# LabFig vs OpenAI Platform

LabFig records 4,976 monthly visits with +44.9% month-over-month growth and Freemium pricing. OpenAI Platform records 234,678,639 monthly visits with -9.6% growth and Paid pricing.

| Metric | [LabFig](https://openaitools.app/tool/labfig) | [OpenAI Platform](https://openaitools.app/tool/openai) |
| :--- | :--- | :--- |
| Website URL | https://labfig.com | https://openai.com |
| Categories | AI Image Generator, Image to Image, Text to Image | AI Models, AI API, Large Language Models (LLMs), AI Chatbot |
| Pricing Model | Freemium | Paid |
| Monthly Visits | 4,976 | 234,678,639 |
| MoM Growth Rate | +44.9% | -9.6% |
| Primary Market | United States | United States |
| Direct Visits | 1,627 | 105,101,079 |
| Review Score | 4.2 | 4.8 |
| Saved Count | 0 | 144 |
| Supported Platforms | Website | Website |

## LabFig

LabFig targets a very specific pain point in academic work: producing clean, consistent scientific figures without a design background. Instead of learning vector software or paying a designer, researchers describe a figure in words, drop in a paper, upload a sketch, or take a photo of a whiteboard, and the tool returns a structured draft with panels, labels, and arrows laid out. It supports journal-oriented aesthetics, with styles modelled on Nature, Cell, or IEEE conventions so figures in the same manuscript look like a set.

What sets LabFig apart from generic image generators is the editing layer. Figures are vector-first: text, arrows, shapes, and colours remain editable after generation, and individual regions can be replaced or regenerated with a short prompt through a feature called Vector Canvas. Exports include SVG and PDF alongside PNG, which matters when a submission template expects resizable artwork. There is also a Figure Enhancer path for cleaning up an existing figure's colour and line weights.

The workbench runs in seven modes covering text, image, PDF, sketch, reference, photo, and enhancer inputs, with credits consumed per generation. Pricing is credit-based across Starter, Standard, and Premium tiers, and academic discounts are available for verified students and educators. LabFig is explicit that AI-generated drafts should be reviewed by a scientist before publication, which is a sensible framing for a tool aimed at manuscript work.

**Pricing & Plans:** Credit-based subscription plans: a Starter tier aimed at occasional figure work, a Standard tier for active PhD students and postdocs, and a Premium tier for high-throughput labs. Annual billing reduces the monthly rate, and verified students and educators receive a discount. Monthly list prices run roughly from about $29.9 to about $149.9 before discounts.

- **Six-plus input modes:** Generate from text descriptions, hand sketches, reference figures, research PDFs, or lab photos.
- **Vector Canvas editing:** Labels, arrows, shapes, and colours stay editable, and single regions can be regenerated with a prompt.
- **Journal-grade styles:** Match the visual conventions of Nature, Cell, or IEEE with one-click styles, or keep a consistent set across a paper.
- **Resizable vector export:** Export SVG and PDF for submissions plus 300 dpi PNG, so figures drop into templates without rework.
- **Figure Enhancer:** Improve the colour balance and line weights of a figure you already have instead of starting over.

**Strengths:** Works from the inputs researchers actually have, from PDFs and sketches to whiteboard photos; Figures stay vector-editable after generation, unlike one-shot image generators; Journal-oriented styles help keep every figure in a manuscript visually consistent; Academic discount available for verified students and educators

[Profile (Markdown)](https://openaitools.app/tool/labfig.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 LabFig and OpenAI Platform compare in monthly traffic?

LabFig has 4,976 monthly visits, while OpenAI Platform has 234,678,639. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

LabFig has a month-over-month growth rate of +44.9%; OpenAI Platform has -9.6%.

### How does pricing compare?

LabFig: Freemium. Credit-based subscription plans: a Starter tier aimed at occasional figure work, a Standard tier for active PhD students and postdocs, and a Premium tier for high-throughput labs. Annual billing reduces the monthly rate, and verified students and educators receive a discount. Monthly list prices run roughly from about $29.9 to about $149.9 before discounts. 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 | [Rendair AI](https://openaitools.app/tool/rendair-ai-platform) | 496,201 | +5.7% | Contact for Pricing | The AI workspace that turns architectural sketches and 3D models into client-ready visuals | [.md](https://openaitools.app/tool/rendair-ai-platform.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/labfig-vs-openai

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