scanfi retweeted
Hades 0.5, the Lampades release, bringing improved built-in web search
No API key. Six indexes and one REST endpoint, each query routed to the class of source that answers it, results fused into one list. Rust, like the rest of it.
On a set of 22 queries written after the constants were frozen: 0.75 for documentation, 1.00 for troubleshooting, 1.00 for entity.
The same engine scored 0.44 the first time I measured it on queries the tuning had never seen. Three bugs came out of that. A source missing from a weight table still competed at full weight, so Hacker News outranked Stack Overflow on error messages. A site's front page outranked the page you asked for. The classifier filed most documentation lookups as general, so the tuned weights never ran.
Ten patches later, the thing that fixed the last of it was not a weight. It was scoring with the binary instead of a script sitting beside it.
scanfi retweeted
For all llama.cpp Qwen3.8-27B users !
With dspine release from @TencentHunyuan, 27b now runs even faster.
Especially for maths and code 🚀
Speed run result of Qwen3.8-27B-UD-Q4_K_M on my RTX 3090 with dflash2 and dspine!
dspine is the fastest at every context depth i tested🔥
dspine vs dflash2 vs no spec
- 8k: 35.6 vs 26.6 vs 28.1
- 32k: 31.1 vs 28.0 vs 23.8
- 64k: 35.5 vs 23.0 vs 19.5
- 128k: only no spec fits, 14.6
Also llama-benchy uses a novel as the text, which is the worst case for drafting. on code and math it's way better, ~125 tok/s, 4.5x over no spec
- code/math: ~125 tok/s (4.5x)
- mixed chat: 90 tok/s (3.2x)
Trade off is context, on my 3090, dspine fits 64k for kv q8_0, with n-max of 7 max context increases to 98k.
gguf: huggingface.co/aj9o9/Qwen3.8…
You need my llama.cpp branch for now: github.com/Ajay9o9/llama.cpp…
THIS IS HUGE !!
Now you can run Qwen3.8-27B even faster !!
@TencentHunyuan just released DSpine for Qwen3.8-27B and it beats DFlash2 really well.
I ported this to llama.cpp and have created ggufs for it,
find all my drafters in my hf link below.
Since it's not supported in upstream llama.cpp, you can clone my updated fork and give it a spin.
- Baseline: 28.2 tok/s
- DFlash2: 50.6 tok/s.
- DSpine: 94–132 tok/s
DSpine's lead over DFlash2 is about 1.75x either way.
DSpine predicts more tokens per verify step on math and code (7.3–7.6 vs 5.7–5.8), which is where its big wins come from.
github.com/Ajay9o9/llama.cpp…
All information is provided on model card.
huggingface.co/aj9o9/Qwen3.8…
I have been using Hermes Agent every day since day one, and I think it is finally time for a full review.
As always, this is completely independent. Not paid, not sponsored. The good and the bad, nothing held back.
This review covers what I use Hermes Agent for, why you should consider it, and how it stacks up against OpenClaw, Claude Code, Codex, and Grok Bot.
Hermes has become essential for me. Let me show you why, starting with the first thing most of you asked.
Which models do I use inside Hermes?
The best thing about Hermes is that it is truly model-neutral. It does not degrade the models. Whatever a model can do, you get directly.
I use GLM 5.3 a lot, and for light and medium tasks it is excellent. Sometimes I switch to GPT Sol 6.1, and I have noticed that the best place to run GPT is Hermes, even better than Codex. I have tried a lot of models in Hermes, and they were all excellent.
So use any model that suits you, as long as the plan is generous, and run two or three at once if you want. Here is the important part: in ninety percent of use cases, your choice of model will not make a big difference. The model here is still just a brain behind bigger layers, and those layers are what control how it behaves.
Usage limits and cost
There is no Hermes quota. Plug in your key, run a local model, or subscribe through Nous Portal. That is all it takes.
You can push Hermes to the max with excellent models without paying a single dollar. And if you decide to pay, you get great value for it.
Caching is great too
Out of 1,013 sessions, here's one that came out right at the average:
219 million input tokens
15.7 million output tokens
3.77 billion cached tokens
About 4 billion tokens in total
94.4% from cache.
Hermes is one of the best I have used for token efficiency, and the transparency is total. While you work, you see the real speed of every provider and every detail.
Light on the machine
Hermes is not heavy at all. One day I set up a full Hermes agent inside a virtual machine with just 2 GB of RAM, and it ran with very high stability on every kind of task I gave it. That shocked me. Codex, for comparison, eats tens of gigabytes of RAM. That difference tells you what an engineering masterpiece Hermes Agent is.
The layer above the model
One of the biggest things that sets Hermes apart is that the agent is separate from its brain. The model is the brain, and you can swap it without losing your memory, your skills or your setup.
Anywhere else, when I use GLM 5.3 I get GLM's usual strengths and weaknesses, and when I use Sol 6.1 I get Sol's. In Hermes there is a layer above the model that gives it a soul, a style and an understanding of how I work, so switching models matters far less. At some point the models feel eighty percent alike in style, in method and in the things you care about. What is left is raw capability, so the most capable models go to the hardest problems.
You own the layer you actually invest your time in. And the beautiful part is that this layer, the identity, the memory, the skills and every tool, is completely mine.
Look at Claude Code getting people banned today, at model performance suddenly dropping, at Codex being stingy with usage one time and slow the next. Those are constraints, and Hermes does not have them. If Claude Code decides to change or remove something, you have no say. In Hermes you can always change whatever you want. That is sovereignty, freedom and empowerment.
Memory that grows with you
When I opened the skills and memory tree, I found that Hermes had reached the point where it knows me better than any other agent. It grew with me through this whole journey, and that is what makes it the ideal partner for my work.
The journey command shows you a star map of your memory and skills, and you can edit or delete anything in it. It is one of the greatest things in Hermes.
One example: when Fable came out I loved it, so I had Fable pass its style and way of thinking on to Hermes. My Hermes became twice as useful after that.
And the instructions stick. Across sessions and updates, the soul, the identity and the instructions are always there. I never feel I need to remind it, and I never notice it forgetting or drifting. It is with me one hundred percent, every time.
Research and academic writing
Hermes is excellent for research and academic writing. With Claude Code or Codex I always have to explain my method, my way of thinking and everything I do not want. In Hermes I explained myself once, and from then on research and writing just happen the way I want. You set it up once, and it keeps growing. It even picked up my taste in design and research.
Skills and tools
Hermes has skills and tools you will not find anywhere else, and the team never stops building. The skills library is one of the best I have seen.
I see about 165 skills built in, plus optional skills and plugins you can add with one click. All useful stuff for growing in any field: iOS apps, computer use, automation, shopping, coding, organization, security, travel, testing, data, streaming, support, sports, reviews, video and more.
The tools cover web search, the browser, the terminal, files, vision, image generation, subagents, scheduled tasks, memory and computer use, and MCP brings in anything else. You can use it with Blender or whatever you want. Use it straight out of the box, or customize it with no ceiling.
Where I talk to it
You can talk to it anywhere: iMessage, Telegram, Slack, Discord and more, and you can customize all of it. When I am out of the house, Hermes is the first thing I think of. I send it a message and everything happens like magic.
My own voice model
Companies that take speech-to-text out of your credits always annoyed me. In Hermes I brought my own model. Everything runs locally on my machine, smooth and fast, exactly the way I want. I even send it voice notes on Telegram, and it just works.
The desktop app
The desktop app is great, and the user experience is one of the best I have seen. I do not like working in the terminal in general, so in Hermes the desktop app is my home.
What I use it for
The idea that Hermes is only for casual users or simple tasks is just not true. It works for every kind of use and then some. I use it for everything I want, and I get great results.
It is the agent I rely on for personal tasks, light work and organization. The test videos and model comparisons I publish are edited entirely by Hermes; I do not touch them. It has helped me study and work, proofread academic research, translate books and documents, run a security audit on my ERP application, and a lot more.
Hermes vs OpenClaw
The most unfair comparison people make is Hermes vs OpenClaw. OpenClaw was a revolution in its time and started a huge wave, and it deserves credit for that. But it is nowhere near Hermes. Not in stability, not in reliability, not in consistency, not in capability. To me, OpenClaw is a tool some people enjoy for two or three days of experimenting. Is it something you can rely on and build projects, ideas and solutions on? Not at all.
Hermes is another story. It even beats tools like Claude Code and Codex. For me it sits in a different category entirely.
Hermes vs Claude Code and Codex
The reply I get most is: you can do all of this in Claude Code or Codex. Yes, you can. But in Hermes I do it the way I want, not the way the model or the company wants, and I enjoy the work instead of fighting the agent.
Hermes also refuses less than any agent I use, and that matters a lot to me. It is my first stop for anything that usually gets refused in Claude Code, Codex and the rest. A while ago I gave Claude Code and Codex a task and both refused. Hermes did it.
Hermes vs Grok Bot
Grok Bot has two real advantages. It works out of the box and it is easy, and it has direct access to X. Beyond that, Hermes crushes it.
Everyone is talking about how fast Grok Bot's quotas run out, and I can confirm it. I am on the Ultra plan, the $200 one, and it does not last me more than a day, two, maybe three. That is not sustainable. To be fair, usage limits are a problem with a lot of providers right now, not only Grok Bot.
The real difference is intelligence. Grok Bot is extremely low on intelligence right now. I ask it to execute a task and it just answers. I ask it a question and it starts executing. I cannot trust it. Its mistakes outnumber its wins, and it keeps telling me it cannot do this, it cannot reach that, this is a limit.
In Hermes, you shape the intelligence layer. I shaped mine to do nothing until it is sure what I want and has reviewed every detail and the full context. Grok Bot has nothing like that, and you cannot shape it. Believe me, I tried.
Do not confuse ease with quality. Grok Bot has a wonderful ecosystem, great templates and amazing growth. But you do not own the environment, you do not choose the kind of intelligence you get, and you struggle to make it through the week.
The problems
Hermes is not perfect, and you should know where it falls short.
Sometimes when I change the model in a session, the interface does not show it. The change happens; the UI just does not read it. Open a new session, come back, and you will see it was applied.
Steering is hit or miss. Sometimes a steering message redirects the conversation right away. But most of the time the agent ignores it completely and waits until the whole task is done, or it spends a really long time on the task before the steering finally kicks in. I always wish steering was instant so no time gets wasted.
Subagents are excellent, but sometimes Hermes hands me a result and then waits for the subagent's report, instead of waiting first and giving me one final result.
Computer use is one of the most important features for me, and it sometimes breaks and needs a real fix. It happened enough that I stopped using it heavily. It usually breaks under heavy work or with medium and weaker models, so give it your most capable models.
That brings me to the most dangerous problem. Weaker models can wreck your Hermes in minutes. You build your setup and the agent's understanding of you with a serious model, then a weak model starts making bad decisions and damages that whole layer. It can even break the app. MiniMax M3 broke my Hermes more than once with its hallucinations.
The fix is simple: stick to the leading, stable models, such as Kimi, Sol, GLM 5.3, DeepSeek Flash, and frontier Qwen models like Qwen 3.8 Max, and stay away from weak, hallucinating ones. Since I stopped using MiniMax M3, I have not hit this once. I do not know if it has been fixed, but I am not risking my stability to find out. What I really want is an optional protection layer for the memory, the soul file and AGENTS.md, so any edit shows up in the interface for me to approve first.
Long tasks can occasionally collapse in goal mode. The agent marks the task done before it is, or gets lost and loops. That happened a long time ago and has not happened since. It is rare and usually comes with weaker models, but I am mentioning it for transparency.
One for Mac users: more than once, an update left my desktop app stuck on an older version. The fix is simple. Quit the app and run hermes update in the terminal. If the app still shows the old version, run hermes desktop to rebuild it.
What I want next
Two things matter most to me.
First, a solid, easy mobile app with beautiful interfaces and that Nous spirit.
Second, an easy mode that works out of the box: add profiles by field, so a researcher, a programmer, or a writer starts from a ready base instead of a raw zero.
A model from Nous Research that understands Hermes better than any other model would be amazing too, but that is not central for me right now.
And I want Hermes to switch modes from natural language. When I give it a goal, it should turn on goal mode by itself and finish the whole task, the way Codex and sometimes Claude Code do.
The community and the team
One moment made me appreciate Hermes more than ever. I wanted Arabic support in the harnesses I use, so I reached out to MiniMax, Zai and others and offered to translate the harness, the website, everything, myself. They all said yes. Then nothing happened.
With Hermes, I did the Arabic localization myself and opened a pull request. They accepted it, and today Hermes speaks Arabic. Your voice as a user is what matters, and that is exactly why I love Hermes.
Another thing that amazed me: one day I sent the team an idea right here on X. I wished I could set the model for each scheduled task. In less than three hours it was built and shipped, and I have been using it ever since. I have never seen that kind of speed. That is what accelerating growth looks like when a project is open source and the whole community builds it.
Where I stand
I have tried most of the well-known tools in the space, and every tool has beautiful positives and annoying negatives. Hermes might be the one with the fewest negatives. Not because it is better or worse than the others, but because in Hermes you can deal with a negative, change it, erase it, and sometimes turn it into a strength. It all comes down to how you customize it.
It is not the easiest tool to start with, so my next post is my full setup, as a skill. Hand it to your agent, answer its questions, and it sets everything up for you. I do not claim it is the best setup, only the one that fits me. Stay tuned!
After all this time, I know exactly where I stand. Hermes is a victory for what open source is supposed to mean.
scanfi retweeted
btw for these asking, this is literally our latest symbolic model
it learns to encode human knowledge as a bunch of top-level definitions on the untyped λ-calculus. no weights
yes, this talks to you. in English. at 1 million tokens/second
how it performs?
poorly
for now :')
hii, I have terrible news
turns out no big fund, among the ones I talked to in the last month, had enough conviction that HOC could become a profitable business. the most common feedback is "nobody will pay" and "big labs will eat you"
so, I've made 3 decisions:
1. a smaller round: $8m at $120m post-money cap
2. I'm investing $1m myself, same terms
3. we'll go all in on core AI research
HOC may die, but not today
~~~
# All in on core AI research?
some asked us to focus on a smaller product. that's bullshit. AGI is coming, who needs another shitty app? I'll just cut that off and jump straight to what I think can have real impact: fundamental AI research. we're a small fish, but we're also looking at places nobody is, so who knows, maybe we'll find something nobody else did?
plus, symbolic models are way more interpretable, so if developing them increases the chance of safe AGI even a bit, that's a better use of my time, and that's what I'll do.
we'll be posting our first SAI models soon~ish
~~~
# The smaller round:
we'll raise up to $8m at a $120m post-money cap, first come, first served, min $100k, SAFEs, closing this week. if you're an accredited investor brave enough to bet against the big funds, reach me at taelin @ higherorderco [.com]
I must be very clear: you're investing in whatever comes out of our symbolic AI research. Bend will likely remain OSS and free. so, in short, there is a 0.669% chance you're investing in OpenAI before GPT-2. most likely, your $ will disappear, as we still don't have a clear long-term revenue path
~~~
# How about Bend?
Bend is a core component of our symbolic AI research, so we'll keep developing and supporting it as currently (if with fewer tokens than I'd wish for 🥲). its development is nearly fully automated now, Bend3 is almost done, and it is getting faster and bigger every day. expect updates at an insane pace soon
~~~
that's it. sorry for the sad news. back to work
scanfi retweeted
0.4.5 let the agent keep the bytes every shell command was about to overwrite. Nothing ever removed them.
0.4.8 gives the journal a reaper. `hades prune` removes whole runs, oldest first, and the newest run is never a candidate, because a reaper that deletes the run you are working in is a bug with a schedule.
The limits section also said Telegram was the only messaging transport for five releases after Discord shipped as a pack. That line is parsed by the suite now, so it cannot rot again.
Which do you prune first, the runs or the claims?
An agent with write access is one bad step from destroying your work.
Hades Agent 0.4.0 saves the bytes of every file write before it happens. hades rewind <run> puts them back. If the file changed since the run left it, it refuses and shows you both digests instead of pretending the undo worked.
An undo that lies is worse than no undo.
scanfi retweeted
I kept this on the backlog too long, and many others may be as well. That was a mistake, because this little model punches hard
@NVIDIAAI Dory1.0-4B scores 60.67 of 66 on Agon, which is 91.92%. That is an exact three-way tie with Flint-40B-A3B and the Strata Qwen3.8 IQ1_M coder at 91.919%. Only LFM2.5-24B-A2B sits above the three, at 93.43%.
It is a looped model. 36 layers: 8 in, a 20-layer block applied four times, 8 out, same weights every pass. llama.cpp counts 192 virtual layers at four loops against 72 at one, so four loops buys 192 layers of compute on 2.23 GB of weights. That is the trade, four loops costs 2.46x the time per token for 1.00x the memory. Decode runs 71.5, 48.0 and 29.0 t/s at one, two and four loops on an RX 5700 XT with 7.98 GiB. That 29.0 is a median across 9,710 timed generations, not a burst test.
It wins no event. 6th of 34 on agent, 6th on code, 12th on reasoning, where 17 of 34 models sit above 95%. It places on consistency, on a bench where code is the event that separates anyone: the median code score is 61% and no model clears 95%. last_loop KV caching is free. Same speed as per-loop, but attention KV stops growing with the loop count, so decode holds at 29.1 t/s out to a 64k window in under 5 GB of VRAM.
The part that matters if you want to run it: it degenerates on hard code. Regex Engine took 3/4 twice, then 0/4 on the third run, 122 KB of output, 102 code fences, 21 minutes of repetition that ate the window. NVIDIA ships temperature 1.0 with top_k 0. I ran their settings as shipped. Nine runs took 8 hours 13 minutes. On an 8 GB card the loop is cheap in memory and expensive in the clock.
scanfi retweeted
i’m so fucking tired of watching politicians talk about superintelligence like it’s some consumer product they can just recall from the market.
we’re talking about the future of scientific discovery itself.
the stakes are incomprehensibly bigger than the political discourse surrounding them.
scanfi retweeted
With yesterday's elections results there is now no doubt that Local AI is the only way forward
scanfi retweeted
I took an Advanced Topics in Computer Vision for my masters in CS focused in AI. CSC 577. Top-tier American university, 2017.
I was the only non-Chinese student in the class. The professor was Chinese.
I arrived late for a class by ~ten minutes, walked in, and it was being taught in Mandarin.
This debate is insane
scanfi retweeted
If you’re actively trying to stop AI development, you’re my enemy and an enemy of humanity.
I consider what you’re doing a direct attack on humanity’s future.
Every disease that could have been cured, every life that could have been saved, every person who could have escaped poverty.
Every opportunity lost is a direct consequence of your actions, and those lives are on your shoulders.
You’re willing to sacrifice all of that because you’re terrified of progress.
I have absolutely zero tolerance for this.
Your movement deserves to be politically defeated, intellectually dismantled, and remembered as one of the greatest obstacles to human progress in history.
jesus fucking christ.
we’re potentially on the verge of the greatest scientific revolution in human history and the first instinct of some politicians is to shut it down.
i genuinely cannot comprehend this mindset.
scanfi retweeted
Everyone standing against AI is an enemy for all humans and a negative force on civilization.
scanfi retweeted
Imagine an Encyclopedia of knowledge crammed into a dataset with extended volumes for modern day coding, design, math, science.
And you can ask it questions in a prompt or verbally so it gives you answers.
Thats what AI is.
Do not be afraid of AI. It's a skill that improves humanity. Its just one big data set of encyclopedias of knowledge.
It is going to help so many solo creators and individual businesses be able to launch who didnt have the resources before.
scanfi retweeted
Replying to @RepYassAnsari
Your phd is in relations, sit your ass down and stay the hell out of the way of progress.
Im sick of opinionated paper pushers like you perpetuating this racist attitude that the chinese cant do shit and we can just pause AI like that will change shit. When you more than likely suck at excel and have no coded shit.
You do realize the box is wide open and never ever closing again. You will left in the dust of history and rightfully so for such a fucking myopic and moronic.
scanfi retweeted
my spidey senses are telling me the labs are, as we speak, using unguardrailed versions of their unreleased models to systematically reverse-engineer ALL of the internet’s software, apps, and games, then feeding the reconstructed source code straight into their training pipelines while simultaneously building guardrails to ladder-pull the rest of us
































