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GPT‑5.3‑Codex‑Spark

openai.com

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Re: GPT‑5.3‑Codex‑Spark

#321

Post by alfiedotwtf »

crystal_revenge wrote: post #179
clickety_clack wrote: post #117

Earlier quoted context omitted.

It would be so cool if it generated live in the presentation and adjusted live as you spoke, so you’d have to react to whatever popped on screen!

There was a pre-LLM version of this called "battledecks" or "PowerPoint Karaoke"[0] where a presenter is given a deck of slides they've never seen and have to present on it. With a group of good public speakers it can be loads of fun (and really impressive the degree that some people can pull it off!) 0. https://en.wikipedia.org/wiki/PowerPoint_karaoke

If you like this, search on YouTube for "Harry Mack". Mindblowing

Re: GPT‑5.3‑Codex‑Spark

#322

Post by chaos_emergent »

freakynit wrote: post #239

Does this prove cerebras chips are generic enough to be able to run the most common architectures of LLM's? Even the proprietary ones?

Not at all, the limitation is software to get the model on the chip and executing correctly. My bet is that they had a FDE who specializes in the chip implement Spark’s architecture on device.

Re: GPT‑5.3‑Codex‑Spark

#324

Post by alecco »

tiffanyh wrote: post #231
pjs_ wrote: post #66

Continue to believe that Cerebras is one of the most underrated companies of our time. It's a dinner-plate sized chip. It actually works. It's actually much faster than anything else for real workloads. Amazing

If history has taught us anything, “engineered systems” (like mainframes & hyper converged infrastructure) emerge at the start of a new computing paradigm … but long-term , commodity compute wins the game.

Chips and RAM grew in capacity but latency is mostly flat and interconnect power consumption grew a lot. So I think the paradigm changed. Even with newer ones like NVlink.

For 28 years Intel Xeon chips come with massive L2/L3. Nvidia is making bigger chips with last being 2 big chips interconnected. Cerebras saw the pattern and took it to the next level.

And the technology is moving 3D towards stacking layers on the wafer so there is room to grow that way, too.

Re: GPT‑5.3‑Codex‑Spark

#326

Post by HumanOstrich »

jychang wrote: post #320
HumanOstrich wrote: post #315

Earlier quoted context omitted.

Not if you're suggesting that "(served by Cerebras)" should be part of the name. They're partnering with Cerebras and providing a layer of value. Also, OpenAI is "serving" you the model. We don't know how they integrate with Cerebras hardware, but typically you'd pay a few million dollars to get the hardware in your own datacenter. So no, "served by Cerebras" is confusing and misleading. Also "mini" is confusing beca…

Uh, that paragraph translated from "marketing bullshit" into "engineer" would be "we distilled the big gpt-5.3-codex model into a smaller size that fits on the 44GB of SRAM of a Cerebras WSE-3 multiplied by whatever tensor parallel or layer parallel grouping they're doing". (Cerebras runs llama-3.3 70b on 4 WSE-3 units with layer parallelism, for example). That's basically exactly what gpt-5.3-codex-mini would be. >…

Uh, the combined offering (smaller model + ~800 tps on cerebras) is nothing like the previous mini offerings, and you're hallucinating details about their process of creating it.

Read more about how Cerebras hardware handles clustering. The limit is not 44 GB or 500GB. Each CS-3 has 1,200 TB of MemoryX, supporting up to ~24T parameter models. And up to 2,048 can be clustered.

Re: GPT‑5.3‑Codex‑Spark

#327

Post by arisAlexis »

rvz wrote: post #88
lemming wrote: post #60

Earlier quoted context omitted.

Tested at Mistral’s scale is a very different thing to tested at OpenAI’s scale.

The scale of being "tested" clearly convinced Meta (beyond OpenAI's scale) [0] HuggingFace [1], Perplexity [2] and unsuprisingly many others in the AI industry [3] that require more compute than GPUs can deliver. So labelling it "untested" even at Meta's scale as a customer (which exceeds OpenAI's scale) is quiet nonsensical and frankly an uninformed take. [0] https://www.cerebras.ai/customer-spotlights/meta [1] http…

Meta didn't offer it. They offered the free llama version on their cloud. Maybe now Zuck will be conincrto buy their chips though

Re: GPT‑5.3‑Codex‑Spark

#328

Post by arisAlexis »

latchkey wrote: post #84
pjs_ wrote: post #66

Continue to believe that Cerebras is one of the most underrated companies of our time. It's a dinner-plate sized chip. It actually works. It's actually much faster than anything else for real workloads. Amazing

Not for what they are using it for. It is $1m+/chip and they can fit 1 of them in a rack. Rack space in DC's is a premium asset. The density isn't there. AI models need tons of memory (this product annoucement is case in point) and they don't have it, nor do they have a way to get it since they are last in line at the fabs. Their only chance is an aquihire, but nvidia just spent $20b on groq instead. Dead man walking…

How do you know the price of a unit ?

Re: GPT‑5.3‑Codex‑Spark

#329

Post by mikojan »

nikkwong wrote: post #29

> Our latest frontier models have shown particular strengths in their ability to do long-running tasks, working autonomously for hours, days or weeks without intervention. I have yet to see this (produce anything actually useful).

Agreed. Optimistically let it resolve merge conflicts in an old complex branch. Looked fine at first but was utter slop upon further review. Duplication, wildly unnecessary complexity and all.
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