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Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

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Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#43
post #21

I have a prediction. By the mid of 2027, we will have >200B MoE models running on basic consumer hardware. I am running Qwen3.6-35B-A3B locally on my 16GB mac with 7-9 tokens/second. Link - https://github.com/deepanwadhwa/samosa-chat This is a GPT4 level model running locally with a decent speed on a 16gb ram macbook air.

> I am running Qwen3.6-35B-A3B locally on my 16GB mac with 7-9 tokens/second.

That is no where near decent at all.

Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#44
Some ppl don't like to hear it. But I would assume that token costs when using an inference provider are cheaper than electricity of using locally.

If we just take into account output token generation for simplicity. With 5tps u get 18k tokens an hour. That would costs around 0.005USD from an inference provider.

I estimate that the server consumes probably around 500W during inference.

In Germany where 1kwh cost around 0.3USD, 18k tokens inferred locally would therefore cost 0.15USD which is 30x the costs of using an inference provider.

But for ppl who worry about their data, running locally might still be good. However, they should be aware, that it is much less efficient than using an inference provider.

The efficiency gap will also significantly increase as new GPUs will make inference much more efficient.

EDIT: I first thought it'd be 180k token, but thanks to someone mentioning in the comments, it is 18k. I guess with that, it will be tough unless u got electricity almost for free. Also, the inference providers are probably still using H200/H100 for those small models. Once they use GB300 or next year the new Ruby GPUs, inference will be cheaper by a factor of 30. By then, running local models will mostly be about privacy.

Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#45
post #27

Earlier quoted context omitted.

> on a decent speed But you said 7-9 tokens/second , that's not a decent speed. I'm not an expert by all means but in my local experiments, less than 12 to 16 tps is too slow.

I think that any workflow that requires the user to stare at the tokens being generated live is using it wrong. Delegate, don't stare! https://mikeveerman.github.io/tokenspeed/?rate=10&mode=text You think of an idea that you want to have the LLM process, queue it up, and go back to what you were doing. Once you've finished reading the next article on HN about a 5 tps Xeon, your task will be complete. It's kind of lik…

We aren’t there yet. Not for frontier development work at least.

Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#46
post #21

I have a prediction. By the mid of 2027, we will have >200B MoE models running on basic consumer hardware. I am running Qwen3.6-35B-A3B locally on my 16GB mac with 7-9 tokens/second. Link - https://github.com/deepanwadhwa/samosa-chat This is a GPT4 level model running locally with a decent speed on a 16gb ram macbook air.

I tried Qwen3.6-35B-A3B, but it couldn't generate a 50-100 line Clojure file without having broken parens mismatches. I know Clojure isn't super popular, but the syntax is pretty simple and the frontier models do fine with it.

Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#47
post #44

Some ppl don't like to hear it. But I would assume that token costs when using an inference provider are cheaper than electricity of using locally. If we just take into account output token generation for simplicity. With 5tps u get 18k tokens an hour. That would costs around 0.005USD from an inference provider. I estimate that the server consumes probably around 500W during inference. In Germany where 1kwh cost arou…

It's the "Race-to-Idle" situation all over again. It consumes less power to complete a task faster, whereas using "low power" hardware that draws max TDP for 30 minutes isn't very power efficient.

The privacy nuts have a better leg to stand on, but even then it's hard to believe that they're using on-prem AI to replace SOTA model inference. As cool as local LLMs are, a lot of the stuff people run is a novelty.

Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#48
post #30
post #27

Earlier quoted context omitted.

> on a decent speed But you said 7-9 tokens/second , that's not a decent speed. I'm not an expert by all means but in my local experiments, less than 12 to 16 tps is too slow.

i am working on making it faster but to me 7-9 tokens/sec feels very good. it was 0 tokens/sec a year ago.

Ignore the haters. What you've done is incredible!

Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#49
post #21

I have a prediction. By the mid of 2027, we will have >200B MoE models running on basic consumer hardware. I am running Qwen3.6-35B-A3B locally on my 16GB mac with 7-9 tokens/second. Link - https://github.com/deepanwadhwa/samosa-chat This is a GPT4 level model running locally with a decent speed on a 16gb ram macbook air.

How are the thermals? I noticed that running any serious workload locally heats system fast.

i have been optimizing for that. for now samosa is capped at using half of the avaiable cores and switching between them, which keeps the system 'less hot' as it would have been. i will also release better thermal control in the next release. at this point its basically sacrificing about 20% of the speed to keep the hardware less stressed (and hot).

Re: Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

#50
post #44

Some ppl don't like to hear it. But I would assume that token costs when using an inference provider are cheaper than electricity of using locally. If we just take into account output token generation for simplicity. With 5tps u get 18k tokens an hour. That would costs around 0.005USD from an inference provider. I estimate that the server consumes probably around 500W during inference. In Germany where 1kwh cost arou…

its 18k not 180k
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