Back to Home

The ReplyHub Manifesto

Why we don't use OpenAI and what we believe in

Why We Don't Use OpenAI

The Problem with OpenAI's Output

If you've used ChatGPT or GPT-4, you know the feeling. The responses are... fine. They're grammatically correct. They follow a template. But they feel hollow.

Every response follows the same pattern: "I understand you're asking about..." → Generic overview → Bullet points → "In conclusion..." → Safety disclaimer.

It's corporate AI-speak. Surface-level. Templated. Robotic.

What Real Intelligence Looks Like

When we tested Cerebras GPT-OSS-120B and Qwen 2.5, we found something different:

  • Actual reasoning through problems
  • Nuanced understanding of context
  • Natural language that doesn't scream "AI"
  • Deep thinking instead of pattern matching

The Speed Myth

OpenAI markets their models as "fast" but:

  • 200-500ms API lag before anything happens
  • Rate limits that throttle real usage
  • Inconsistent performance
  • Streaming to hide the slowness

Meanwhile, Cerebras GPT-OSS delivers:

  • 3000 tokens per second (not a typo)
  • Consistent sub-200ms total response time
  • No rate limit games
  • Complete responses, fast

OpenAI's Approach:

  • • Closed source
  • • Safety theater over utility
  • • Corporate customers first
  • • Restrictive usage policies
  • • "AI should feel like AI"

Our Approach:

  • • Use the best models (Cerebras, Gemini)
  • • Quality over brand names
  • • Indie builders first
  • • Your data, your rules
  • • AI should be indistinguishable from human expertise

Models We Actually Recommend

Cerebras GPT-OSS-120B

"This model excels at efficient reasoning across science, math, and coding applications."
  • • Real reasoning: Actually works through problems
  • • 3000 TPS: Genuinely fast, not marketing fast
  • • $0.25/M tokens: 10x cheaper than GPT-4
  • • No templates: Every response is thoughtful

Cerebras Qwen 2.5 72B

"The best overall model we've tested."
  • • Natural output: Doesn't feel like AI
  • • Nuanced understanding: Gets context and subtext
  • • Creative solutions: Not just pattern matching
  • • Consistent quality: No random bad responses

Google Gemini 2.5 Flash

"Perfect for RAG and retrieval tasks."
  • • Huge context: 1M tokens
  • • Fast and cheap: $0.075/M tokens
  • • Reliable: Consistent performance
  • • Multimodal: Handles images too

Why This Matters

Your customers can tell when they're talking to "AI". They know the OpenAI template. They recognize the corporate speak. They feel the lack of genuine understanding.

With ReplyHub and our chosen models:

  • Customers get real answers, not templates
  • Responses feel human, not robotic
  • Problems get solved, not summarized
  • Conversations feel natural, not scripted

For Indie Builders

You're not building for Fortune 500 companies who want "safe" AI that sounds corporate. You're building for real people who want real solutions.

That's why we:

  • Default to Qwen 2.5 (best overall)
  • Recommend GPT-OSS for reasoning
  • Use Gemini for retrieval
  • Never recommend OpenAI

The Bottom Line

OpenAI

Templated responses + API lag + Surface thinking + Corporate speak

ReplyHub

Real reasoning + 3000 TPS + Deep understanding + Natural language

We built ReplyHub because we were tired of AI that feels like AI. Your customers deserve better than templates. Your business deserves better than surface-level thinking. And you deserve better than OpenAI's limitations.

Choose quality. Choose speed. Choose models that actually think.

Choose ReplyHub.

Start Building Better AI