Too bad you probably need something like an 8x B300 node to run this. Black Friday is coming soon though, but I fear this open intelligence will be pacing anyone's liquidity frontier so I'll probably keep trailing the frontier for a while with nvidia/qwen3.8-27B-NVFP4 on dual RTX PRO 4000 in TP=2. I can almost fit 450k context in there.
You could easily run it with SSD streaming on as little as 192GB RAM (The dense portion is around 115GB or so at native precision, and the remainder would fit KV and a cache for the most commonly referenced experts.) This fits Gorgon Halo, which is a reasonably priced platform. It would be slow, but still usable for high-value tasks.
> a flood of 8x B300 will be homelab ready in a few months
Haha, that's beyond wishful thinking, I'm afraid. We're not even seeing a flood of A100s (6 yo and several generations old). Every GPU is still being squeezed right now, and the trend will probably continue for the foreseeable future.
Last I checked AWS still sells EC2 instances using 2018 era GPUs. Most people underestimate just how much long tail demand there is and how long these cards last, despite the higher power consumption.
A lot of the data center build out has been bipartisan. Unless Dems realize they need to listen to their constituents to avoid a 2028 bloodbath (they probably won't), I wouldn't count on that to save us from RAM/GPU prices.
Doesn't seem to outpace DeepSeekV4.1-Flash by much. Hy4 also announced their models and they have tons of internal benchmark, and K3.1 doesn't score that high on those benchmarks whereas Opus5.5 does, so it seems K3.1 is benchmaxxed.
For reference, Hy4 Preview was a 770B model (49B active) + 10B MTP (0.7B active). Not nearly the same potential as Kimi K3 (which is 2.8T) wrt. real-world knowledge (which matters at the new frontier of advanced research and scholarly tasks).
Depends on what you're using it for. DSf is pretty good at executing planned coding tasks but it isn't very intelligent. K3.1 doesn't need to be a coding master if it can be a fable replacement.
Subtle quote from their website:
> Advancing the Frontier of Open Intelligence.
Too bad you probably need something like an 8x B300 node to run this. Black Friday is coming soon though, but I fear this open intelligence will be pacing anyone's liquidity frontier so I'll probably keep trailing the frontier for a while with nvidia/qwen3.8-27B-NVFP4 on dual RTX PRO 4000 in TP=2. I can almost fit 450k context in there.
You could easily run it with SSD streaming on as little as 192GB RAM (The dense portion is around 115GB or so at native precision, and the remainder would fit KV and a cache for the most commonly referenced experts.) This fits Gorgon Halo, which is a reasonably priced platform. It would be slow, but still usable for high-value tasks.
Possible data center bans incoming + tons of GPUs sitting in warehouses due to lack of power infrastructure to power them.
Perhaps a flood of 8x B300 will be homelab ready in a few months
> a flood of 8x B300 will be homelab ready in a few months
Haha, that's beyond wishful thinking, I'm afraid. We're not even seeing a flood of A100s (6 yo and several generations old). Every GPU is still being squeezed right now, and the trend will probably continue for the foreseeable future.
Last I checked AWS still sells EC2 instances using 2018 era GPUs. Most people underestimate just how much long tail demand there is and how long these cards last, despite the higher power consumption.
The world is bigger than the US. If the political climate in the US obstructs the build out, the build out will occur somewhere else.
>The world is bigger than the US
This is cope. It's cute that you think it's true, but it's not really much bigger than the US.
No, they'll be shipped off to Asia where technology is embraced.
>Possible data center bans incoming
A lot of the data center build out has been bipartisan. Unless Dems realize they need to listen to their constituents to avoid a 2028 bloodbath (they probably won't), I wouldn't count on that to save us from RAM/GPU prices.
AND developer cloud has an image for K3 running it on a single MI300x. Offloading to system ram can be quite decent.
I cant say how well that image works as I'm still waiting for them to approve my gpu access
Do you need 450k context?
I usually keep under 200k if I can help it for Claude/ open ai
And lower locally on my Mac to save on prefill.
Doesn't seem to outpace DeepSeekV4.1-Flash by much. Hy4 also announced their models and they have tons of internal benchmark, and K3.1 doesn't score that high on those benchmarks whereas Opus5.5 does, so it seems K3.1 is benchmaxxed.
For reference, Hy4 Preview was a 770B model (49B active) + 10B MTP (0.7B active). Not nearly the same potential as Kimi K3 (which is 2.8T) wrt. real-world knowledge (which matters at the new frontier of advanced research and scholarly tasks).
I'm not talking about Hy4 Preview. I'm talking about Hy4, it was announced this morning. - https://hy.tencent.ai/research/hy4
Depends on what you're using it for. DSf is pretty good at executing planned coding tasks but it isn't very intelligent. K3.1 doesn't need to be a coding master if it can be a fable replacement.
If someone released a 0.1bit quant I can run it. /s