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FlashQLA
A
Perplexity
S
DALL-E 3
B
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.AI search done right. Cited answers, not chat theater.OpenAI's image model. Built into ChatGPT Plus.OpenAI's browser agent. Clicks and types on websites for you.
CategoryDev PlatformResearchImageAgents
PricingFree (MIT License, open-source)Free + $20/mo ProIncluded with ChatGPT Plus $20/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.Replacing Google for any question where you want a cited answer in seconds.ChatGPT Plus users who want images without paying extra.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
  • Sources every claim
  • Fast, current answers
  • Pro Search runs multi-step research
  • Spaces for persistent context
  • Excellent prompt understanding
  • Built into ChatGPT — no extra subscription
  • Good at composition + concepts
  • 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 general chatbot
  • Answers can be shallow on complex topics
  • Aesthetic ceiling below Midjourney + Ideogram
  • Text rendering worse than Ideogram
  • No fine control
  • 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.)S-tier for search. I use it before Google now. If you're still Googling everything, try this for a week.B-tier standalone, A-tier value if you already pay ChatGPT. Don't pay for it separately.B-tier. Still early. Manus is more flexible for less money.
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