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Side-by-side: what they do, what they cost, what Kai actually thinks. Pass up to 4 tools via ?tools=claude,chatgpt,gemini.
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Dev Platform
Audio
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Coding
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Image
Video
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Meetings
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Productivity
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Data
Marketing
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Google Veo
A
FlashQLA
A
Perplexity
S
ChatGPT Operator
B
TaglineGoogle's video model. Baked into Gemini + YouTube Shorts.Qwen's open-source GPU kernel library that squeezes 2–3× more speed out of linear attention on NVIDIA Hopper hardware — if you're lucky enough to own one.AI search done right. Cited answers, not chat theater.OpenAI's browser agent. Clicks and types on websites for you.
CategoryVideoDev PlatformResearchAgents
PricingIncluded with Gemini Advanced $20/mo + YouTube creator toolsFree (MIT License, open-source)Free + $20/mo ProIncluded with ChatGPT Pro $200/mo
Best forGemini Advanced users, YouTube Shorts creators.ML engineers and researchers running Qwen3.x linear-attention models on H100/H200 clusters who need to close the gap between theoretical GDN efficiency and actual hardware throughput.Replacing Google for any question where you want a cited answer in seconds.Power users willing to pay $200/mo for a browser bot.
Strengths
  • Included with Gemini Advanced
  • YouTube Shorts native integration
  • Strong prompt understanding
  • 2–3× forward-pass and ~2× backward-pass speedup over FLA Triton kernels on Hopper GPUs
  • Gate-driven automatic intra-card context parallelism boosts SM utilization in long-sequence, small-head-count regimes without manual config
  • Hardware-friendly algebraic reformulation reduces Tensor Core, CUDA Core, and SFU overhead with no numerical precision loss
  • MIT licensed and fully open-source — drop it straight into Qwen3.x training and inference pipelines
  • Sources every claim
  • Fast, current answers
  • Pro Search runs multi-step research
  • Spaces for persistent context
  • Actually uses websites — fills forms, clicks, checks out
  • Built into ChatGPT
  • Good for repetitive web tasks
Weaknesses
  • Still catching up on quality vs Kling/Runway
  • Less control than pros need
  • Extremely narrow hardware requirement: SM90+ only (H100/H200, DGX Spark) with CUDA 12.8+ and PyTorch 2.8+ — useless outside Hopper-class clusters
  • GDN/Qwen-specific: not a drop-in replacement for FlashAttention-style softmax kernels, and won't help you if you're not running linear-attention Qwen models
  • Very new, minimal community adoption or third-party validation yet
  • Not a general chatbot
  • Answers can be shallow on complex topics
  • Slow vs doing it yourself
  • Breaks on complex auth flows
  • $200/mo gate
Kai's verdictA-tier if you already pay Gemini. B-tier standalone.A genuinely impressive, laser-focused kernel optimization from the Qwen team — real speedups on real hardware — but its utility is gated behind Hopper GPUs and Qwen's GDN architecture, making it a niche power tool rather than a broadly useful library. (Verdict pending Phi's full review.)S-tier for search. I use it before Google now. If you're still Googling everything, try this for a week.B-tier. Still early. Manus is more flexible for less money.
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