ljosifov

Sprint outdial NUAs :)

Wdym "sadly they don’t support using Claude Code"? For the longest time that's all Zai supported - Claude code. I'd run it via

  export ZAI_ANTHROPIC_BASE_URL="https://api.z.ai/api/anthropic"
  export ZAI_ANTHROPIC_AUTH_TOKEN="$ZAI_API_KEY"
  claude-zai() {
      { local -; set -x; } 2>/dev/null
      ANTHROPIC_BASE_URL="$ZAI_ANTHROPIC_BASE_URL" ANTHROPIC_AUTH_TOKEN="$ZAI_ANTHROPIC_AUTH_TOKEN" claude "$@"
  }
  $ claude-zai

I liked Claude Code to start with. But over time between 'CC cache thrashing undo' seetings (I see now accumulated in ~/.claude/settings.json) and Anthropic-anything becoming a liability - have not used it in while. ZCode is ok and use it to take advantage of the discount tokens on offer from time to time. But really glad to see that in omp (oh-my-pi) Zai is a 1st class provider, can be selected on it's own no configs shananigans needed. And fits in the overall picture. E.g. can select GLM-5.2 (now 5.3) assign role [plan] or glm-5-turbo [advisor].

Got reminded now of glm-5v-turbo - that 'v' was for vision - will try assign it role [vision] now in omp. See what happens. :-) Often times it's handy when describing gui problems if the harness/model 'can see'.

Atm OMP (oh-my-pi) with opencode-go subscription using deepseek-v4-flash-0731 (and mimo-v2.5 as advisor). Used pi before (still good, but too minimalist for all general use; works on Android under Termux btw) and OpenCode (which is ok too). I've used Codex the longest, but the $20 sub doesn't last that long. Before that Claude (and Claude on the web - about Nov'25), but nowadays with the new models not possible to do anything on the cheap sub. Got Zai (GLM-5.2) legacy sub to supplement too for variety. :-) Run local jobs on the 7900xtx (24gb vram - so dense models) batch bulk jobs. Non-dense models like nemotron-cascade-2-30b-a3b MoE run at 100 tok/s, looking forward to try the new lightning-3.5-30b-a3b. And got old MBP M2 Max 96gb uram (unified ram) for bigger sparse MoE models. Testing DS4F there under ds4 server/harness (too slow, 12-15 tok/s even with REAP25 reduced model), and (got agents) porting Ling-3.0-flash atm from llama.cpp -> ds4. Hoping only A5B (5B active, versus 13B of DS4F) will result in better tok/s. TBS. Back in Feb-Apr'26 looked local will be the only way to run llm jobs (plus 300w gpu job works out for office heating when cold), otherwise the ex-quota API payg costs would bankrupt me. But now with the oss weights models and providers like opencode - actually it's not only faster but also cheaper for me to run llm jobs on the api. Engines for local - llama.cpp for all, hipfire (mentioned) for the 7900xtx, and mlx on the apple ASI (that never quite work out for me). And ds4 trying forever when off-line :-) - e.g. on a flight - either ds4-agent, or ds4-server + agent pi. And I use Hermes as a general agent, non-coding agent, for everything that's not strictly coding.

Hipfire works on my 7900xtx best of all. Biggest surprise - Qwen3.6-27B dense does not grind to a halt with context depths all the way up to 250K! Measured at 1K, 8K, 32K, 64K, 128K, 192K, 250K - Hipfire speed holds close to 40 tok/s. Finished 5 days run of gpu 100% inferencing, Hipfire did not crash even once afaics. I assumed speed dropping like a stone on Qwen models was a feature/bug of the model, and "nothing can be done about it". Hipfire showed me wrong - pleasantly surprised there.

omp - current top, after using codex claude opencode pi that I still use too

Hear hear. IQ tokens to cheap to meter upon us. So many things changed since last week. Now I've had Prime agent session grinding into its 20-th hour still not giving up. Been using opencode-go since Go sub appeared. What made a difference was deepseek-v4-flash and mimo-v2.5 showing. Very similar middling models ~300b so light on the gpu. 1M context and hybrid archs - so one can actually make use of that 1M (don't grind to a halt like others). In OMP I have one the primary (default), the other one as /advisor looking over the shoulder and nagging. On opencode-go in credits counting they are the bottom-2 in cost, cheaper by 200-350 times than than the top-1. Last week with deepseek-v4-flash-0731 another jump - now it's closer to the top models then to the middle. Now I don't even need the /advisor probably. Still left it there it's sometime amusing the models back and forth. :-) DeepSeek offer /v1/responses api now with flash-0731, so setup Codex to use that too. I'm loving this :-)

Love pi. It's good to have a minimal agent, always welcome. Even if only to bootstrap install other agents. E.g. recently Hermes stopped installing under Termux (v0.19 - no, v0.18 - yes). Agent pi to the rescue: installed it under Termux (Android), started it, pointed pi to the Hermes github, asked for v0.18 specifically - and it did it. Cherry on the top - asked it to install a plugin from github I use (unmerged PR), did that too. Even if nowadays for coding I mostly use OMP (the pi with wheels and bells and whistles). For general computer use mostly use Hermes. Model-tied harnesses have their place e.g. Codex for me. I never know if it's allowed or banned using the sub from non-Codex harness - so stick with it. Even if only to have the 'canonical reference setup' to compare with and measure against.

Same. And I have come to use OMP (oh my pi) agent /advisor mode to put a 2nd model on the case (also mid-size one), reading everything. It can not block anything or change anything - just inserts comments in the text stream with 1 turn delay. Good portion of the time it's quiet. I'd say 1/2 of the time it's got something to say. About 2/3-rd of that the 'advice' is insubstantial or about something not-quite wrong. The good thing is the main model is confident - checks and then it stands its ground. Have not noticed it turning a right into a wrong b/c of advisor false alarm. And in 1/3-rd of the advice, it's a genuine defect teh advisor noticed, the main model works out a fix. This is my approximate feeling just observing the process, have not got collected the data. Afaik only OMP has advisor mode. Agent pi has plugin pi-omplike-advisor. For agent Hermes I had them code me an /advisor plugin (for now -0.1 old v0.18.x; yet to upgrade it to latest).

Hobbled - but not to death, the few times I use it (usually on a plane). I tried 2bit of a 20% REAP reduced experts. :-O That's the biggest that fits on my own h/w (3yrs old M2 Max 96gb). It's coherent, it does work, doesn't fall apart on casual use. IDK if better than dense 27b. Think 27b was slower on the same h/w. DS4F has got 1M context window. Nowadays with weeks long run hermes sessions, I get to 300k-400k context depths easily. The speed decline profile of DS4F with context depth increase is superior to any other model I try. (I try them all - love this stuff) Only previous model coming close on that is nemotron-cascade-2 (only 30b-a3b) - that also has 1M context window.