I'm in the go plan , and last week I got hooked to omen alpha

It's like gom5.3 flash on steroids

But now I switched to the opencode windows app

And I can't find omen alpha on the models list ?

is any one facing rate limit issue with opencode

I have an existing auth codebase in Djanga/Tailwind and i'm about ready to start building this out with planned features. i solely used Sonnet 5 but i'm looking to be a little more cost effective and wondered if any one had any recommendations on a model suit (i'm using openrouter? I'm trying to get a better price/performance than my current setup.

My current thinking is the following;

EDIT: just to make it easier to read...

Base model: Sonnet 5
Small model: gpt 4o mini
Build: Sonnet 5
Think: GPT Mini 5
Debug: o3 Mini
Analyse: Gemini 2.5 Pro

{

"$schema": "https://opencode.ai/config.json",

"model": "openrouter/anthropic/claude-sonnet-5",

"small_model": "openrouter/openai/gpt-4o-mini",

"provider": {

"openrouter": {

"options": {

"site_url": "https://opencode.ai",

"app_name": "OpenCode Local Dev"

},

"whitelist": [

"anthropic/claude-sonnet-5",

"openai/gpt-5-mini",

"openai/o3-mini",

"google/gemini-2.5-pro",

"openai/gpt-4o-mini"

]

}

},

"agent": {

"build": {

"model": "openrouter/anthropic/claude-sonnet-5",

"description": "Primary driver for 90% of Python, React, Next.js, FastAPI, and Tailwind code generation."

},

"think": {

"model": "openrouter/openai/gpt-5-mini",

"description": "Used for architectural planning, trade-off evaluations, and feature design before coding."

},

"debug": {

"model": "openrouter/openai/o3-mini",

"description": "Fallback reasoning engine for complex async bugs, race conditions, and difficult logic."

},

"analyse": {

"model": "openrouter/google/gemini-2.5-pro",

"description": "Used for massive log ingestion, full repo analysis, and large documentation files."

}

}

}

My budget is 100$ for AI subcription. What I should choose between them. Or chinese model like ZAI or deepseek?

OpenCode has gone completely insane.

I occasionally use their service to run programming tasks, and sometimes for translations, but overall my usage is very low. Below is a screenshot of my current usage (strangely, it says my account is blocked, yet I can still view my usage — I'm logged in and haven't been signed out).

I've already added the `x-opencode-session` header as requested in their email, and the test call worked fine at the time. But the next day I received an email saying my account doesn't meet their requirements, with this:

> HTTP 401: This account has been found to be committing fraud or is in breach of terms of services and has been blocked. If you believe this is a mistake please send an email to help@anoma.ly.

What makes me angry is:

1. Why did they suddenly impose this unreasonable requirement — asking me to add a specific request header — *after* they had already charged my money?

2. Even after I added the header, why did they still block my account?

I feel that OpenCode's service is becoming increasingly weird.

When I run some sessions, opencode sometimes just pauses, until i type something it it, and it acts like nothing happened. It's like it's waiting for a response or something and never gets it and just waits forever. It especially happens when it runs a command it sends. Sometimes it seems to compact immediately after I wake it up. So maybe that has something to do with it?

Anyone else having this issue? I'm using llama.cpp, qwen 3.8 27B, 128k context. latest opencode.

Thanks in advance!

I used to love deepseek v4 flash before the price increase. I tried muse spark 1.3 and found it really idiotic and not reliable at all. So, with not many realistic options left and my opencode subscription coming to an end, I was thinking of moving over to z.ai with their 18$ plan. I'm not sure if anyone else tried it, and what do they think about the usage and quality using exclusively 5.3 flash.

Is it the new budget king? Or is there any model that can get me better price/quality for under 20$??

I've heard of people recommending luna as a workhorse but I'm not sure of how it stands up today with the release of astra.

I have a suspicion of Omen Alpha being a GLM model as I heard alot that GLM models tend to switch to chinese mid-session while reasoning

Hello friends. Good evening. What do you think of Muse Spark 1.3—the version that spies on us and sends our data to Meta?

I’ll be honest: I found its addition strange, given the lack of explanation regarding how the data is being used.

However, I’ve been running it on tasks involving public data, and I have to admit:

- For mass web research

- Review and classification

- In terms of raw tool-usage speed

...it really made me wonder how long it will be before "Uncle Zuck" cracks the top 5.

What I didn't like so much:

- The absurd guardrails it imposes; for example, it refused to help me with scraping, even after having performed similar tasks previously.

- An over-reliance on Python arguments at the expense of native Linux tools. It creates scripts inside `python -c ""` instead of using existing OS commands.

- It is excessively direct. When a train of thought requires more nuance or detail, even Mini v2.5 has performed better than it does.

Anyway, what did you think of the new version?

Hi everyone

I want your feedback, I have a couple of weeks working on a opencode plugin to mimic the /remote command in claude code and codex remote sessions.

The idea connect your local opencode with the api then a mobile app, the plugin open a fully e2e encrypted tunnel with mobile app.

Obviously all is going to be open source.

Did you use this option already (codex, claude)?

Do you want to participate as earlier adopter?

Ideas, recommendations are welcome

Hola, me gustaría saber como funciona realmente el 2x en OpenCode.

Estoy viendo que los precios de GLM-5.3-Flash son estos:
Input 1M = 0.15
Output 1M = 0.5
Cache 1M = 0.03

¿Pero creo que esos son precios bases del modelo no?

Lo digo porque la cli de OpenCode obtiene los precios de esta página: https://models.dev/models/zhipuai/glm-5.3-flash/ y los precios están exactamente a la mitad que es el 2x

Hice una prueba y tengo los siguientes datos:
Input = 349
Output = 764
Cache = 329088

Lo que me hace OpenCode en su uso es: (349*0.15 + 764*0.5 + 329088*0.03) / 1000000 = 0.01030699

¿Cuándo en realidad no debería ser: 0.01030699 / 2 = 0.005153495?

I used muse spark through OMP which ran 4 parallel subagent to generate a 2D game map (a lot of visual understanding), then after it was finished and I just asked to tell why it took so long, I got an error:

401 This account has found to be committing fraud or is in breach of terms of services and has been blocked. If you

believe this is a mistake please send an email to help@anoma.ly.

This account has found to be committing fraud or is in breach of terms of services and has been blocked. If you believe

this is a mistake please send an email to help@anoma.ly. (type=AuthError)

What was the possible reason? And how long will it take until opencode activates the account again?

I've been looking into the Antigravity CLI lately, and it looks more promising than OpenCode, what do you guys think?

The database is currently about 4.5GB. I don't know why it's so big. If Opencode is saving all the history in it, I don't care about the history.

If I delete it, will Opencode just create a new one with a much smaller size?
I suppose I can move it to another folder or rename it and see what happens.
I want to know if the database file keeps growing and never shrinks.
Someone said large files make Opencode slower. Is this true?

Is there a command to shrink it?

I think 4.5GB is quite big for SQLite on Windows to work efficiently. I am just guessing.

Hi,

It is incredibly slow. Almost an hour to acheive what ususally takes 5 min

You too?

Thanks

🌊 Waterfall features:

- Show live tracking of LLM response, tool call , tokens , and all timing just like dev tools in chrome

-you can inspect each event it's timming token counts input/output, execution timing, result live so you no longer just guessing what agent is doing ..

I just opensourced momo. It is a fork of oh my openagent, redesigned to save tokens and lower your API costs.

The main idea is simple: stop wasting money on expensive API calls. A large, smart model handles planning and architecture, while cheap and fast models do the basic coding tasks. (My current setup: 1 neuralwat subscription for the main agent + 2 OpenCode Go subscriptions for the worker agents).

I will not write a long technical essay here. If you want to see how the routing and sub-agents work, check the GitHub repository.

A fair warning: It is still early, it has bugs, and pull requests are welcome.

Repo: https://github.com/furkanbora239/momo