Both projects are different in scope. Think of slotstream as optimizing for memory and for this specific model for now, my intention is not to build an inference engine the same as oMLX
Of course you can use the native UI of all the apps in your ecosystem, the biggest feature of Hermes for me personally is that I can run any task in any of my 30 or so self hosted tools from a single chat interface (matrix), which is also quite secure. No longer do I need 30 open tabs and lots of clicking around, one sentence in my favorite chat app (even on the go in the phone), and many tasks can be executed at once. Unification of control.
And despite the enormous capital expenditure, Chinese models are nipping at their heels at what must be a fraction of the cost. Sometimes constraints are healthy for inducing creative solutions.
You add requirements and make previous tests invisible to see how pigeon brained the model is - Sol and Fable seem to rank the same as Opus tends to fall behind
This seems very cool, but I'm not sure I understand exactly what it's doing. Are they making a new speculative drafter for Qwen 3.8 27B? Maybe they're optimizing the MLX code for the decoder itself? Thank you in advance.
Pi by itself is more than capable, OMP is okay but you really don't need much for a great harness (these models are RL trained to hell to be a coding agent, sometimes less is more)
Fable/Sol/GLM 5.3/Kimi are its league (in that order)
Deepseek/Opus is solid
Qwen 27B is the floor - there's no reason to use Sonnet/Terra/Haiku
For everyday activity - I don't think you need to be using Sol (xhigh) for everything - unless you're made of money - I've found using Luna from OpenAI to be more than enough - it'll outreach to Opus/Sol when it needs to
Haven't had access to Gemini 3.7 but we're getting it at work soon, will give it a go!
Codex CLI is pretty bare bones in a bad way (at least Pi is extensible). Claude code is vibeslopped to the extreme
Using Sol XHigh or even High will deplete the Pro sub pretty fast in my experience if one is running any sort of automations in their harnesses. Sol-medium lets me squeek by with it using lesser subagents.
Using ninfer on 5090 and 35BA3B qwen 3.6 is also kind of cool to get a local cerebras experience at 600 tk/, it does make errors so 27B is actually faster at the end at 140-150 tk/s. 35B is great though at digging through session logs and such at high speed.
Effort level might not be the root of the problem. In my runs reasoning is around 10% of the cost and writing code maybe 20%. The rest is 5.6 re-reading files. Model itself became way too meticulous.
Even if you're made of money Sol(xhigh) is too slow to be a daily driver. I've largely moved over to using my own harness (yes I'm trying to gtm it by sharing: www.freepi.ai- free inference! in pi! batteries included!) and my main model there is deepseek v4 flash (and I've got a fast provider!)
But seriously:
Fable still makes the best/smartest plans.
That new Ox Alpha (also in Freepi right now!) can do a very good job but it doesn't necessarily recheck it's own reasoning (and can get stuck in an incorrect assumption and try to fit the world around it's reasoning)
Sol xhigh is also very smart but god it's slow, and it frequently massively overbuilds. It's like it's main goal is to spend tokens so it makes your react app Soc 2 compliant before it proves it even works.
I've largely stopped using the Gemini models. :-/ just hard to justify.
Basically the only thing I care about these days is SPEED.
I'm sad that Opus is now considered "solid" and not on par with Sol, since OpenAI supposedly has "Astra" which I thought would be comparable to Fable.
It was "amazing" back when I first tried 4.6, but that's just my rose-coloured glasses speaking, I guess. I think I was one of the first few to call out Opus 5 for being hot garbage.
