at Lancaster University and says its technology has been behind 175+ publicly disclosed vulnerabilities in prominent AI systems. It is designed to slot into existing engineering workflows through APIs, CI/CD pipelines and Burp Suite integration, so AI security assessment can run before deployment and continuously in production rather than as a periodic external exercise.

**Pricing & Plans:** Mindgard does not publish public pricing. Plans are quoted based on scope, deployment model and enterprise requirements. Contact the team for a demo and custom quote.

- **Attacker-style AI reconnaissance:** Agent-native reconnaissance maps models, agents, tools, instructions, permissions and behaviours the way an attacker would before launching attacks.
- **Continuous AI red teaming:** Continuous, adaptive testing of AI agents and systems against evolving attack techniques, rather than one-off audits.
- **Proprietary vulnerability intelligence:** Findings are backed by a knowledge base built from more than 175 publicly disclosed AI vulnerabilities across major AI systems.
- **Remediation and runtime protection:** Runtime protections and remediation guidance help close defensive gaps and verify that fixes actually hold.
- **Governance and compliance support:** Risk reduction, evidence and reporting aligned to AI policies and governance requirements, keeping AI compliant as it changes.

**Strengths:** Attacker-led methodology focuses on provably exploitable risk rather than generic prompt noise; Backed by a decade of Lancaster University AI security research and 175+ disclosures; Covers recon, red teaming, assessment, remediation and runtime protection in one platform; Integrates with CI/CD, APIs and Burp Suite for continuous assurance

**Limitations:** Requires a sales conversation; no transparent public pricing; Some capabilities overlap with other AI security vendors, so evaluation takes care; Fully realising value assumes integration into CI/CD and security workflows

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

## Frequently Asked Questions

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

DeepSeek has 372,761,591 monthly visits, while Mindgard has 153,455. 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%; Mindgard has +1.3%.

### 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). Mindgard: Contact for Pricing. Mindgard does not publish public pricing. Plans are quoted based on scope, deployment model and enterprise requirements. Contact the team for a demo and custom quote.

## 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 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) |

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

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