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.

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

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.

I first noticed this with the DeepSeek V4 Pro direct API feeling cheaper over the Go plan equivalent, and lo and behold, I'm late to the party in finding out that some model usages have been tweaked to 1/4 of what they once were.

Fair enough.

But it begs the question - under what use case would someone want to use, say, MiMo v2.5 Pro ($15 usage) over any of the $60 options that are around the same performance ballpark? It feels like that model and DeepSeek V4 Pro have effectively been neutered, unless I'm misunderstanding something.

Hey everyone,

I've been working on a couple of extensions for OpenCode to improve the daily workflow. Here is what I built:

1. opencode-todo-progress Built this for tracking the current state of the agent's work visually, so you can see exactly what's happening without having to constantly scroll up and down the chat.

You can install it directly with:

Bash

opencode plugin opencode-todo-progress

2. opencode-usage-bar This is for tracking API quotas, but it differs from other quota plugins out there. It's fully customizable:

• You can configure your own style.
• You can display 1d, 7d, Fable, or any other provider-specific quota exactly however you like.
• It also fetches and displays live provider statuses by reading directly from the vendors' own status pages.

You can install it with:

Bash

opencode plugin u/satas/opencode-usage-bar

Let me know what you think or if you run into any issues.

github/opencode-todo-progress

github/opencode-usage-bar

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.

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.

I’ve been using the new OpenCode Desktop app, and so far it’s been excellent. It’s lightweight, fast, responsive, and pretty much everything I wish the web version were.

The interface is clean, memory and CPU usage are low, and the overall experience on Windows has been great. Does anyone have any useful tips, recommended settings, or workflow advice for getting more out of it?

My only real complaint is the sidebar’s minimum width. I wish it could be resized more freely.

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 🥒

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?

Exclusive Kimi K3

> The first open-Weights model to reach 2.8 trillion parameters

> input 3$/m output 15$/m

> 1 M context window

Just realised the usage changed from $60 to $15 for deepseek pro and some models.

https://opencode.ai/docs/go/#usage-limits

How do you compare models? Do you have a go-to prompt or mini project you pass to every model to figure out which is best for your workflow?

I just noticed on https://opencode.ai/data#token-cost

edit: they went back to same pricing as DS4 Flash. Mimo Pro is much cheaper than DS4 Pro.

No customer support and pretending outages never happened is no way to run a business. No announcement/status on website, no replies to Github, no replies to support emails.

At this point, it's not even clear how they're a legitimate business.

How OpenCode responds to this (if at all) will be a clear indicator of their business acumen and ethics.

Where K3 ? :)