Live data from Hacker News

Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

cerebras.ai

81–90 of 135 posts

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

#81
post #76

I have been using Z.ai's (creators of GLM) "Coding Plan" with GLM-4.6. $3/month and 3x higher limits than Claude Pro, they say. (I have both and haven't run into any limits yet, so I'm probably not a very heavy user.) I'm quite impressed with the model. I have been using GLM-4.6 in Claude Code instead of Sonnet, and finding it fine for my use cases. (Simple scripting and web stuff.) (Note: Z.ai's GLM doesn't seem to…

I just asked glm-4.6 how to setup a z.ai api key with claude code and it kept on saying it has no idea what claude code is...

Quite funny, actually.

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

#82
post #22

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,…

I was AI skeptic too a year ago , but recently i wanted a windows exe program to do the same as a complicated bash script on linux.

i gave the bash script to claude code, which immediately started implementing something in the zig language. after a few iterations, i had zig source code that compiled in linux , produced a windows exe and perfectly mimicked the bash script.

I know nothing about zig programming.

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

#83
post #22

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,…

Your post has inspired me to check them out. How do you use it, with their UI oe to power some other open source tool? Do you suggest that this thing is so fast its simpler now to quickly work on one thing at a time instead of the 5 background tools running in parallel which might have been a pattern we invented because these things are so slow?

you want to be using something like opencode in a terminal, not the web ui.

you’ll need to try it and see what the speed does to your workflow.

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

#85
post #81
post #76

I have been using Z.ai's (creators of GLM) "Coding Plan" with GLM-4.6. $3/month and 3x higher limits than Claude Pro, they say. (I have both and haven't run into any limits yet, so I'm probably not a very heavy user.) I'm quite impressed with the model. I have been using GLM-4.6 in Claude Code instead of Sonnet, and finding it fine for my use cases. (Simple scripting and web stuff.) (Note: Z.ai's GLM doesn't seem to…

I just asked glm-4.6 how to setup a z.ai api key with claude code and it kept on saying it has no idea what claude code is... Quite funny, actually.

Ask and you shall receive!

https://docs.z.ai/devpack/tool/claude

tldr

    "env": {
        "ANTHROPIC_AUTH_TOKEN": "your_zai_api_key",
        "ANTHROPIC_BASE_URL": "https://api.z.ai/api/anthropic"
    }
Although if you want an Actually Good Experience I recommend using Claude Code Router

https://github.com/musistudio/claude-code-router

because it allows you to intercept the requests and forward them to other models. (e.g. GLM doesn't seem to support search or images, so I use Gemini's free tier for that.)

(CCR just launches Claude with the base url set to a local proxy. The more adventurous reader can also set up his own proxy... :)

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

#86
post #28

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…

[deleted]

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

#87
post #85
post #81

Earlier quoted context omitted.

I just asked glm-4.6 how to setup a z.ai api key with claude code and it kept on saying it has no idea what claude code is... Quite funny, actually.

Ask and you shall receive! https://docs.z.ai/devpack/tool/claude tldr "env": { "ANTHROPIC_AUTH_TOKEN": "your_zai_api_key", "ANTHROPIC_BASE_URL": "https://api.z.ai/api/anthropic" } Although if you want an Actually Good Experience I recommend using Claude Code Router https://github.com/musistudio/claude-code-router because it allows you to intercept the requests and forward them to other models. (e.g. GLM doesn't seem…

Benchmark score

Humans : 1

AI : 0

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

#88
I used their $50 plan and with the previously offered Qwen3 coder 480B. While fast - none of the “supported” tools I tried were able to use it in a way that didn’t hit the per minute request limit in a few seconds. It was incredibly frustrating. For the record, I tried OpenCoder, VSCode, Quen Coder CLI, octofriend and a few others I don’t remember.

Fast forward to now, when GLM 4.6 has replaced Qwen3 coder in their subscription plan. My subscription was still active so I wanted to give this setup another shot. This time though, I decided to give Cline a try. I’ve got to say, I was very pleasantly surprised - it worked really well out of the box. I guess whatever Cline does behind the scenes is more conducive to Cerebra’s API. I used Claude 4.5 + Thinking for “Plan” mode and Cerebras/GLM 4.6 for “Act”.

The combo feels solid. Much better than GPT-5 Codex alone. I found codex to be very high quality but so godawful slow for long interactive coding sessions. The worst part is I cannot see what it’s “thinking” to stop it in its tracks when it’s going in the wrong direction.

In an essence, Cerebras + GLM 4.6 feels like Grok Fast 1 on steroids. Just couple it with a frontier + thinking model for planning (Claude 4.5/GPT-5/Gemini Pro 2.5).

One caveat: sometimes the Cerebras API starts choking “because of high demand” which has nothing to do with hitting subscription limits. Just an FYI.

Note: For the record, I was coding on a semi-complex Rust application tuned for low-latency mix of IO + CPU workload. The application is multi-threaded and makes extensive use of locking primitives and explicit reference counting (Arc). All models were able to handle the code really well given the constraints.

Note2: I am also evaluating Synthetic's (synthetic.new) open-source model inference subscription and I like it a lot. There's a large number of models to choose from, including gpt-oss-120 and their usage limits are very very generous. To the point that I don't think I will ever hit them.

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

#90
post #58

Earlier quoted context omitted.

The industry of "software" is so large... While I agree with web development going this route, I'm not sure about "everything else". You could argue that that's the bulk of all software jobs in tech, and you'd likely be correct... But depending on what your actual challenge is, LLM assistance is more of a hindrance then help. However creating a web platform without external constraints makes LLM assistance shine, tha…

Well, there are certainly kinds of code LLMs would struggle with, but people generally underestimate what LLMs are capable of. E.g. Victor Taelin is implementing ultra-advanced programming language/runtime writing almost all code using LLM now. Runtime (HVM) is based on Interaction Calculus model which was only an obscure academic curiosity until Taelin started working on it. So a hypothesis that LLMs are only capabl…

I took a look at the Taelin's work [1].

[1] https://github.com/HigherOrderCO/HVM

From my understanding, main problem there is a compilation into (optimal) CUDA code and CUDA runtime, not language or internal representation per se. CUDA is hard to debug, some help can be warranted.

BTW, this HVM thing smells strange. The PAPER does not provide any description of experiments where linear parallel speedups were achieved. What were these 16K cores? What were these tasks?

Post reply on HN