# Markup: Document Annotation vs OpenAI Platform

Markup: Document Annotation records 263 monthly visits with -17.8% month-over-month growth and Free pricing. OpenAI Platform records 234,678,639 monthly visits with -9.6% growth and Paid pricing.

| Metric | [Markup: Document Annotation](https://openaitools.app/tool/markup-document-annotation) | [OpenAI Platform](https://openaitools.app/tool/openai) |
| :--- | :--- | :--- |
| Website URL | https://www.getmarkup.com | https://openai.com |
| Categories | AI Developer Tools, AI Document Extraction, Large Language Models (LLMs) | AI Models, AI API, Large Language Models (LLMs), AI Chatbot |
| Pricing Model | Free | Paid |
| Monthly Visits | 263 | 234,678,639 |
| MoM Growth Rate | -17.8% | -9.6% |
| Primary Market | Türkiye | United States |
| Direct Visits | 109 | 105,101,079 |
| Review Score | 4 | 4.8 |
| Saved Count | 0 | 144 |
| Supported Platforms | Website | Website |

## Markup: Document Annotation

Markup is an annotation tool focused on one core job: turning free-form text into structured datasets that are ready for NLP and machine learning. Instead of wrangling spreadsheets, you work directly with the document and mark up the pieces that matter, whether that is named entities, fields, relationships or categories. The result is a consistent, machine-readable dataset you can export into a training or evaluation pipeline.

It is aimed at developers, data scientists and research teams who need to build labelled corpora quickly. Rather than forcing everything through a heavyweight enterprise platform, Markup keeps the interface lightweight and task-focused so annotators can move fast, and it leans on AI to propose likely labels and extractions that a human then confirms. That combination helps teams bootstrap datasets far faster than purely manual labelling while keeping a human in the loop for accuracy.

Markup runs in the browser, with an interactive demo available on the site and a sign-up path to create projects. It markets itself as a free, open annotation tool, making it accessible for small teams, prototypes and research work where budget and setup time are limited.

**Pricing & Plans:** Free to use, with an interactive demo on the site and a sign-up flow to start annotating. No paid tiers are advertised.

- **Text to structured data:** Mark up documents and free text to extract names, entities, relationships and fields into clean tabular or JSON output.
- **Designed for NLP and ML:** Built for NLP and ML workflows, so exported datasets plug into model training pipelines without heavy reformatting.
- **AI-assisted annotation:** AI assistance proposes labels and extractions to reduce repetitive manual work, while you keep final control over correctness.
- **Browser-based demo:** An interactive demo lets you test the annotation flow before committing to a full project setup.

**Strengths:** Purpose-built for converting free text into structured, model-ready data; AI assistance speeds up annotation while leaving final control to the human; Simple, task-focused browser interface with an interactive demo; Free and approachable for prototypes, research and small teams

**Limitations:** As an early-stage tool, documentation and community support are lighter than mature annotation suites; Automatic AI extraction still needs human review to confirm labels are correct; Requires JavaScript and a browser session, with no heavy offline or desktop workflow; The interface is designed for focused annotation tasks rather than full project management

[Profile (Markdown)](https://openaitools.app/tool/markup-document-annotation.md)

## OpenAI Platform

While ChatGPT serves end users, openai.com and the OpenAI Developer Platform (developers.openai.com) provide the foundational API, SDKs, and enterprise infrastructure powering thousands of production AI applications worldwide. In late 2026, OpenAI's API catalog is anchored by the GPT-6 and GPT-6.1 model suite—all featuring a 1.05-million-token context window and up to 128K output tokens. The lineup spans GPT-6 Astra for frontier reasoning and mission-critical research, GPT-6.1 Sol for near-Astra intelligence at one-fifth the price, GPT-6.1 Terra for fast visual reasoning and computer use, and GPT-6 Luna for ultra-high-volume, low-latency tasks, alongside specialized models like `gpt-5.3-codex` and `gpt-6-astra-law`.

The OpenAI Platform has evolved well beyond basic chat completion endpoints. Through the unified `v1/responses` API, developers can orchestrate stateful multi-step agents equipped with built-in server-side tools—including live web search, vector file search, code interpreter sandboxes, and GUI computer use—without stitching together external orchestration frameworks. Every flagship model supports configurable reasoning effort (`none`, `low`, `medium`, `high`, `xhigh`, and `max`), strict JSON schema Structured Outputs, and multimodal image/audio inputs, while `gpt-live-1` powers per-second billed speech-to-speech voice agents.

OpenAI bills API usage on a transparent consumption model scaled across usage tiers (Build, Launch, and Grow, scaling up to 40M+ tokens per minute). In 2026, aggressive price cuts on the 6.x generation dropped entry-level intelligence on GPT-6 Luna to $0.10 per million input tokens and $0.50 per million output tokens, while GPT-6.1 Sol runs at $2/$10 and flagship GPT-6 Astra sits at $10/$50. Engineering teams can cut spend by 90% on repeated context using automatic Prompt Caching, save 50% on asynchronous workloads via the Batch API, and enforce regional data residency with a 10% compliance uplift.

**Pricing & Plans:** Usage-based pay-per-token API billing: GPT-6 Astra at $10/1M input and $50/1M output tokens; GPT-6.1 Sol at $2/1M input and $10/1M output; GPT-6.1 Terra at $1/1M input and $5/1M output; GPT-6 Luna at $0.10/1M input and $0.50/1M output; GPT-Live-1 voice at $0.05/minute; 90% discount on cached inputs and 50% off via Batch API.

- **GPT-6 & GPT-6.1 Model Lineup with 1.05M Context:** Spanning GPT-6 Astra ($10/$50 per MTok), GPT-6.1 Sol ($2/$10), GPT-6.1 Terra ($1/$5), and GPT-6 Luna ($0.10/$0.50), all with a 1,050,000-token context window and 128K max output.
- **Configurable Reasoning Effort Controls:** Tune thinking token budgets per API request across six granularity levels (`none`, `low`, `medium`, `high`, `xhigh`, `max`) to balance latency, accuracy, and cost.
- **Responses API & Native Computer Use Tools:** Combine model inference with hosted web search, file search, function calling, and autonomous GUI computer-use actions in a single stateful API call.
- **GPT-Live-1 Realtime Voice API:** Build ultra-low-latency multimodal voice agents billed per second ($0.05/minute) without rounding up to whole minutes.
- **90% Prompt Caching Discount & Batch API:** Cached input tokens bill at just 10% of standard input rates, while asynchronous 24-hour Batch API jobs cut both input and output token costs by 50%.

**Strengths:** 100-fold cost flexibility from GPT-6 Luna ($0.10/$0.50 per 1M tokens) up to frontier GPT-6 Astra ($10/$50 per 1M tokens); Unified 1.05M-token context window and 128K output limit across the entire flagship GPT-6 and GPT-6.1 family; 90% discount on cached input tokens and 50% Batch API discount dramatically reduce production inference bills; Industry-standard SDKs, Structured Outputs, and built-in Responses API tools minimize boilerplate agent code

**Limitations:** Long-context requests exceeding the standard window threshold trigger roughly 2x higher per-token billing rates; Flagship GPT-6 Astra ($10 input / $50 output per 1M tokens) is significantly more expensive than Claude Opus 5.5 ($4/$20) and Grok 4.7 ($2/$6); Regional data residency endpoints incur a 10% price uplift on models released after March 2026

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

## Frequently Asked Questions

### How do Markup: Document Annotation and OpenAI Platform compare in monthly traffic?

Markup: Document Annotation has 263 monthly visits, while OpenAI Platform has 234,678,639. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Markup: Document Annotation has a month-over-month growth rate of -17.8%; OpenAI Platform has -9.6%.

### How does pricing compare?

Markup: Document Annotation: Free. Free to use, with an interactive demo on the site and a sign-up flow to start annotating. No paid tiers are advertised. OpenAI Platform: Paid. Usage-based pay-per-token API billing: GPT-6 Astra at $10/1M input and $50/1M output tokens; GPT-6.1 Sol at $2/1M input and $10/1M output; GPT-6.1 Terra at $1/1M input and $5/1M output; GPT-6 Luna at $0.10/1M input and $0.50/1M output; GPT-Live-1 voice at $0.05/minute; 90% discount on cached inputs and 50% off via Batch API.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Provides direct API access to Google's Gemini models with generous free prototyping tiers, but lacks OpenAI's ecosystem breadth. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 2 | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | 35,101,353 | -6.2% | Freemium | Alibaba Cloud's 4th-generation multimodal AI assistant and foundation model lineup (Qwen4-Max, Qwen4-Plus, Qwen4-Flash & open-weight Qwen4-27B) with 1M context. | [.md](https://openaitools.app/tool/qwen-4.md) |
| 3 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Unifies hundreds of third-party models under a single API key, offering greater model choice than OpenAI's curated catalog. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 4 | [BigModel](https://openaitools.app/tool/bigmodel) | 5,700,686 | -17% | Freemium | Provides developer APIs for Zhipu AI's proprietary GLM models, serving as an alternative enterprise foundation model stack. | [.md](https://openaitools.app/tool/bigmodel.md) |
| 5 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Optimized for lightning-fast serverless execution of generative media and image models, rather than general text LLMs. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 6 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Specializes in high-performance serverless inference and dedicated GPU clusters for open-source models, bypassing closed commercial restrictions. | [.md](https://openaitools.app/tool/together-ai.md) |
| 7 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Focuses heavily on running and fine-tuning open-source vision and language models via simple APIs, unlike OpenAI's hosted closed models. | [.md](https://openaitools.app/tool/replicate-ai.md) |
| 8 | [Atlas Cloud](https://openaitools.app/tool/atlas-cloud) | 777,031 | -16.4% | Paid | One OpenAI-compatible API for 500+ image, video, audio, and LLM models | [.md](https://openaitools.app/tool/atlas-cloud.md) |
| 9 | [Appen](https://openaitools.app/tool/appen-com) | 665,840 | +0.2% | Contact for Pricing | Human-validated training data and evaluation services for frontier AI models | [.md](https://openaitools.app/tool/appen-com.md) |
| 10 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Delivers ultra-low-cost serverless inference for open-weight models, though with fewer enterprise orchestration tools than OpenAI. | [.md](https://openaitools.app/tool/deep-infra.md) |

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Source: https://openaitools.app/compare/markup-document-annotation-vs-openai

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