# Bagel vs OpenAI Platform

Bagel records 7,329 monthly visits with -27.5% month-over-month growth and Free pricing. OpenAI Platform records 234,678,639 monthly visits with -9.6% growth and Paid pricing.

| Metric | [Bagel](https://openaitools.app/tool/bagel) | [OpenAI Platform](https://openaitools.app/tool/openai) |
| :--- | :--- | :--- |
| Website URL | https://bagel-ai.org | https://openai.com |
| Categories | Open Source AI Models, AI Models, AI Image Generator, AI Chatbot | AI Models, AI API, Large Language Models (LLMs), AI Chatbot |
| Pricing Model | Free | Paid |
| Monthly Visits | 7,329 | 234,678,639 |
| MoM Growth Rate | -27.5% | -9.6% |
| Primary Market | United States | United States |
| Direct Visits | 2,868 | 105,101,079 |
| Review Score | 4.6 | 4.8 |
| Saved Count | 1 | 144 |
| Supported Platforms | Website | Website |

## Bagel

BAGEL is an open-source unified multimodal model released on May 20, 2025 by a research team led by Chaorui Deng, Deyao Zhu, Kunchang Li, Chenhui Gou, Feng Li and colleagues. Its goal is to deliver functionality comparable to proprietary multimodal systems such as GPT-4o and Gemini 2.0, but in an open form that anyone can fine-tune, distill and deploy. Rather than stitching a separate vision model to a separate image generator, BAGEL is natively multimodal from pre-training onward.

The model handles image and text inputs and outputs in a mixed format, so the same system can reason about a picture, hold a conversation, generate photorealistic imagery, edit an existing image, transfer style, navigate a 3D environment or predict future video frames. Architecture-wise, BAGEL adopts a Mixture-of-Transformer-Experts design with two encoders capturing pixel-level and semantic-level features, trained via a Next Group of Token Prediction objective on trillions of interleaved language, image, video and web tokens.

The project publishes benchmark comparisons against open models such as Janus-Pro-7B, Emu3-8B, TokenFlow-XL-13B and BLIP3-o-8B. BAGEL reports strong scores on understanding benchmarks like MME-P, MMBench, MMMU and MMVet, and leads the published generation table with an overall score of 0.88 across single-object, two-object, counting, color, position and color-attribute tasks. The team also documents emergent behaviour, noting that complex intelligent editing appears only after foundational understanding and generation skills are established.

**Pricing & Plans:** Free and open source. The project publishes the model for fine-tuning, distillation and deployment; there is no paid tier listed on the project page.

- **Unified understanding and generation:** A single model accepts mixed image and text inputs and produces mixed image and text outputs for reasoning, conversation and generation.
- **Intelligent image editing:** Pre-training on interleaved video clips lets BAGEL preserve identities and fine detail while performing edits that go beyond basic manipulation.
- **Style transfer and composition:** BAGEL transforms images between styles and worlds using minimal alignment data, and composes new scenes across turns.
- **Video-derived navigation:** By learning from real-world video, the model can navigate varied environments including painted and sci-fi worlds.
- **Thinking mode:** A built-in reasoning mode expands short prompts into detailed, logically consistent visual outputs.

**Strengths:** Open source and freely deployable, with no licensing fee on the project site; One architecture covers understanding, generation, editing and navigation; Strong published scores against comparable open multimodal models; Explicit thinking mode improves prompt fidelity for complex edits

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

Bagel has 7,329 monthly visits, while OpenAI Platform has 234,678,639. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Bagel has a month-over-month growth rate of -27.5%; OpenAI Platform has -9.6%.

### How does pricing compare?

Bagel: Free. Free and open source. The project publishes the model for fine-tuning, distillation and deployment; there is no paid tier listed on the project page. 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 | [MiniMax Image-01](https://openaitools.app/tool/minimax-image-01) | 5,253,734 | -13.2% | Contact for Pricing | MiniMax's open-weight model for turning prompts into images | [.md](https://openaitools.app/tool/minimax-image-01.md) |
| 6 | [Gemma Open Models by Google](https://openaitools.app/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | Freemium, Paid | Google's family of lightweight, open-weight AI models | [.md](https://openaitools.app/tool/gemma-open-models-by-google.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Tencent Hunyuan](https://openaitools.app/tool/tencent-hunyuan-large-model) | 1,485,463 | -1.2% | Contact for Pricing | Tencent's multimodal foundation-model family for text, vision, image and speech | [.md](https://openaitools.app/tool/tencent-hunyuan-large-model.md) |
| 10 | [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) |

---
Source: https://openaitools.app/compare/bagel-vs-openai

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