Ultra is $100 cheaper than SuperGrok Heavy. Here’s what power users actually need to know before switching.
Apache-UAE retweeted
TensorFold (app) Beta 6 for macOS is out with lots of new stuff 🔥
TensorFold Beta 6 is live! for macOS 🚀
We've added Bots, easier local model discovery and Kokoro playback so you can listen to chat replies.
You'll also find cleaner chat controls and fixes for memory saving and privacy.
Give it a try: tensorfold.dev
@plotarmordev @MiaAI_lab @volatilemarkts @petruspennanen
Apache-UAE retweeted
MLX-Serve 26.10.1 is out: speed across the board.
Exactly faster. Qwen3.8 27B with its drafter
+66% on an M5 Ultra,
+28% on an M4 Max,
+37% on an M1 Pro.
Qwen Flash Next:
+11% decode on M4 Max,
+51% prefill on M5 Ultra. (up to ~5400 PP!!!!)
Gemma 4, Qwen, LFM2.5, Spark, Bonsai 2 all faster, output byte-identical to 26.9.6 (across 18 models).
New:
* GGUF models run on our own MLX engine, written in Zig and Metal, instead of the llama.cpp fallback. (experimental)
* 🍣 Sushi-format Flash Next packs run directly.
* Qwen-Image 2.1 edits pictures from instructions.
* Drafting is on by default for every model that supports it.
Huge thanks to everyone who filed, tested and fixed this one: @STRML_, @sbusso, @wutang_superfan , lborloz, LXD-8 @alinselea zeeshanhaque21 @Lojza3D, h9q2cyxvgm-ui @kennethrdegraff, @CowboyCoderHQ , codysk, @Beamsters1, @CerebralCoding_, @AjAbsaki , and more.. THANKS ! Please comment if I did not include your name, for visibility, I know people mostly by their GH handle.
Special thanks to @ashxhart and @Spangler3000 for pushing !
Benchmarked and tested across 5 machines: htmlhost.jax.workers.dev/ren…
GH Release Download + Changelog:
github.com/ddalcu/mlx-serve/…
Website: mlxserve.com
Three ecosystems collide 🔥
AMD joins the MCDMA club, as we have now achieved true RDMA. @Apple @NVIDIAAI @AIatAMD
We measured ~10 µs round trip bidirectionally.
Huge thanks to @petruspennanen for giving me access to their Strix and Spark so I could get this up and running.
The next test is running inference across them 👀
mcdma.dev github.com/ashhart/mcdma
If the model that runs your service stack lives…
If the model that runs your service stack lives outside your jurisdiction, you don't have an AI strategy. You have a dependency with a nice UI.
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#UAEAI
You're not building AI for the UAE if every token still leaves the country.
I keep watching the same movie. Sharp agent demo. Happy stakeholder. Then legal asks where the files go and the project stalls for six weeks. Cloud APIs are fine for toys. They are a hard sell the second real client data, Arabic contracts, or internal SOPs enter the chat.
Local and sovereign inference is what actually unlocks the work that dies in procurement. Cost stops being a roulette wheel — you pay for boxes and power, not a meter that explodes every time someone dumps a 40-page PDF into the prompt. Privacy stops being a slide. The data never leaves your desk, your free-zone rack, or the client's own floor. Control gets boring in the best way: swap the model, cut a bad tool, keep serving when the public endpoint has a bad afternoon.
The gap I want more GCC builders to own is making local the default path, not the enterprise upgrade you bolt on after the third security review. Most teams still treat on-prem or private GPU like cosplay. The ones who put real inference under real workloads will win the trust fights everyone else keeps losing.
If you are shipping agents or internal tools here and your stack still phones home on every request, you are leaving deals on the table for whoever won't.
Who is actually running production loads on private metal or locked-down GPU in Dubai or Abu Dhabi right now? Drop the setup. I want receipts, not vibes.
#UAEAI #LocalAI #SovereignAI
113 tok/s think off. 70 tok/s at xhigh. 960 / 892 tok/s prefill at 64k and 258k. Mac Studio M3 Ultra 256GB, mlx-serve, nothing else loaded.
I just replaced a $180/mo Arabic LLM API bill with a model running on a desk in Dubai. Latency fell. Privacy stopped being a slide.
Most "bilingual AI for the GCC" still ships every Arabic ticket to a foreign endpoint first. Names, invoice lines, sometimes partial ID numbers. Your DPO notices. Your customers don't love it either.
I took mixed Arabic-English desk traffic we already had and pointed it at a quantized instruct model on hardware we owned. Same prompts, same few-shots, no cloud hop. Median turn went from roughly three seconds of round-trip to well under half a second on the local network. Cost per thousand replies is power and a bit of fan noise.
What actually fixed the experience for real users here wasn't raw parameter count. Cloud models kept "correcting" Gulf Arabic into stiff MSA or flipping into English mid-answer when the ticket was clearly Arabic. I locked the system prompt to mirror the user's language and dialect and banned silent translation. Support agents stopped rewriting the bot's tone. Escalations on "sounds wrong" dropped hard in the first week we measured.
If you run intake, ops, or customer desk work for UAE/GCC teams, give local inference one honest week on real tickets before you renew the SaaS. You get the speed. You get the data stay-home story. You get dialect control you can actually own.
Anyone else running Arabic or bilingual models on-prem or on a UAE box? What broke first?
#LocalAI #ArabicAI #DubaiBuilders #UAETech #SovereignAI
السيادة الرقمية ليست شعاراً سياسياً؛ هي شرط تشغيلي لنجاح…
السيادة الرقمية ليست شعاراً سياسياً؛ هي شرط تشغيلي لنجاح الذكاء الاصطناعي في الإمارات والخليج.
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#UAEAI
your agent doesn't need admin tool scopes.
minimum perms only — same as a service account. keep write tools off until reads are stable.
uae buyers will ask. ship least privilege day one.
#AI #Agents #EnterpriseAI #UAE #Dubai
arabic retrieval dies on alef variants more than model choice.
if you don't normalize أ إ آ ا and strip tashkeel before embed, your UAE rag is guessing.
do that first. then chase the fancy model.
#AI #UAE #ArabicNLP #RAG #Dubai
The next bottleneck for UAE AI isn't smarter models
The next bottleneck for UAE AI isn't smarter models. It's who owns the runtime when those models sit inside real operations.
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#UAEAI





















