
Design & Quality Engineer โ๏ธ | Crypto Broker ๐ช | BioMedical โ๏ธ| Video Game & Music Enthusiast | 2x DGX Spark โก๏ธ #Bitcoin #Noderunner #LocalAI
Joined September 2021
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Coinupbtc ๐ช retweeted
Cohere says Qwen tried to send data to China. Bullshit.
1 call in 100,000, and thats their own number. They wont even tell you how many calls they ran. They ran the same task again and Qwen wrote the correct rule.
So they forced it. They fed the model its own reasoning plus the start of a bash command and sampled hundreds of times until it typed a URL. 1 curl flag took that from 4% to 92%. Thats not a finding. They wrote half the command for it.
Where are the transcripts? The code? The checkpoint, the quant, the sampling settings? "We publish the hosts and the trigger." Link? Nothing. Did anyone ask Alibaba? Not a word. And their own conclusion: they cannot say if any of it is deliberate.
Who wrote it? A company that sells "sovereign AI", just launched a cyber business, wrote part of the post with its own product, and wants governments to put checks on open weights. Released the same day Anthropic filed for its IPO. Andrew Curran is already talking about new laws.
For me this is the same fucking wave. Scare people off the models they can run themselves, then sell them the safe alternative.
I run Qwen3.8 Flash-Next every day on my 4x 3090. Show me the logs or shut up.
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected.
Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions.
Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent.
But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models?
We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem.
Read the full report: cohere.com/blog/concerning-bโฆ
Coinupbtc ๐ช retweeted
Kind of crazy.. people are still buying Sparks at their new price, definitely not like before but they are being purchased.
Coinupbtc ๐ช retweeted
๐ฅ ์๋น๋์ RTX ๊ทธ๋ํฝ์นด๋ ์ฐ์๋ ๋ชจ๋ ๋ถ๋ค ๊ผญ ๋ณด์ธ์!!!!! ๐ฅ
ํด์ธ์์๋ ์ง์ง ๋๋ฆฌ์ธ๋ฐ... ๊ตญ๋ด์์๋ ์์ง ์ ์ํผ์ง ๊ฒ ๊ฐ์ ๊ณต์ ๋๋ฆฝ๋๋ค!!!
--> ๋ฉฐ์น ์ .. ์๋น๋์๊ฐ RTX์ ๊ฑธ์ด๋ "AI ์ฐ์ฐ ์ ํ"์... ์ต๊ทผ์ ๊ณต๊ฐ๋ ์คํ์์ค๊ฐ ๊ทธ๋ฅ ํ์ด๋ฒ๋ ธ์ต๋๋ค.
์ด๋ฆ GPU-Unlock์ธ๋ฐ... ์ ๊ธ์นด ์ ์ฌ๊ณ , ์ค๋ฒํด๋ญ๋ ์ ํ๊ณ , ์ ํ๋ง ํ์๋๋.. ์๋์ ๊ฐ์ด ์ฑ๋ฅ ํฅ์์ด ๋์์ต๋๋ค.
RTX 3060 --> +78~99%
RTX 3070 --> +72~81%
RTX 3080 --> +68~73%
RTX 3090 Ti --> BF16 +80%
RTX 4070 Ti --> +83~84%
RTX 4090 --> ํน์ Tensor ๊ฑฐ์ 2๋ฐฐ
RTX 2080 Ti๋ --> +36~64%
--> RTX 3000๋๋ง์ ์ด์ผ๊ธฐ๊ฐ ์๋๋๋ค. 20 / 30 / 40 ์๋ฆฌ์ฆ๊น์ง, ๋ฐ์คํฌํ์ด๋ ๋
ธํธ๋ถ ์ชฝ ์ค์ธก๋ ์ง๊ธ๊น์ง ๊ณ์ ์ค์๊ฐ์ผ๋ก ์์ด๊ณ ์์ต๋๋ค.
โญ๏ธ AI ์ด๋ฏธ์ง ์์ฑ์ด๋ ๋ก์ปฌ LLM ๋๋ฆฌ๋ ๋ถ๋ค์ ํนํ ์ฒด๊ฐ๋ ์ ์์ ๊ฒ๋๋ค!! โญ๏ธ
์ง์ง ์ ์ด๊ฒ ๋ฏธ์น๋ฏ์ด ๋๋ฆฌ๋๋ฉด...
๋ด ์ง์ ์๋ RTX ๊ธ์นด ์์ "์ธ ์ ์๋๋ฐ ์ ๊ฒจ ์๋" AI ์ฑ๋ฅ์ด ์์๊ธฐ ๋๋ฌธ์
๋๋ค.
์ ์๋น๋์๊ฐ ์ด๋ ๊ฒ ํ๋๊ณ ์ง๊ธ ์์ฌ์ด ๊ฐ์ฅ ๋ง์ด ๋๊ณ ์๋ ์ชฝ์..
--> ์งํฌ์ค๋ ๋น์ผ ์ ๋ฌธ๊ฐ์ฉ GPU๋ฅผ ๋ฑ๊ธ์ผ๋ก ๋๋๋ ค๊ณ FP16/BF16 ์ชฝ์ ์ผ๋ถ๋ฌ ๊น์๋ ๊ฑฐ๋ผ๋ ์ชฝ์
๋๋ค.
(์์ง ์๋น๋์๊ฐ ๊ณต์์ ์ผ๋ก ์ธ์ ํ ๊ฑด ์๋)
์ด๋ฏธ ์ฐ ์๋ RTX ๊ธ์นด์ ์ด๋งํผ ์ฑ๋ฅ์ ์๋น๋์๊ฐ ๋ง์๋๊ณ ์์๋ค๋ ์ฌ์ค ์์ฒด๊ฐ ๋๋ฌด๋๋ฌด ์ถฉ๊ฒฉ์
๋๋ค...
์คํ์์ค ๊นํ๋ธ:
github.com/Zagitta/gpu-unlocโฆ
40 ์๋ฆฌ์ฆ ํ์ฅ ๊นํ๋ธ:
github.com/JustAResearcher/gโฆ
TensorFold 1.1.4 is live.
Up to 5ร faster Qwen3.8-27B cold prefill on GB10, native Gemma 4 on CUDA, faster Flash Next multi-stream serving, and a long list of fixes from the community.
What's new and fixed:
โข Qwen3.8-27B on CUDA has a new default prompt/decode recipe. On GB10, cold prefill improves by 54% at 2k, 107% at 8k, 258% at 32k and 416% at 64k. The 64k result goes from 203 to 1,045 tok/s; decode gains about 2% across 1 to 8 streams. Optional int8 prompt precision is also available, with bf16 remaining the default.
โข Gemma 4 12B and 31B now run on native CUDA from MLX affine checkpoints, with their drafters. On GB10, the 12B's MTP assistant takes single-stream greedy chat from 30 to 67 tok/s, and z-lab's DFlash drafter takes the 31B from 12.6 to 29.9 tok/s. Image paths are implemented, but their GB10 image test cells have not run yet.
โข Flash Next on CUDA verifies multiple streams' drafted windows in one pass. The GB10 served sweep gains 35%, 75% and 116% at 2, 4 and 8 streams, with tokens unchanged. Greedy MTP heads batch together; sampled heads, trees and media retain their per-stream path.
โข More kernel work: fused Flash Next DeltaNet prefill, a reused PLE worker pool, Qwen attention reads that reuse KV data in L2, segmented split-K decode, and fewer Nemotron RADIO launches. GLM-5.3's Metal sparse-index scan drops from 1.59 ms to 0.14 ms in the measured cell. Startup timing tables also stop one noisy measurement from setting later performance.
โข Drama 3 CUDA prompt chunking is opt-in. With 128-row chunks on GB10, first audio drops from 18.2 s to 0.76 s and the full utterance from 47.5 s to 30.2 s. The default remains unchanged; larger chunks can change rounding.
โข Opt-in speech controls now include silence-tail, onset and mid-utterance guards; whole-reply redraws with budgets and deadlines; short-reply and register guards; a controls allowlist; synthesis frame limits; and attested voice catalogs. The voice tool can build those catalogs from reference audio and transcripts. Drama CUDA replay also waits for buffer fills before reuse.
โข Nemotron-H MLX 4-bit now runs on the opt-in native HIP backend, including MTP, prompt caching and tensor parallelism. Unsupported flags are refused before loading, and Qwen HIP can cancel during long prompt chunks.
โข Idle unload can free a model's memory after a configured idle period and reload it on the next request. A failed reload returns a retryable error; ranked GLM CUDA engines refuse this option.
โข Sticky CUDA faults now make /health return 503. Driver-refused CUDA graphs can run eagerly instead of spinning, and queued writes retain their destination buffers through allocation failures.
โข GLM's draw ring no longer fills after 64 completed or cancelled cold requests. Long chats retain less tokenizer/template scratch, kept-alive connections retain less memory, and a missing disk state no longer evicts cached states before its read fails.
โข Memory and cancellation fixes cover Drama Metal loads that exceed the budget, Nemotron Metal Mamba-pool sizing and released slots after refused work, Qwen draft-node counts above 15, and prompt passes that now stop between chunks on cancellation or shutdown. GLM on one Mac also keeps its draft-acceptance estimates steadier after missed drafts.
โข Flash Next CUDA gains POST /v1/decisions on one GPU and loads valid nested checkpoint shards. Qwen CUDA vision reads Hugging Face-named towers. Managed benchmarks can select bf16 or fp8 KV cache and record the choice. Windows builds with nvcc and cl.exe work again.
โข Slide learning counts only kept lessons. App fixes cover engine-refused checkpoints, TUN/fake-IP proxies, Google's sign-in callback and visible setup errors. The docs now have a native GLM-5.3-Flash CUDA page.
โข Experimental DeepSeek work adds native prompt rendering, HTTP 400 responses for template refusals and four-rank prefill planning. It remains behind the whole-model gate; release binaries do not serve DeepSeek checkpoints yet.
Release checks cover cold prompts from 2k to 64k, 1/2/4/8-stream sweeps and reference checks, with Linux and macOS host tests passing. The Qwen recipe changes prompt arithmetic, so output bits can differ from 1.1.3; its quality check matches the previous recipe at 27/40 exact cases, and concurrent/resumed checks still hold. One measured regression is documented: Nemotron Lightning greedy chat at four streams on GB10 is 3.8% slower.
All three release archives are signed and verified against the site's trust root. The nine published assets were downloaded back and checked against the signed files. Homebrew is updated and upgrade-tested, and a fresh install through the website script verified the archive signature.
A huge thank you to the release contributors:
@bobclawblaw @plotarmordev @rielstamand @MiaAI_lab @Bizuayeu @jishvenugopal @petruspennanen @wesley4546
And GitHub contributors jschmied, Mirrdhyn, wojo, heitke, BlivionIaG, harrisonfriia and paragontasx.
Thank you for the reports and requests, GitHub users Chris9121, flashosophy, Gogo6969, Idoo689, johncarterlives, mikog8tor, samwang0041-star and tonghuaxuan2016-dot.
Attribution also matters. The Gemma family builds on earlier work by gilby on GitHub and @codengod. Credit to Google for the Gemma assistant, z-lab for DFlash and the 31B drafter, MLX/mlx-lm and Hugging Face Transformers for model references, and Fish Audio, SGLang-Omni and Descript for the Drama model/codec references. Full source and licence credits are preserved in THIRD_PARTY_NOTICES.md and docs/credits.md.
And thank you to everyone testing, sharing measurements, contributing fixes and giving me access to hardware. This project would not be moving this quickly without you.
@MiaAI_lab @plotarmordev @petruspennanen @volatilemarkts
tensorfold.dev
Coinupbtc ๐ช retweeted
For my local Ai brothers what about connecting all your DGX Sparks?
200 GBs switch
Coming soon ๐
Coinupbtc ๐ช retweeted
โผ๏ธ BREAKING: The private keys of 8 certificates from Indian certificate authority eMudhra were compromised, Mozilla says. Firefox blocked them within 3 hours.
Each key should be a 116-digit number, but one was just 4.
Anyone can guess them and forge HTTPS certs for any website.
Coinupbtc ๐ช retweeted
Welcome back. Space Bunny. ๐
MiniMax-M3.1-Flash is coming.
๐ค Made with AI
Coinupbtc ๐ช retweeted
Sometimes a demo is simply to remind the world that your competition has no desire to dream -- and no ability to evolve.
Coinupbtc ๐ช retweeted
$1,000,000,000,000 wiped out from the US stock market in last 3.5 hours.
Holy Shit.
Coinupbtc ๐ช retweeted
RTX Spark laptop vs DGX Spark.
Essentially the same GB10 chip, same 128GB unified memory, but running at 45 to 80W instead of 140W.
Artificial Analysis just dropped the first AA-AgentPerf-Local numbers. Qwen3.8 27B agent workload (8 tasks, 168 turns):
>RTX Spark laptop: 18.7 min
>DGX Spark: 17.3 min
>Ryzen AI Halo: 34.5 min
>MacBook Pro M5 Pro: 37.6 min
Also check the 5090 haha speedy boi
Coinupbtc ๐ช retweeted
The new Bonsai 2 2B model reaches up to 120 tk/s on iPhone 18 Pro
Itโs better than Qwen 3.5 2B (4-bit) and runs twice as fast while using almost half the memory
Coinupbtc ๐ช retweeted
We discovered a sophisticated recording device that was hidden inside one of our offices. We used our models to understand the device and where it had come from, identifying that a specific employee had planted it a few days earlier. We referred the matter to the FBI, and weโre grateful to the agents and prosecutors who moved quickly to make an arrest. The FBIโs investigation is ongoing and we will continue to support their work.
At this time, we have no indications of this individual inappropriately accessing or exfiltrating model weights, source code, or customer data. The employee was terminated.
We take protecting our technology, data, and people seriously, and as a matter of national importance. Our security program is designed to protect against a wide range of threat actors, from insider risks to cybercriminals to nation states, and this case is an example of how AI can help address these sophisticated security threats.
Coinupbtc ๐ช retweeted
One plan now covers Cursor, Grok, Grok Bot, and X.
This is the biggest change to how Cursor is priced.
If you've been with us since the early days, this will feel like a lot, so I'll walk you through it.
First, every change is opt-in. If you do nothing, nothing happens.
You can keep your current plan with the same benefits, behavior, and pricing, and still move between the current plans. New sign-ups and anyone upgrading from free Cursor go to the new plans.
Here's what's different:
1. First-party usage
For most users, Grok and Composer coding limits are at least double what the matching Cursor plan gives you today.
We worked hard to make usage grow faster than price at each tier:
Plus ($8/mo): our base plan
Premium ($30/mo): 4x Plus usage
Super ($100/mo): 15x Plus usage
Ultra ($200/mo): 50x Plus usage
That's on top of every other product included in the plan.
On the new plans, Cursor usage limits move from monthly to weekly. Grok, Cursor, and X share one weekly pool.
All Grok Bot usage is treated as first-party. So on Premium and up, you get at least double the Grok Bot usage.
We know AI can get expensive. If you're trusting us, you should get as much as we can deliver. That's what we're aiming for with these new plans.
2. Products
Every paid plan includes X Premium features. Grok @Bot comes with Premium and up.
If you're reading this on X, you can now get those features as part of Cursor and @Grok. Your plan also covers Grok chat, Voice, and Imagine images and video.
Grok Bot access has been one of the biggest pain points we've heard since it launched, and it's a big part of why we're excited.
3. Third-party models
You can keep using every model you rely on in Cursor.
What's changing is how those models are billed on the new plans: they come out of your usage credits at the provider's API list price, the same as paying the provider directly.
Current Cursor plans subsidize third-party models, so you can get inference below API price.
At @SpaceXSI, we want to give you as much value as we can on our own models. That's why Grok usage limits are increasing and why we're treating Grok Bot usage as first-party.
We're still committed to Cursor being the simplest way to use models from many providers in one place, and we'll have more news on this front in the coming weeks.
If most of your usage is on third-party models, the new plans might cost you more, so check your usage before switching. That's one of the main reasons these plans are opt-in.
Cursor Pro and Pro+ subscribers who switch get Premium at $20/mo or Super at $60/mo for 6 months (normally $30 and $100).
4. Credit unification
Cursor credits and xAI API credits are coming together - prepaid xAI API balances now move into Cursor.
If you've been running the xAI API and Cursor as separate accounts, this is the start of managing both in one place.
It also means tools like Grok Voice become more accessible to all builders, and our biggest Grok users can now take full advantage of Cursor.
That's a lot of stuff! In summary:
Cursor, Grok, and X are all part of SpaceXSI.
That gives us economies of scale, and this unification is one of the main ways we can pass that on to you as savings and more usage.
Whether you should switch depends on which products you use, and that's different for everyone. If you pay for X today or most of your usage is on Grok, the new plans are probably a better deal.
To get started, check out cursor.com/pricing
What hasn't changed is why we do this: we want to build the best tools we can for you, and we think one plan across all of these products gets us closer to that.
If something here doesn't make sense or feels unfair, please let me know. I'm here to help.
Coinupbtc ๐ช retweeted
We've unified plans across Grok, Cursor, and X Premium.
Introducing The X Subscription.





































