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FlashQLA
A
Rows
A
Recraft
S
ChatGPT Operator
B
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.Spreadsheets with AI + live integrations baked in.Vector + raster AI for designers. Actually controls the output.OpenAI's browser agent. Clicks and types on websites for you.
CategoryDev PlatformDataImageAgents
PricingFree (MIT License, open-source)Free + $19-$89/user/moFree + $12-$48/moIncluded with ChatGPT Pro $200/mo
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.Ops teams, marketers, anyone building dashboards from multiple sources.Designers, brand teams, anyone needing vector output or tight style control.Power users willing to pay $200/mo for a browser bot.
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
  • Pull live data from Stripe, Slack, Google Analytics, etc.
  • AI functions inside cells
  • Modern UX
  • Exports SVG vectors — rare in AI image gen
  • Strong style control + consistency
  • Brand kit for consistent outputs
  • Actually uses websites — fills forms, clicks, checks out
  • Built into ChatGPT
  • Good for repetitive web tasks
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
  • Not a full Excel replacement for heavy users
  • Integrations best on paid tiers
  • Less hyped than Midjourney
  • Learning curve for non-designers
  • Slow vs doing it yourself
  • Breaks on complex auth flows
  • $200/mo gate
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 most interesting spreadsheet in years. Great for ops dashboards.S-tier for designers. The only one that takes vectors seriously.B-tier. Still early. Manus is more flexible for less money.
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