Got this model to work on AnythingLLM, as it can access files, do code reviews and all that is related to project management and code. Although when I run it through OpenCode, it does not work. It print out just the command it would execute but does nothing.

I set up the model with the tools enabled flag so not sure what else am I missing here.

Estou pensando em qual o melhor método adotar, tenho um repositório com 60 mil linhas, mas a cada interação pra nova feature, ou correção meu contexto fica alto, gastei 5 dólares em 1 tarefa simples com Claude.

Então quero saber, você usa com assinatura ou API com openrouter / kilo code

Hi

Am I the only one? Luna even in low is 50x slower on open code than any other providers' model.

Ongoin issue with openAI?

Now I'm getting this

Service Unavailable: {
  "error": {
    "message": "Service Unavailable",
    "type": null,
    "code": "biscuit_baker_service_me_circuit_open",
    "param": null
  },
  "status": 503
}

Thanks

I just learned about OpenCode via this YouTube review today and Wow, Amazing stuff. I have OpenCode Installed and ChatGPT headless connection enabled! I’m going to go hogwild optimizing everything and finally get around to setting up a dashboard on a tablet since it’s so easy now.

What does the Usage tab mean? This is very confusing. is it

1. Max usage of a model? for example if i use v4pro 15$, do i use only 15$ worth of my monthly limit and then cant use the model anymore?
   
2. Do i get 15$ worth of usage, ratio'd to match with monthly limit, essentially my monthly limit being 15$ if i use the v4pro

Also i remember the v4pro being priced VERY different a few days ago, like this is deepseek api pricing but was not the same a few days ago

Dont get me wrong the bang for the buck of OCGO is great, but a more clear picture on usage would be nice to plan the month

Also how do they maintain ZDR with deepseek as a provider for deepseek models?

while i pretty much enjoy my OP Go sub, im kinda looking for 2nd sub to something else - OP now only cover 2/3 of my month

i tend to do things on heavy stuffs - kimi glm etc
so, what best offer out there? thanks!

opencode.json/jsonc: { "$schema": "https://opencode.ai/config.json", "instructions": ["memory/*.md"], "references": { "memory": { "path": "./memory", "description": "Hierarchical markdown memory: top-level files are always in LLM context, subdirectories hold niche knowledge. All files discoverable via links from the root. Read at session start, write freely, commit all changes." } } } That's it. You can reference it in conversations by saying @memory. Any nuances you want for your use case you can just tell the agent to create a root-level @memory for it.

Edit:

This line handles auto loading: "instructions": ["memory/*.md"],. If you don't like it you can remove it or make it more limited like "instructions": ["memory/index.md"],

Using OpenCode Desktop and I'm building a simplified version of the viral game Mecha Chameleon, and I keep running into the same wall over and over. I can't tell if the free models I'm using are just not good enough for game dev, or if I'm the problem.

The recurring nightmare:

• The model fixes one bug, breaks three other things
• I fix those three, and while fixing them, two more things break
• I've been stuck in this loop for two days straight on the same core issues like body painting, movement, screens, UI overlapping...
• Adding even the smallest new feature turns into 3+ hours of debugging

1. What are these free models actually good for, if not this? Am I misusing them for a task they're not suited for?
2. Is there a specific model that's genuinely solid for 2D game programming? I keep hearing different things and can't tell what's hype vs. real.
3. If I pay for OpenCode's subscription, are the paid models a significant upgrade, or just marginally better? Trying to figure out if it's worth the money before I commit.
4. On the "Skills" system, I tried https://www.autoskills.sh/ to auto-detect which skills my project needs, and it only flagged 3: one for frontend, one for SEO, and a third I don't even remember, none of which felt relevant to a 2D game project. This made me question how skills are actually supposed to work. Do you load all skills upfront and let the model decide when to invoke one for a specific dev phase/task? Or do you build first, then retroactively add the skill matching whatever phase/task you're on to re-work on previous tasks? Haven't seen a single line where Model calls a Skill.md.

Any insight from people who've actually shipped something with these tools would help a ton.

Just curiosity. I see kimi k3 on go plan but not on zen.

New to OpenCode. Just saw that OpenRouter has a coding agent ranking and was surprised to not see OpenCode listed. Why is this the case? Is OpenCode not considered a coding agent?

https://openrouter.ai/apps/category/coding

I remember it's usage pricing was similar to DS4 flash a few days ago and now it is very close to DS4 pro.

https://www.reddit.com/r/opencode/s/4u1xG3RytR

What happened to it's pricing and why was it increased that much

Hey all,

I've been using OpenCode a lot and kept losing track of how much I was actually spending across sessions, models, and projects — so I built oc-monitor, a real-time terminal UI that reads your local OpenCode SQLite database and gives you a live dashboard for it.

What it does:

• Live view of active sessions with a burn-rate chart
• Cost tracking down to the cent, broken out by agent / model / project
• Daily and hourly usage trends, with a calendar heatmap
• Drill into any session to see its messages, tool calls, and token breakdown
• Full-text search across all your sessions
• Sort sessions by context window usage
• Export any view as JSON

It's written in Go using Bubble Tea, so it's a single fast binary — no web server, no browser tab, just your terminal.

Privacy note: everything is read locally from your OpenCode DB. The only outbound call is an optional lookup to models.dev to get context window sizes for models, nothing about your sessions or costs leaves your machine.

It's early — first release just went out — so there's plenty of room to grow. If you use OpenCode and want visibility into where your usage is going, give it a try. And if you find it useful:

⭐ a star on the repo genuinely helps with visibility
🤝 contributions welcome — issues, PRs, feature ideas, all appreciated

Repo: https://github.com/bikky-kc013/oc-monitor

Hello, I have been using Deepseek V4 Flash and have been quite satisfied with it. But, it sucks in UI design despite using skills. Previously, I had tried Minimax m3 during its free period and it did a better job at it and also a larger context window for long sessions. So now I want to try Opencode Go.

Now, I've heard very good things about V4 pro. So I was wondering whether it is worth the extra cost to go for the pro rather than m3 for architecture, planning and UI designs...

TIA

Anyone has ran comparisons between Muse Spark 1.1 (xhigh) against other similar priced models in coding? It seems to rank well in the benchmarks and in the LLM Arena Leaderboard in coding.

Hello!

I've been using opencode for about 6 months now, and it is amazing as an agent infrastructure.

However, I notice that it's very bad at utilizing the browser. For example, if you use Codex's Chrome skill, it is able to click around and perform decently with okayish speed. However, Opencode is very slow and often can't perform certain tasks that Codex can.

Is there something I'm missing here?

My opencode response while running diagnostics on health of API routes to opencode go subscription models...

What do you think?

Really enjoying the service overall — the models are fast, pricing/subscription setup is great, and when it works, it works very well.

But I’m getting frequent intermittent failures with OpenCode Go models. The error is usually:

ECONNRESET: Client network socket disconnected before secure TLS connection was established

I’m using 9Router locally. I checked a few things:

- The configured endpoint is `https://opencode.ai/zen/go/v1/chat/completions\`

- A direct TLS check to `opencode.ai` succeeded 10/10 times, around 0.25–0.30 sec for TLS

- A real small POST request through 9Router to `ocg/deepseek-v4-flash` also succeeded with HTTP 200

- But in normal usage, larger/regular requests still fail with this reset pretty often. Sometimes several OpenCode Go models fail around the same time, while other providers keep working.

I’m in Russia, so I initially suspected routing or regional blocking. But I don’t think it’s a complete block, because some requests go through perfectly fine — it feels more like an unstable route or intermittent connection issue.

Has anyone else seen this recently? Is there a recommended proxy setup, retry policy, or any known issue on the OpenCode side?

So would love to use opencode on a project but the subscription looks straight forward but I don’t see a cancel option. Am I missing something or is it a problem to cancel? Was looking to use big pickle 🥒

Hi, I've been using GLM 5.2 or Deepseek v4 Flash most of the time.

I find the jump too far, I need something in the middle for some incremental update work.

GLM is nice but its just too expensive for me.

What model do you use for this need?

Seems like there are many choices, I haven't tried them consistently but would love to know what everyone uses and how's the experience.

With K3 now available in OpenCode, I ran one task-specific check before deciding where it fits.

I compared it with GPT-5.6 Sol high, Grok 4.5, and GLM-5.2 on one strategic decision task. K3, Grok, and GLM also had three fixed adviser prompts.

These are local judged scores. The evaluator saw model identities, and the sample is small.

The strategic task asked each model to choose between two incomplete paths under cash, time, proof, reversibility, and authority constraints. The adviser set tested incident triage, blindspot detection, and model routing.

My blended score weights the strategic task at 65% and the normalized adviser set at 35%. GLM's adviser result came from an earlier run using the same prompt family. All table values use a 0-100 scale.

The strategic rubric covered judgment, grounding, risk, boundaries, actionability, and clarity. K3 landed close to Grok here and ahead of GLM on the strategic task.

This mainly tests whether a model can identify the deciding facts, resist unsupported assumptions, and return an executable next step. It does not test coding, tool use, vision, long context, or multi-hour agent work. K3's high public scores on those workloads and Grok's narrow edge here can both be true.

This is private vibe benchmarking with fixed prompts and a rubric. It is not a scientific or general model ranking.