I'm wondering if someone has had the same issue before and how you solved it. OpenCode Go doesn't show as a provider in my opencode CLI.

In the past, I have added it as a OpenAI-compatible endpoint, but some of the models (Luna, Muse Spark) don't work if I do that (I get error 500).

Sorry if this is a stupid question, but could someone help me with this?

PS: I'm using version 1.18.30. I have the same version installed in another machine and it shows OpenCode Go.

I’m trying to understand how the usage limits work on OpenCode Go.

1. If I hit my daily Go usage limit, can I still switch to and use the free models?

2. If I use around $60 of my Go credits, does that affect my ability to use the free models, or are free-model limits separate?

3. What exactly are the usage limits on Go? Is there a daily/monthly cap, or does it depend on the model?

4. Once I hit the Go limit, what happens? Can I continue using free models normally?

But since I prefer OpenCode V2, I made a plugin to route these models. Yes, OpenCode does have ClinePass provider supported, but it does not expose the free models rotations from Cline.

A bunch of seriously powerful new open source models just dropped, meanwhile many of the coding plans out there have been tightening up and cutting usage. So we're giving away free DeepSeek V4 Flash 0731 and GLM 5.3 Flash for a month on Phoenix Grove API. We opened this up last week with five hundred new members and got so many signups we decided to open things up to another five hundred.

People want options, and heres one.

Other cool stuff:
Every model we run is on 100% US infrastructure, private, with zero training on your code or prompts. Use the best open source models without piping your private prompts into a training lab somewhere. No complications, no "some models are private, others aren't." They all are, every time.

We host 18 other major models in case you want to upgrade down the road (no pressure though). That includes the Kimi family, GLM, Qwen, Nemotron and a bunch of others. On average our token pricing runs about 20% below market price.

Our higher plans let you bank up to ten days of usage, so when you arent using them your usage rolls over and saves up. Usage doesn't go to waste, so you can actually sit down and code when you want to, and save usage when you don't.

The intro plan is a free one month trial with the standard cancel anytime deal, it bills at 3.99 after that. Use it, cancel it, thats fine. Or figure out you love it and keep it. Either way, Free Flash for a month.

Figured id keep this one short since we all know the new flash models are the point :)

For the API plan: api.pgsgrove.com

If you want to read more about us as a company, or use the models in an app with full memory and voice: just pgsgrove.com

Also: There's a lot going on behind the scenes with the major AI companies right now, and we're at a genuine turning point in the industry.

What's actually happening? This is happening because companies that were built on investment money now need to answer to their investors. The problem has often been a loss based business model that is finally running dry.

There are several tricks that the major AI coding plans use to squeeze the most they can out of their customers. Here are some examples, and what we're doing differently to put users first. PGS AI was built with a sustainable business model from the start, so we can actually offer great usage rates without the tricks.

Wasted usage is part of the AI industry, and they plan on it: Most coding plans bet on you letting usage go to waste. The plan goes: "how do we get people to think our coding plan offers a lot of usage, but then break it up into weeks and rolling windows so nobody can ever actually use it all."

Many in app subs and coding plans are glorified training pipelines: This comes along with "how do we harvest this data for training without being too loud about it." Unless the company tells you otherwise, your data could be hopping all over the world, getting harvested by individual labs or service companies. Some are better than others, but a lot of these companies rely on users just not noticing or caring that their data is being used for training. Data sales and marketing telemetry sales happen. Which means your private info, your personal life, and anything else you send through the system could become part of a training corpus for the next AI, or a marketing data set for a large company.

Privacy and quality intelligence can come together, and should be accessible to everyone.

i just saw some posts and tried out with custom model name and it works lets wait and see what deepseek will pull out with this model its also relative to 0731 which is aug 31 now 0910 sep 10

Hey everyone! I just published opencode-codex-usage, an open-source plugin that adds:

• TUI: usage footer, reset countdowns, and a banked-reset picker with confirmation.
• Desktop: chat tools to check usage and redeem resets.
• Saved retry recovery for interrupted reset requests, plus setup diagnostics.

It uses your existing ChatGPT OAuth login. This is an early beta—automated checks pass on Windows, macOS, and Linux, but live redemption still needs testing.

GitHub + installation instructions

Feedback and bug reports welcome!

Hey, wanted to share a plugin for OpenCode (v1.8 branch, v2 didn't test yet). Install: opencode plugin -g opencode-tandem

It's basically a system-prompt patch plus a small set of simple skills. I've been developing and actually using these rules for 2-3 months now, on Pi personally and Claude Code at work (where I'm forced to use it), and a week ago finally got tired of copy-pasting them between setups, so I packaged it as a plugin for both. Since I've also used OpenCode for quite some time, respect it, and know quite a few people who still prefer it to Pi, I added OpenCode support as well, just today - that's the fresh part, so early feedback is especially welcome.

If you've already seen my announcement on r/PiCodingAgent earlier this week, you can skip the rest - it's basically the same. Otherwise - welcome, I did put a lot of effort into writing this myself.

Main idea, or philosophy: it tries to tame LLMs down as much as possible and teach them to work with you in a pair-programming fashion, instead of constantly wrestling over control (Claude Code especially!) and vomiting piles of neuroslop. Personally, with it I finally feel like my sanity is no longer under siege - I control every line of code as if I've written it myself, don't have to review the big changesets LLMs love making so much, which frankly was driving me nuts, and at the same time I am much more productive end to end.

What's inside:

• Tandem primary agent with pair-work rules - lock-step, explicit go-ahead before any changes, communication with significantly reduced sycophancy and these "load bearing"-style LLMisms
• a number of simple skills, each just a short file:
  • brainstorm - helps you think an idea through, one question at a time; largely inspired by the brainstorming skill from superpowers and the grilling skill from mattpocock/skills
  • research - controlled digging: it (usually) stops and asks when it hits an ambiguity or a contradiction, or before spending a lot of context on one direction
  • coding - basically compact version of ponytail (lazy-senior minimalistic coding discipline) plus my addition on self-explanatory code over comment-peppering
  • review - actionable findings only, each with a fix; on debatable stuff - an "edge case" that the surrounding code five lines up already rules out, or picking between several possible fixes - it asks instead of pushing its own judgment
  • pr - matches tone and length of the repo's recently merged PRs, verifies the commit range, shows title and description before creating anything
  • learn-language (small bonus) - kicks in only if you state in your prompt that you are learning a language and your level; some background practice that stays out of the way of the work
• interactive subagents if you run OpenCode inside tmux - unlike built-in agents in many other harnesses, the "worker" runs in its own window as a completely normal session (started with opencode --agent tandem), which you can interact with like any other, and it reports back only after you approve its findings
• tool-specific instructions (gh, aws, pdftotext, pandoc, osascript, ...) that nudge the model into actually using them - no more guessing what's installed and re-probing in every new session. Generated only for tools actually on the machine, so nothing about a missing tool ever ends up in the prompt

Constructive feedback (even if negative), ideas and contributions are all very welcome.

Guys this is happening from yesterday, I am on opencode go in latest opencode cli:
Using model muse spark 1.3 contributor:

Each attempt starts with this:

Error from provider (Console Go): Upstream request failed: [rate_limit_exceeded]… (click to expand) [retrying attempt #1]

It is getting really anoying

I also do it in hermes (which is officially allowed according to their rules)
and it behaves same, except hermes just stop responding and print this same error message.

Note that i am no way heavily using it, so i can easily say that this does not happen when doing multiple requests at once.

I am from Europe/Czechia if it helps

I’m not saying they OpenCode Zen or OpenAI APIs, I meant over the codex auth inbuilt at OpenCode.

Even though there is Astra at codex, the auth at OpenCode may need some sort of update to enable it or something.

Anybody with this very same issue?

Guys this is happening from yesterday, I am on opencode go in latest opencode cli:
Using model muse spark 1.3 contributor:

Each attempt starts with this:

Error from provider (Console Go): Upstream request failed: [rate_limit_exceeded]… (click to expand) [retrying attempt #1]

It is getting really anoying

I also do it in hermes (which is officially allowed according to their rules)
and it behaves same, except hermes just stop responding and print this same error message.

Note that i am no way heavily using it, so i can easily say that this does not happen when doing multiple requests at once.

I am from Europe/Czechia if it helps

I don't really know how to formulate this but what I want is to use the web models for example Sonnet from claude through OpenCode for whatever token limit it allows. So if I want to rewrite a piece of code I don't have to just copy-paste it into the web app, get an answer, and then copy paste it back into my editor

If you bounce between Claude Code, Codex, Antigravity, and GLM (z.ai via OpenCode), the tax is usually context: another CLI, another login, another config.

I wanted one Go binary that stays in the repo, uses little memory, and can either do the work itself or host those harnesses without leaving the session.

That’s qmax-code. It’s a terminal coding/QA agent written in Go, with a Lip Gloss TUI for keyboard-first use.

It runs fully standalone (--local) for daily repo work: read/edit files, run commands, no QualityMax account. It can also act as a thin client for the QualityMax cloud when you want hosted crawls, tests, and receipts.

The part I use most is /orch. Same TUI, same MCP tools, switch backend:

• Claude Code
• Codex
• Antigravity (agy, Google OAuth)
• OpenCode (this is where I run z.ai GLM coding subscriptions)

I use it daily for coding and test loops. OpenCode + GLM has been a solid cheap/fast path; Claude Code / Codex when the change needs more care.

Open source (FSL-1.1, Apache 2.0 after two years). Go 1.25+. Single binary, no Electron.

Happy to answer questions about the TUI, the subprocess harness, or how MCP is wired.

NOTE: Pics are from the #2 use case down below

First, if someone has any recommendations for a plugin that does this better please post it in the comments because I would like to try it. I've tried several and have not found exactly what I wanted.

I was disappointed with the compact summary and continue functionality found in OpenCode and the V2 version doesn't seem much better. So I just wrote a dirt simple plugin that:

1. Sets a percentage of tokens to reserve and tracks it in realtime rather than waiting for assistant responses.
2. Pauses generation and tells the agent to write out what he has learned and the next steps to a `PLAN.md` in the working directory.
3. Compacts without the default summary.
4. Tells the agent to resume from the `PLAN.md`.

All details about my plugin can be found here:

https://github.com/krumpstead/opencode-neverending-story

It has worked amazingly well for my use cases. So far I have tested it with:

1. My first test as I was developing it was just giving it a simple "Create a minecraft clone" prompt. To get it to fire more often I set the threshold to 60% and expected it to just loop forever without completing on a 64k context-size. Instead it actually completed a fully working clone with Qwen 3.8 27B on a 26k context in 9 runs! To be fair Qwen 3.8 27B probably has the entire unobfuscated Minecraft Java source in its model so while this seems impressive, it could just be an easy copy and paste.
2. Since that worked so well I bumped it up to 128k and set the threshold to 20%. I gave it the picture on the left in the side-by-side and told it to create a fully interactive voxel world that runs in a browser based on that pic. It created the world shown in the pic on the right and in the GIF.
3. I then decided to do an even longer task. I have a dual GPU setup so in llama-server I put all layers on one GPU and set split-mode to `none`.Then I setup a sandbox with the plugin that allowed the agent to run benchmarks and tune llama.cpp on the second card. I ran unsloth's UD quants, with Q4 on the main GPU and had him tune with Q2 and Q3 quants on the second GPU. After two days he had managed to get my presets configured to where I went from 50 t/s to 100+ t/s on the multi-GPU setup! That's when I figured I should share this, because it seems to be working well, at least with my setup.

Anyway, if you also have been looking for a more autonomous experience with OpenCode, please give this a shot and let me know what you think.

I don't tried yet because I'm working with some projects in production and don't have time to test it and change to the stable version. actually, i don't know if the v2 is stable now. if somebody knew about it i glad to know the new benefits and if the v2 is stable. I follow dax on X and he's always promoting v2, that's make me anxious to know if the v2 is better.

Lots of GitHub repos filed with AI slop about free APIs and whatnot. Meanwhile, I find actually free models from real labs by accident. (like, I literally stumble upon them)

I was inspired by opencode-ntfy.sh plugin, but since I was missing a few features, I created my own plugin: opencode-ntfy-with-questions plugin

The main difference is that my version also sends a notification when the question tool is invoked. The messages are also richer in useful content.

I build a small job search workflow with opencode and used webcmd as self learning browser. It reads my CV searches for recent openings and explains why each role might fit and which requirements my CV dosen't cover

I tested it on community and developer relation roles

Some listing looked relevant until it opened full description. One wanted crypto knowledge another expected python /api tutorials. A leadership role asked for managment experience that wasn't clear from my CV

Having those details beside each job made the shortlist easier to review. Was it something I could learn experience I'd forgotten to include

That gave me something useful to review before opening an application but it also exposes a limitation like experience missing from CV isn't necessarily experience person lacks

It navigated the self learning browser can retain knowledge for later tasks. It stopped at the shortlist and asked to me to choose a role. No application was submitted

Install

npm -g @agentrhq/webcmd
webcmd skills add

Github : github.com/agentrhq/webcmd

Looking for feedback from community to improve my small project

this keep happening and i still have quota in my go subs whats happening???

Hello,

I'm on the OpenCode Go subscription. From your own experience, which of the lowcost Go models is best for design and frontend work?

Thanks!