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Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

cerebras.ai

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Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#21

Post by elzbardico »

renewiltord wrote: post #16

Unfortunately for me, the models on Cerebras weren’t as good as Claude Code. Speedy but I needed to iterate more. Codex is trustworthy and slow. Claude is better at iterating. But none of the Cerebras models at the $50 tier were worth anything for me. They would have been something if they’d just come out but we have these alternatives now.

I don't care. I want LLMs to help with the boring stuff, the toil. It may not be as intelligent as Claude, but if it takes care of the boring stuff, and it is fast while doing it, I am happy. Use it surgically, do the top-down design, and just let it fill the blanks.

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#22

Post by divmain »

I have been an AI-coding skeptic for some time. I always acknowledged LLMs as useful for solving specific problems and making certain things possible that weren't possible before. But I've not been surprised to see AI fail to live up to the hype. And I never had a personally magical moment - an experience that shifted my perspective à la the peak end rule.

I've been using GLM 4.6 on Cerebras for the last week or so, since they began the transition, and I've been blown away.

I'm not a vibe coder; when I use AI coding tools, they're in the hot path. They save me time when whipping up a bash script and I can't remember the exact syntax, or for finding easily falsifiable answers that would otherwise take me a few minutes of reading. But, even though GLM 4.6 is not as smart as Sonnet 4.5, it is smart enough. And because it is so fast on Cerebras, I genuinely feel that it augments my own ability and productivity; the raw speed has considerably shifted the tipping point of time-savings for me.

YMMV, of course. I'm very precise with the instructions I provide. And I'm constantly interleaving my own design choices into the process - I usually have a very clear idea in my mind of what the end result should look like - so, in the end, the code ends up how I would have written it without AI. But building happens much faster.

No affiliation with Cerebras, just a happy customer. Just upgraded to the $200/mo plan - and I'll admit that I was one that scoffed when folks jumped on the original $200/mo Claude plan. I think this particular way of working with LLMs just fits well with how I think and work.

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#23

Post by behnamoh »

nine_k wrote: post #18
behnamoh wrote: post #4

If they don't quantize the model, how do they achieve these speeds? Groq also says they don't quantize models (and I want to believe them) but we literally have no way to prove they're right. This is important because their premium $50 (as opposed to $20 on Claude Pro or ChatGPT Plus) should be justified by the speed. GLM 4.6 is fine but I don't think it's still at the GPT-5/Claude Sonnet 4.5 level, so if I'm paying…

> What kind of workflow justifies this? Think about waiting for compilation to complete: the difference between 5 minutes and 15 seconds is dramatic. Same applies to AI-based code-wrangling tasks. The preserved concentration may be well worth the $50, especially when paid by your employer.

they should offer a free trial so we build confidence in the model quality (e.g., to make sure it's not nerfed/quantized/limited-context/etc.).

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#24

Post by renewiltord »

elzbardico wrote: post #21
renewiltord wrote: post #16

Unfortunately for me, the models on Cerebras weren’t as good as Claude Code. Speedy but I needed to iterate more. Codex is trustworthy and slow. Claude is better at iterating. But none of the Cerebras models at the $50 tier were worth anything for me. They would have been something if they’d just come out but we have these alternatives now.

I don't care. I want LLMs to help with the boring stuff, the toil. It may not be as intelligent as Claude, but if it takes care of the boring stuff, and it is fast while doing it, I am happy. Use it surgically, do the top-down design, and just let it fill the blanks.

Give it a crack. It took a lot of iteration for it to write decent code. If you figure out differences in prompting technique, do share. I was really hoping for the speed to improve a lot of execution - because that’s genuinely the primary problem for me. Unfortunately, speed is great but quality wasn’t great for me.

Good luck. Maybe it’ll do well in some self-directed agent loop.

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#25

Post by conception »

behnamoh wrote: post #23
nine_k wrote: post #18

Earlier quoted context omitted.

> What kind of workflow justifies this? Think about waiting for compilation to complete: the difference between 5 minutes and 15 seconds is dramatic. Same applies to AI-based code-wrangling tasks. The preserved concentration may be well worth the $50, especially when paid by your employer.

they should offer a free trial so we build confidence in the model quality (e.g., to make sure it's not nerfed/quantized/limited-context/etc.).

A trial is literally front and center on their website.

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#26

Post by conception »

mmaunder wrote: post #19
gatienboquet wrote: post #10

Vibe Slopping at 1000 tokens per second

Yeah honestly having max cognitive capability is #1 for me. Faster tokens is a distant second. I think anyone working on creating valuable unique IP feels this way.

This us where agents actually shine. Having a smart model write code and plan is great and then having cerebra’s do ask the command line work, write documents effectively instantly and other simple tasks does sped things up quite a bit.

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#27

Post by typpilol »

bigyabai wrote: post #7
cschneid wrote: post #5

Earlier quoted context omitted.

so apparently they have custom hardware that is basically absolutely gigantic chips - across the scale of a whole wafer at a time. Presumably they keep the entire model right on chip, in effectively L3 cache or whatever. So the memory bandwidth is absurdly fast, allowing very fast inference. It's more expensive to get the same raw compute as a cluster of nvidia chips, but they don't have the same peak throughput. As…

For $50/month, it's a non-starter. I hope they can find a way to use all this excess bandwidth to put out a $10 equivalent to Claude Code instead of a 1000 tok/s party trick I can't use properly.

I feel the same and it's also why I can't understand all these people using small local models.

Every local model I've used and even most open source are just not good

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#28

Post by mythz »

AI moves so fast that Vibe Coding still has a negative stigma attached to it, but even after 25 years of development, I'm not able to match the productivity of getting AI to implement the features I want. It's basically getting multiple devs to set out and go do work for you where you just tell them what you want and provide iterative feedback till they implement all the features you want, in the way you want and to fix all the issues you find along the way, which they can create tests and all the automated and deployment scripts for.

This is clearly the future of Software Development, but the models are so good atm that the future is possible now. I'm still getting used to and having to rethink my entire dev workflow for maximum productivity, and whilst I wouldn't unleash AI Agents on a decade old code base, all my new Web Apps will likely end up being AI-first unless there's a very good reason why it wouldn't provide a net benefit.

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#29

Post by odie5533 »

I find the fast models good for rapidly iterating UI changes with voice chat. Like "add some padding above the text box" or "right align the button". But I find the fast models useless for deep coding work. But a fast model has its place. Not $50/month though. Cursor has Compose 1 and Grok Code Fast for free. Not sure what $50/month gets me that those don't. I liked the stealth supernova model a lot too.

Re: Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

#30

Post by NitpickLawyer »

Flux159 wrote: post #17

Was able to sign up for the Max plan & start using it via opencode. It does a way better job than Qwen3 Coder in my opinion. Still extremely fast, but in less than 1 hour I was able to use 7M input tokens, so with a single agent running I would be able easily to pass that 120M daily token limit. The speed difference between Claude Code is significant though - to the point where I'm not waiting for generation most of…

> For reference, each new request needs to send all previous messages - tool calls force new requests too. So it's essentially cumulative when you're chatting with an agent - my opencode agent's context window is only 50% used at 72k tokens, but Cerebra's tracking online shows that I've used 1M input tokens and 10k output tokens already.

This is how every "chatbot" / "agentic flow" / etc works behind the scenes. That's why I liked that "you should build an agent" post a few days ago. It gets people to really understand what's behind the curtain. It's requests all the way down, sometimes with more context added, sometimes with less (subagents & co).

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