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FlashQLA
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Lovable
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Rows
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Gemini
A
TaglineQwen'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.Build a full app from a prompt. Stripe-ready.Spreadsheets with AI + live integrations baked in.Google's answer. Best integrated with Workspace + free for a lot.
CategoryDev PlatformDesignDataChatbots
PricingFree (MIT License, open-source)Free + $25-$100/moFree + $19-$89/user/moFree + $20/mo Advanced (bundled with 2TB Drive)
Best forML 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.Non-devs + solopreneurs shipping MVPs.Ops teams, marketers, anyone building dashboards from multiple sources.Anyone already on Google, research tasks, summarizing long documents.
Strengths
  • 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
  • Generates full apps + DB + auth
  • Good for non-developers
  • Ships faster than hand-coding
  • Pull live data from Stripe, Slack, Google Analytics, etc.
  • AI functions inside cells
  • Modern UX
  • Native Google Workspace integration
  • Very long context (1M+)
  • Deep Research feature
  • Free tier is generous
Weaknesses
  • 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
  • Complexity ceiling
  • Can generate brittle code
  • Not a full Excel replacement for heavy users
  • Integrations best on paid tiers
  • Writing quality trails Claude
  • Over-refusals on edge content
  • UI is cluttered
Kai's verdictA 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.)A-tier. The strongest 'no-code' AI builder right now. Great for founder MVPs.A-tier. The most interesting spreadsheet in years. Great for ops dashboards.A-tier. The Deep Research feature is genuinely useful. Don't sleep on it if you're already paying Google.
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