Test AI Models

Compare AI models side-by-side on same prompt

111 followers

Compare AI models side-by-side on same prompt

111 followers

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AI Metrics and Evaluation

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LLM Developer Tools

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Prompt Engineering Tools

Test AI Models is the only platform that lets you test YOUR actual prompts across multiple AI models simultaneously with zero setup. Unlike generic benchmarks, API routers, or Reddit rabbit holes, we show real-time quality, speed, and cost comparisons - so you can choose the winner before writing a single line of code. No API keys, no 24-hour setup, no guessing. Just paste your prompt and get answers in 30 seconds. We solve pre-deployment model decision for your AI apps, automations or agents.

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Launch tags:Productivity•Developer Tools•Artificial Intelligence

Launch Team / Built With

Wispr Flow: Dictation That Works Everywhere — Stop typing. Start speaking. 4x faster.

Stop typing. Start speaking. 4x faster.

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Maker

📌

Hey Product Hunt! 👋 I'm Marko, founder of Test AI Models and CEO of Eterna Creative, a product studio in Serbia. Over the past 4 years, I've built 15+ apps and helped dozens of clients integrate AI into their products. ❓ The problem Three months ago, a client asked me: "Should we use ChatGPT or Claude for scope estimation?". I spent 5 hours reading Reddit threads. Every answer contradicted the last: "GPT-4 is always superior" "Claude destroys GPT for customer support" "Gemini is 5x cheaper and just as good" On Reddit I found out that someone chose GPT-4 by default and in 4 months they got $1,5k surprise API bill. Someone else was using Gemini then switched to Claude - it took 2 weeks to re-integrate (different API structure, error handling, rate limits), which was more than $2,000 in developer hours. Another guy got hit with a $13,500 overnight bill from OpenAI as they thought rate limits were configured - but they weren't. But nobody actually tested the client's specific use case that I needed. ❌ Why existing solutions don't work - Industry benchmark tools: Amazing for benchmarks, but they test "write a poem about cats." Your customer support bot needs a different evaluation than a code generator. - LLM subscriptions: $40-60/month to compare just 2-3 models, but they hide true API costs - API integrations: see the costs, but time it takes to integrate one, then 3, then 7 models means $2k+ wasted just to test for single product - API routers: Great for routing APIs after you've integrated. But they don't help you decide which model to choose first. - Reddit threads: 5-10 hours/week lost reading opinions. "GPT-4 is best" vs "Claude is better" vs "Use Gemini." Nobody tests YOUR specific prompt. The real problem: You can't know which model wins for YOUR use case until you test YOUR actual prompts. ⏲ Why now? The AI landscape exploded. There are now 1,000+ models uploaded to Hugging Face daily. DeepSeek just released models that rival GPT-4 at 1/50th the cost. Claude Sonnet 4.5 launched and is shaking the ground. Developers face decision paralysis. Which model? At what cost? For which task? Meanwhile, documented cases of bill shock keep growing: $55K overnight (leaked API key), $120K weekend charge (startup), $2K average unexpected bills. The gap is obvious: No tool lets you test YOUR prompts across models, see real costs, and decide BEFORE integrating. ✨ Our solution Test AI Models solves the pre-deployment decision. Paste your actual prompt → We run real API calls across ChatGPT, Claude, Gemini & 4 others in parallel → See quality + speed + exact costs side-by-side → In 30 seconds. No API keys. No prepaid credits. No 24-hour setup. ✅ Benefit 1: Test YOUR actual prompts Not "write a poem." Your real production prompts: - AI agent step - Customer support response template - Code generation instruction - Content writing brief - Data analysis query Generic benchmarks ≠ your specific use case. We test what actually matters to you. ✅ Benefit 2: See exact costs with scale projections Real example from our platform: - Customer support refund email: ChatGPT: $0.0045/query → $450 at 100K queries Claude: $0.0038/query → $380 at 100K Grok: $0.0011/query → $110 at 100K Switch from ChatGPT to Grok = Save $340/month. That's the number that makes someone actually change their integration. ✅ Benefit 3: Zero friction, instant results Traditional approach: - Set up 7+ provider accounts (2-3 hours) - Configure billing for each (1-2 hours) - Generate API keys (30 min) - Read documentation (2-3 hours) - Install SDKs (1-2 hours) - Write test code (2-4 hours) - Debug issues (2-4 hours) Total: 24+ hours + $70-100 prepaid credits Test AI Models: Paste prompt, hit enter, 30 seconds to results. 🤝 How we make money (transparency) Freemium + pay as you go model: FREE: 25 free models selection runs PRO: $19/month access - (50% discount on Launch week) +$5 in API tokens (1:1 passthrough - no commission) Why this pricing? - One prevented integration mistake ($800 avg) = 89 months paid - Setting up APIs individually costs $2,000+ in time + wasted credits We want to be accessible to indie devs, not just enterprises Future revenue: Additional tires for agents, advanced alerts, team collaboration features, etc. We will never: Sell your prompts or data, charge hidden fees or show ads 🎉 Social proof Current traction: - Won "Best Use of AI" Bubble/Contra hackathon - 240+ prompts tested by early users ⚔ Why I'm qualified to build this: Running a product studio means I see this problem constantly. Every client asks: "Which AI model?" I got tired of not having a good answer. Plus, I'm building Test AI Models WITH Test AI Models. We use our own platform daily to decide which model to use for our own features. If it doesn't work for us, we fix it. 👉 What's next Current (Phase 1): Text models and core platform - ChatGPT, Claude, Gemini, Grok, Perplexity, DeepSeek, Qwen - Test previews Phase 2 (Month 2-3): Sub-models and additional features - Additional models and sub-models - AI agent workflow testing - Smart alerts - Recommendation engine Phase 3 (Month 4-6): Image and audio models comparison - Image generation: DALL-E 3, Midjourney, Flux, Stable Diffusion, Ideogram... - Text-to-Speech: ElevenLabs, OpenAI TTS, Play.ht - Speech-to-Text: Whisper, AssemblyAI, Deepgram Phase 4 (Month 7-12): Video models comparisson - Text-to-Video: Runway, Pika, Luma - Image-to-Video: Stable Video Diffusion What should we prioritize? Vote with your comments. ⏱ Honest limitations What we DON'T have yet: - Only text models (image/audio/video coming based on demand) - No local model support (Llama, Mistral, Qwen) - No API access (web-based only) - No team collaboration features - No prompt versioning What we're NOT: - Not a production API router (use OpenRouter for that) - Not a chatbot interface (we're for testing, not daily use) - Not replacing comprehensive benchmarks (Arena is great for research) We solve one problem really well: Helping you choose the right model BEFORE you integrate. 🎁 Special Product Hunt offer - Discount: Lifetime PRO membership access for $99, or 50% off on any purchase - Product champions: Assembling team of 50 product champions for lifetime free access who will help us build the product with occasional feedback Use code PRODUCTHUNT50 for both options. Discount valid in launch week 23th Feb - 2nd March. No credit card required for free testing. What I need from you 1. Test it with YOUR real prompt Don't test generic stuff. Use your actual production prompt and tell me: Did results surprise you? Which model won for your use case? What's missing? 2. Brutal feedback wanted Missing features? Wrong approach? Confusing UI? Bad pricing? Tell me. I'm here all day to respond. 3. Vote if it helped If Test AI Models saved you time, money, or prevented a bad decision, an upvote helps other developers find it. Thank you for checking out Test AI Models. Let's make AI model selection suck less. - Marko www.testaimodels.com P.S. We're building Test AI Models WITH Test AI Models. Follow us for weekly transparent updates on which models we use and why.

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1mo ago

Congrats on the launch and the product! It feels very pain-point and niche-oriented, and that caught my attention immediately.

We also faced this problem while building CoreSight. I'll be sharing the product with some friends who are also starting to build their own things and are unsure which model to choose.

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13d ago

Maker

@andreitudor14 Thank you very much Andrei, this is what we are trying to achieve - focus on AI developers and make their lives easier - as we did for us with this product.

Checked your product, i like it, will be useful when we start to look for funding. I love how you positioned "coming soon" features. Congrats, and I hope you can find even better LLMs for CoreSight with Test AI models.

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12d ago