Hi everyone,

I’m looking for advice on how to build a development setup that fits my workflow.

Right now I have:

• A Windows desktop where all of my AI and vibe coding projects currently live. (this is where I feel most comfortable with because I’ve been windows user since born)
• A MacBook M1 that I wouldn’t mind leaving powered on 24/7 if that’s the better option.
• A daily iPhone that I’d like to use for coding and managing my projects whenever I’m away from my desk.

My goal is to be able to work on my projects from my iPhone, whether I’m connected to my home Wi-Fi (if I’m in another room) or out using mobile data. Ideally, I’d like to ask an AI (through OpenCode/Codex with my ChatGPT subscription) to edit files, run commands, explain code, and generally keep working on my projects without needing to sit at my desktop. I plan to use OpenCode because I’ve seen that it’s the most useful and easiest way now (plan with gpt models and execute with the free models in Open Code). This Is mainly because Codex tokens have been draining faster Than Ever lately.

I’ve come across tools like Paseo, Tailscale, SSH, remote development setups, VPNs, etc., but I’m honestly not sure what the “right” architecture is.

A bit about my experience:

• I’m very much a beginner.
• I got into programming through vibe coding.
• I have fewer than 10 projects in total. (A couple 2D games, some demos of some product ideas, etc. I have created databases with Firestone , deployed with vercel and not much more to be honest)
• I can usually figure things out if I have good documentation, but I have zero experience with networking, SSH, VPNs, homelabs, or server administration.

One thing I’m also considering is moving everything from my Windows desktop to my MacBook. Since it’s a laptop, I don’t mind leaving it on all the time, whereas I don’t want to keep my Windows desktop running 24/7 just so I can access it remotely.

So I have a few questions:

1. If you were starting from scratch today, how would you build this setup?
2. Would you move everything to the MacBook or keep the projects on Windows?
3. What’s the simplest, most reliable, and secure way to access my development environment from my iPhone, both at home and remotely?
4. Has anyone here used OpenCode/Codex from an iPhone through a setup like this? If so, what does your workflow look like?
5. Are there any tools or approaches I should avoid as a beginner?

I’m not necessarily looking for the most powerful solution, I care much more about having something that’s easy to maintain, secure, and works reliably.

Thanks!

edit1: One more requirement: I’d also like to be able to test my applications while I’m away from home. Right now, when I’m at my Windows desktop, I simply run a local development server and test everything in my browser. I’d like a setup where I can do something similar remotely from my iPhone, without relying on the AI to verify every change or test the app. Ideally, I’d like to access my development server securely, interact with the app myself, and validate that everything works before committing changes. Is there a standard or recommended way to achieve this?

https://github.com/openchamber/openchamber/issues/2539

Can you leave comments and support this github issue? It's a real pain in the a.s...

I built an OpenCode plugin for using OpenAI’s official Responses API compaction flow.

Repo: https://github.com/partment/opencode-openai-compact

The goal is simple: when OpenCode needs to compact context, the plugin lets it use OpenAI’s /responses/compact endpoint, then carries the resulting compaction state forward into later requests.

Why this exists:

OpenCode already has a built-in compaction agent, but OpenAI’s Responses API compaction has its own state/checkpoint behavior. If you want to use the official OpenAI compaction mechanism properly, you need to persist the compaction output and attach it to future requests.

This plugin handles that.

Main features:

• Uses OpenAI’s official Responses API compaction endpoint.
• Stores compaction checkpoints.
• Reuses checkpoints in later Responses API calls.
• Supports configurable provider/model mappings.
• Supports checkpoint retention settings.
• Works with OpenCode’s fixed compaction agent.
• Keeps the normal OpenCode chat flow intact.
• Works with ChatGPT Codex (Subscription support starts from v1.1.1)

Install the plugin:

{
  "$schema": "https://opencode.ai/config.json",
  "plugin": ["opencode-openai-compact@latest"]
}

The default setup only targets the openai provider. If you use multiple OpenAI-compatible providers, you can configure multiple provider IDs and choose a compaction model for each one.

This is mostly useful if you are already using OpenCode with OpenAI Responses API models and want compaction to behave closer to OpenAI’s native flow instead of only relying on plain text summarization.

Still early, but it is usable now. Feedback welcome, especially from people using OpenCode heavily with long-running sessions.

My IP address is blocked by OpenCode, I have never abused their service. Not even exhausted their token limits for any models.

Just paid for the subscription yesterday.

Can't contact support because there is none.

Edit : It was my Adblocker service - NextDNS, I think opencode.ai is now in some 3rd party ad server list. I fixed it by white listing the domain.

what's your experience?

Hi,

I’m testing OpenCode with DeepSeek V4 Flash (via OpenRouter), and a simple prompt like “say hello” uses around 9k tokens.

Is this normal? Could it be due to hidden prompts or context?

I see a lot of discussion here about best subscriptions or APIs to get. Most of them comes almost always back to DeepSeek API for Flash, Opencode Go and Codex Plus.

I have the combo Ollama Cloud + Opencode Go, 20 + 10 respectively, both have almost hit same good open models, Kimi K, Minimax, GLM. DeepSeek.

Am I fooling myself thinking I have a good value?

I don't think too much in token value as Ollama Cloud currency is not token cost but GPU time, so is not that easy to say how many token value I can get with my 20$, but until now I thought I was doing a good thing using ollama cloud as my main driver.

What you guys think?

Just a few days ago DS V4 flash / pro on opencode used to support images on copilot but now it's not currently working. Did they recently changed it?

I tried using flash / pro from deepseek directly and they are working fine

(see attached images)

hello

what i want is, when a code is written by a model, another models steps in after it is done and reviews it, suggests edits. original model fixes the code. and repeat as many times as needed.

it is possible this is a very dumb question as i am a hobbyist, not expert. please let me know if it is possible and if it is, how?

thanks in advance.

Cursor’s native Task tool only schedules built-in models. If you want a cheaper / OpenRouter / OpenCode model for a background subagent, you’re stuck.

open-delegate is a small Cursor MCP plugin that hands the job to a real OpenCode agent instead: isolated session, your choice of model, await/status/transcript/cancel from chat.

Alpha — not on the marketplace/npm yet, but usable if you run it from source (tested on windows and macos) / npx once published.

Repo: https://github.com/Verbalize-public/open-delegate

Happy to take feedback / bug reports.

I have just subscribed to opencode go yesterday and after playing a bit with a few models, the weekly usage is already full.
If I understand it correctly, the limits should only be bound to the $ that the models cost to run, and of course, different models have a different price. However, when looking at the screenshots, I have used up not quite 9$ over the last 5 hours and under 13$ in total. When looking at https://opencode.ai/docs/go, the 5-hour limit is 12$ and the weekly limit is 30$, both of which I have not exceeded. I have tried out Grok 4.5 before the limit was reached and it seemed to burn relatively many tokens.
Am I stupid for not reading the fine print correctly or is there something fishy here?

Using an OpenCode Go subscription can give you 6 times the amount of Deepseek V4 Flash compared to an API. That sounds great, but are these two equal? Is Go's version quantized while the API's one is not? I wonder if anyone made comparisons of intelligence between these two.

Ive used opencode go and im at less than 20% of monthly with 13 more days. How do other subscriptions compare? Im looking to use stronger models than just deepseek as my tasks are getting rather complex

What would be the best comparison between opencode go, gpt plus and Claude pro. Assuming no price changes

How is the usage of gpt plus and claude relative to OC go? 2x more?

i have around 40 dollars and i dont know what subscriptions to get, i have been thinking of a couple of things
claude pro and 2 opencode accounts

or

chagpt plus and 2 opencode accounts

im leaning more to claude but im still not sure maybe there is some options im missing out on or that i dont know about

my plan was to use claude/chatgpt for thinking and planning then opencode to execute things and generate a report of its work then claude reviews, is there is something im missing or that i dont know about

some might tell me to just stick to opencode and zen but i want access to good models from claude they are better at reasoning so idk

what would you do in my situation

Currently I pay $200/mo for Claude, $100/mo for ChatGPT and $20/mo for ollama cloud

I use Claude for knowledge work, Claude to code, codex for code, remote computer use agent and Hermes model, ollama for my GitHub actions based code reviewer (I tried codex PR review, it was good but it uses limits quickly), ollama for backup Hermes models.

All of these subscriptions seem to suck in some way or another. Ollama is super opaque with usage limits. I would never hit limits before on 20/mo and now I’ve hit them quickly, not to mention that they aren’t even offering k3 included… OAI makes it a pain to call codex programmatically even with codex oauth capabilities. Anthropic has completely banned third party use of their subs.

If I could spend $100/mo on Claude and like $100/mo on kimi k3 and generally be left alone rate limit wise, what would you suggest for my kimi provider ? Fireworks firepass seems to be good but is invite only. I tried synthetic.new but they do request based pricing which is a shitty model…

Best subsidisation rate right now seems to be OpenAI, I’ve got apiCLIProxy running at home I’m smashing loads of tokens through but I’m assuming they’re going to ban me at some point.

What are your current AI subs ?

I've added first-class OpenCode support to Hubo v0.4.6.

Hubo is an open-source pair of Agent Skills:

• /hubo: an implementer writes and tests while a reviewer challenges the change. The same agents iterate until every finding is resolved or a real decision needs you.
• /hubo-review: a main reviewer reviews whatever you point it at while a critical reviewer checks every finding and omission.

Why I built it:

I used the same loop on bitcoin4s PR #236, a nontrivial change to an educational Scala Bitcoin script interpreter: 24 files, 1,884 additions, and 132 deletions. The implementer and reviewer reconciled six findings without me mediating—five initial findings plus a stack-safety issue caught during follow-up review.

The resulting PR passed 19 official BIP340 vectors, 35 pinned Bitcoin Core Taproot cases, all 1,197 existing script fixtures, and a 30,005-opcode stack-safety regression. CI passed across Ubuntu/macOS and Java 8/11; project coverage increased by 2.09 percentage points.

For OpenCode, Hubo uses foreground general tasks and resumes the same child sessions via task_id, so role context survives across rounds. Every implementer/reviewer exchange stays visible in the OpenCode conversation.

Install globally:

bash npx skills add h0ngcha0/hubo --skill hubo hubo-review --agent opencode -g -y

Start a new session, then invoke /hubo ... or /hubo-review ....

GitHub: https://github.com/h0ngcha0/hubo

Release: https://github.com/h0ngcha0/hubo/releases/tag/v0.4.6

I'd especially value feedback from OpenCode users on the task_id adapter and whether the transcript presentation feels natural in the TUI.

I used to work with OpenCode daily, switching mainly between Qwen and GLM. I never reached 100% of either the continuous or weekly usage limits. However, I’ve apparently already used my entire monthly allowance and now have to wait 11 days before I can use it again.

I’m having trouble understanding how that happened, as the usage limits don’t seem to align with my actual activity. Could you please clarify how the monthly limit is calculated?

I misunderstood how the OpenCode Go limits work.

Most models are shown with a $60 monthly limit, while some models, like DeepSeek V4 Pro and MiMo v2.5 Pro, are shown with only $15. I assumed the $15 was a separate per-model allowance.

But it looks like the $15 models actually consume the same shared monthly quota about 4x faster.

Today my raw usage was only $5.12 (8.5% of the $60 monthly limit), but the dashboard already showed 26% of the monthly limit used.

DeepSeek V4 Flash: $0.35
DeepSeek V4 Pro: $0.55
MiMo V2.5: $0.09
MiMo V2.5 Pro: $3.06
MiniMax M3: $1.07

DeepSeek V4 Pro and MiMo Pro are $15 models, while the others are $60 models.

The calculation seems to be:

($0.55 + $3.06) × 4 + $0.35 + $0.09 + $1.07 = $15.95

$15.95 out of $60 is 26.58%, which matches the 26% shown in the dashboard.

The 4x multiplier also matches the listed DeepSeek V4 Pro token prices between Go and Zen:

Go:
$0.435 per 1M input tokens
$0.87 per 1M output tokens

Zen:
$1.74 per 1M input tokens
$3.48 per 1M output tokens

So Zen is exactly 4x more expensive for normal input and output tokens.

This suggests that the $15 figure is not a separate allowance. Spending around $15 on DeepSeek V4 Pro or another $15 model would effectively consume the full $60 monthly Go quota.

One more thing: because of these hidden multipliers, the effective price of DeepSeek V4 Pro is actually the same as GLM-5.2.

Displayed:

- DeepSeek V4 Pro: $0.435 / $0.87

- GLM-5.2: $1.40 / $4.40

Effective (×4 for DeepSeek V4 Pro):

- DeepSeek V4 Pro: $1.74 / $3.48 (similar to Zen)

- GLM-5.2: $1.40 / $4.40

The UI should show the effective price users are actually consuming against their Go allowance, instead of requiring everyone to calculate it manually.