OpenAI

APIs and tools for building AI products

5.0•885 reviews•

38K followers

APIs and tools for building AI products

5.0•885 reviews•

38K followers

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Foundation Models

The most powerful platform for building AI products. Build and scale AI experiences powered by industry-leading models and tools.

OpenAI Reviews

The community submitted 885 reviews to tell us what they like about OpenAI, what OpenAI can do better, and more.

5.0

Based on 885 reviews

Review OpenAI?

Reviewers mostly see OpenAI as a practical, everyday tool that is strong at writing, coding, research, brainstorming, and structured tasks. Users praise its speed, ease of use, and broad capabilities, while founders building on it say it is especially reliable for instruction following, tool calling, structured outputs, and fast prototyping; makers of Wispr Flow, Lovable, and TestMu AI highlight quick testing and low-latency work. The main complaints are generic or inaccurate answers, limited context or memory, pricing, usage limits, and frequent model updates.

+889

Summarized with AI

Pros

AI API (42)

fast performance (28)

AI integration ease (22)

AI model variety (20)

AI productivity boost (20)

AI innovation (19)

AI text generation (16)

AI creativity enhancement (14)

AI developer experience (12)

AI natural language processing (11)

Cons

AI accuracy issues (9)

AI pricing (3)

AI environmental impact (2)

Pros

Cons

Reviews

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Most Informative

Founder Reviews (857)

Other Reviews (28)

•1 review

What's great

fast performance (28)AI text generation (16)AI API (42)

The quality jump is real — outputs feel more intent-aware and less like prompt guessing
• Speed + reliability makes it usable for daily, production-level workflows, not just demos
• The ecosystem effect is huge: devs, creators, and teams can all build on the same foundation
• It’s one of the few AI products that keeps improving without increasing cognitive load

What’s most impressive is how OpenAI continues to turn cutting-edge research into something immediately practical. Curious what you’re most excited to unlock next with this release

What needs improvement

AI bias (1)AI environmental impact (2)

• More transparency and control around model behavior and updates, especially for teams using it in production
• Clearer guidance on best practices across different use cases (dev, design, marketing, ops)
• Better long-term memory / project-level context to reduce re-explaining complex systems
• More predictable pricing and usage limits as capabilities continue to expand

Still an incredible product — these improvements would make it even easier to rely on at scale.

vs Alternatives

Gemini 2.5 Pro

We chose OpenAI because it consistently strikes the best balance between capability, reliability, and developer experience. The models are strong across reasoning, multimodality, and real-world tasks, but what really stands out is how quickly those advances become usable products.

Beyond model quality, the ecosystem matters: stable APIs, clear documentation, and a fast-moving community make it easier to go from prototype to production. Compared to alternatives, OpenAI feels less like a single model and more like a long-term platform we can confidently build on.

Ratings

Ease of use

Reliability

Value for money

Customization

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1.3K views11mo ago

•29 reviews

What's great

fast performance (28)AI integration ease (22)AI productivity boost (20)AI innovation (19)AI natural language processing (11)

I use Codex as a second-opinion auditor on top of Claude Code, not as the primary builder. Claude writes the code, Codex reviews the reasoning catches edge cases Claude missed, flags assumptions, sometimes spots a cleaner approach.

The two-model loop has measurably improved the quality of what ships, especially on anything involving auth, payments, or migrations where one wrong assumption is expensive.

What needs improvement

AI pricing (3)

Pricing adds up fast when you're running it alongside another paid model for solo founders the combined bill is the main blocker. Would also love a "diff-only review" mode where Codex only audits the lines that changed, instead of re-reading context every call.

Smaller token footprint = more affordable as a daily-driver auditor.

vs Alternatives

Claude Code

Actively enforced just running Claude alone for months (cheaper, simpler) and tried Cursor's multi-model setup. Settled on Codex specifically because its reasoning style is different enough from Claude's that it actually catches things rather than agreeing with whatever Claude said.

Two models trained on similar data give you one opinion twice Codex gives you a genuinely independent read.

Ratings

Ease of use

Reliability

Value for money

Customization

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614 views6mo ago

•13 reviews

What's great

ChatGPT is useful for writing content, learning new things and solving everyday problems It saves time and makes complex topics easier to understand

What needs improvement

Sometimes the answers can be inaccurate or miss important context Better accuracy and more consistent responses would make it even more useful

vs Alternatives

I like the simple interface and how ChatGPT helps with writing coding research and brainstorming everything feels easy to access in one place

Ratings

Ease of use

Reliability

Value for money

Customization

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16 views9d ago

•9 reviews

What's great

fast performance (28)AI innovation (19)

GPT-5.1 represents a meaningful step forward in LLM capabilities. Three key improvements stand out:

1. Engine Segmentation & Personality Presets

The ability to segment different engine types with distinct personalities is genuinely useful. As a GTM builder, this means I can deploy contextually-optimized responses without extensive prompt engineering overhead.

2. Superior Instruction Following

The model now handles multi-step constraints simultaneously. Complex instructions that previously required 3-4 iterations now work on the first try. This directly reduces latency in production systems.

3. Improved Tone Adaptation

GPT-5.1 understands conversational context better. It shifts tone appropriately based on input, which matters more than people realize for enterprise adoption. Technical superiority loses to human-like interaction every time.

The Real Unlock: This isn't a revolutionary leap. It's a solid incremental advance that compounds when deployed at scale. The real advantage goes to teams building on top of this—not those claiming AGI is here.

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726 views12mo ago

•6 reviews

As a developer building tools in the AI space, the consistency and speed of this new API are just fantastic. It's genuinely enabling a new wave of applications. A thought for the roadmap: I've noticed that managing and versioning prompts for team collaboration is becoming a key challenge for many builders. Have you considered adding any metadata or versioning features to the API endpoints to help with this? Regardless, this is a huge leap forward. Thank you for empowering the developer community.

What's great

fast performance (28)AI developer experience (12)

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303 views1yr ago

•4 reviews

I didn’t expect to use ChatGPT this much, honestly. At first it was just quick code checks or drafting emails — now it’s practically my sidekick for half the stuff I do. Need to parse some weird logs? Drafting policy docs? Figuring out how to regex something I haven't touched in a year? Done in seconds. It’s like having someone around who always has the answer (and doesn’t mind explaining it twice when I’m too tired to get it the first time). What I really appreciate is that it doesn’t just spit out info — it thinks with me. Helps break down problems, map out steps, even sanity-checks configs or scripts before I try them in prod. That level of back-and-forth? Game changer. It’s not perfect, sure — sometimes I have to nudge it in the right direction — but even then, it's miles ahead of googling through forum posts and Stack Overflow rabbit holes. At this point, if ChatGPT went down for a day, I'd probably have to take a walk and rethink my workflow.

What's great

fast performance (28)AI productivity boost (20)AI problem-solving (7)AI coding assistance (9)

What needs improvement

AI accuracy issues (9)

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248 views1yr ago

•4 reviews

An incredibly useful tool! Not only does it boost work efficiency, but it also unlocks tons of creative possibilities. I used the following prompt to create my new profile picture, haha! "Transform the character in the attached photo into a 3D chibi-style clay figurine, placed within a Polaroid frame. The visual effect should show the character breaking through the Polaroid's borders, extending into the real world's 2D space. Specifications: Aspect ratio: 9:16 (vertical composition) Character design: Convert the subject into a chibi 3D figurine at 1/4 scale, full-body, retaining original clothing and style with soft, clay-like textures. Background: Extend the Polaroid's background in chibi style (no additional characters), matching the original scene. Polaroid text: Handwritten font: 'XXXX' at the bottom"

What's great

AI image generation (8)AI productivity boost (20)AI creativity enhancement (14)

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101 views1yr ago

•8 reviews

OpenAI has completely reshaped how I build and communicate. The APIs are powerful, flexible, and surprisingly intuitive. Whether it's coding, writing, or ideation—it's like having a super collaborator on call. Would love even more transparency around model updates and roadmap, but overall, it’s a game-changer.

What's great

AI integration ease (22)AI API (42)AI productivity boost (20)AI creativity enhancement (14)

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91 views1yr ago

•4 reviews

OpenAI’s API has genuinely transformed the way I work and approach daily challenges. I’m not a technical expert, but using ChatGPT has made writing, researching, and even tackling tricky problems so much easier and more efficient. What impresses me most is how it helps break down complex issues step by step, offering clear and helpful solutions. Of course, there are times when the answers aren’t perfect or miss the mark, but overall, the experience has been outstanding. I hope to see even more improvements in the future, making the AI even more intuitive and accurate. Thank you to the OpenAI team for making advanced technology accessible and useful for everyone!

What's great

AI accessibility (2)AI API (42)AI productivity boost (20)AI problem-solving (7)

What needs improvement

AI accuracy issues (9)

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73 views1yr ago

•10 reviews

GPT Models: The Generative Pre-trained Transformer series, including ChatGPT, revolutionized natural language processing, enabling machines to communicate effectively with humans. Codex: This AI system powers GitHub Copilot, offering software developers a way to streamline their coding processes. DALL·E: OpenAI’s image-generation model showcases the creative potential of AI by generating unique, high-quality images from textual descriptions. Reinforcement Learning Research: OpenAI’s advancements in reinforcement learning have laid the foundation for robotics and gaming applications.

What's great

AI image generation (8)AI innovation (19)AI natural language processing (11)AI coding assistance (9)

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54 views1yr ago

used OpenAI to build FetchSandbox

•8 reviews

What's great

I run GPT alongside Claude in FetchSandbox's generation pipeline — parsing OpenAPI specs, discovering realistic workflows, sanity-checking output across 60+ APIs. Where GPT earns its place is breadth and reliability: it's seen every API convention under the sun, and its structured output (function calling / JSON mode) parses cleanly every time — which matters when you're generating at volume and can't babysit each result. It's the dependable workhorse: fast, consistent, and it just works. For a solo founder shipping a lot, that consistency is gold.

What needs improvement

Main friction is scaling headroom — rate limits and the tier ramp can bite when a batch job spikes, so I've had to build retries/backoff around occasional latency. Smoother burst handling for high-volume generation jobs would help. Model version churn is the other one: pinning a version and migrating on deprecation adds overhead. Minor next to how much it just works, though.

vs Alternatives

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350 views4mo ago

used OpenAI to build Floot in ChatGPT

•2 reviews

ChatGPT is where hundreds of millions of people already think through their ideas, so that's where we wanted Floot to be. With apps in ChatGPT, Floot sits right in the sidebar: people describe an app, watch it build in a live preview and publish it, and the AI runs on the ChatGPT plan they already pay for.

Alternatives Considered

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10h ago

used OpenAI to build Hyperif

•1 review

At Hyperif, we rely on Azure OpenAI to power our platform, enabling us to offer a robust, secure, and scalable solution to our users. The ability to run our own dedicated instances and infrastructure ensures that we can maintain complete control over data privacy, safeguarding our users' information. Azure OpenAI allows us to leverage OpenAI’s powerful models while providing the separation and security we need. It’s the perfect balance—highly flexible, with seamless API integration that’s both easy to use and implement. This makes it simple for us to integrate advanced AI functionality into Hyperif, delivering consistent performance with peace of mind. The clear and straightforward APIs have allowed us to focus on building the features our users love, without worrying about the complexities of the underlying infrastructure. With OpenAI through Azure, we’re able to provide a secure and powerful AI-driven experience while ensuring our users’ data stays private and protected.

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262 views1yr ago