r/opencode

Should I buy OpenCode Go for 10$ and add 15$ on Zen for other models and extra usage if needed or just ChatGPT Plus for 23€ (or Google AI pro for 21.99€)? Which of these would be a better deal for coding? To use like 60/40 or 50/50 assistant, not fully vibecode.

Since OpenCode CLI supports multiple providers at once (/connect), I've been stacking ChatGPT Plus ($20) with OpenCode Go ($10) and it's a killer combo. Here's the breakdown:

🥇 ChatGPT Plus — Your "Chief Architect"

• GPT-5.5 Thinking for complex reasoning, architecture, system design
• Deep Research, Agent Mode, Canvas
• Use for the ~20% of sessions that need top-tier reasoning

🥈 OpenCode Go — Your "Engine Room"

• 14 open-source coding models (DeepSeek V4 Pro/Flash, Qwen 3.7 Max, MiniMax M3, GLM 5.1, Kimi K2.5, etc.)
• $10/mo with usage pool: ~$12/5hrs, $30/week, $60/month ceiling
• Throughput example: ~31K requests/5hrs on DeepSeek V4 Flash
• Zero-retention policy, global endpoints (US/EU/SG), OpenAI-compatible API
• First month is $5

🔧 Workflow in OpenCode CLI

Configure both in opencode.json:

{
  "provider": {
    "openai": { "options": { "apiKey": "sk-..." } },
    "opencode": { "options": { "apiKey": "go-..." } }
  }
}

Then /connect both keys and use /models to pick the right model per task.

Real patterns I use:

1. Architect → Builder — Design with GPT-5.5 Thinking in Plan mode, implement with DeepSeek V4 Pro in Build mode
2. Smart Review → Bulk Fix — GPT-5.5 for security-sensitive reviews, DeepSeek V4 Flash for mass refactoring
3. Research → Implementation — Deep Research for best practices, Qwen 3.7 for writing the code

Why it wins: $30 gets you top-tier reasoning and high-volume throughput. ChatGPT Plus alone is rate-limited on heavy coding. Go alone lacks the deep reasoning. Together they cover both ends.

full blog post: https://searchagentsky.com/r/9f8678e502d0-developer-power-stack-chatgpt-plus-20-opencode-go-10-opencod

Anyone else running a multi-provider setup in OpenCode CLI? What's your stack?

hi everyone. my free trial of chatgpt plus is ending soon. i’ve been using codex + gpt-5.5 mostly for vibe coding, and i really liked it (its my first time using agents to help with code actually)

i can pay for a monthly subscription, but not something like $100/month. my realistic budget is around $20, maybe $30 max

the main issue is limits. with gpt-5.5 medium i get around \\\\\\\~10 prompts per 5-hour limit when working on my project. my weekly usage sometimes drops close to 0% in about 3 days if i code a lot. if i code less, it can last almost the full week

is there anything close to gpt-5.5 for coding, but with more tokens or better limits?

i also looked at claude, but people often say it is expensive and burns through limits fast. is that true? would something like sonnet 4.6 / sonnet 5 on medium last even less than chatgpt plus? who have used/compares them both, what can you say about claude

i also tried opencode go for $5 with glm-5.2, but it was pretty bad for me. with around 250k context it somehow used about $9 very quickly. i don’t understand how it burned through credits that fast. they also have minimax m3, deepseek v4 pro and some other models, but i don’t know if any of them are actually good enough for coding (mostly typescript coding)

what would you choose for vibe coding under $20-30/month?

i really care about

1. code quality close to gpt-5.5(medium, i love when it one shots with code) or about that
2. enough usage time to actually work for a while
3. good handling of a larger project context
4. no surprise credit burn from huge context

should i just stay with chatgpt plus + codex, or is there a better option right now for price / limits / code quality?

For context, I have used the top frontier models before switching to Opencode Zen, and Opencode harness + Deepseek-v4-Flash is genuinely more than enough to get everything done.

• I rarely need/use visual input but if I do, I switch to MiMo
• I don't "vibe code" I plan and document the most important aspect diligently with good clarity before I push a prompt
• I manually define my data structure, architecture decisions, schemas, workflows for functions, and features. May clarify them on plan mode before implementation.
• Then I let Deepseek-v4-Flash implement the plans in build mode.
• I like to know how my code runs. It makes it easier to plan debugging or upgrades. And I make upgrades pretty often since I have active users. In the past, asking AI to make the changes without being tapped in just led to more work due to mistakes I did not know it made (even with Claude).

I know the other models seem to do better in benchmark testing but in experience with my workflow I have not seen much of a difference to justify the higher cost.

So I am curious

What are your go-to models?
How involved are you in your workflow?
When is Deepseek-v4-Flash genuinely not enough?

I've made a few posts here before because I'm interested in getting Cline Pass, but I'm still confused about the limits.

Has anyone here actually used it enough to understand how the limits work?

I'm not looking for guesses. I'm hoping to hear from people who have been using it heavily for coding for a while.

Have you run into any limits? If so, how often? Or has it been generous enough that you haven't really noticed them?

I'd really appreciate hearing some real world experiences before I subscribe.

1. SSS
   1. Mimo 2.5
      1. The usage you get out of this thing is nuts, you could spam billions of tokens a day without giving a single f, and its a great worker too and multimodal. Even if mimo 2.5 pro was price matched it would still fall below this absolute trooper.
2. S
   1. M3
      1. With the token plan you get a good amount of use, and the lowest hallu rate means we are making steady progress all the time, which is such a breath of fresh air compared to the either they can do it or not and back and forth you get with most when they are challenged.

I am not doing an entire tierlist for sure but also anything that doesn't give a good amount of use is effectively disqualified, or at most relegated to situational use. The strongest argument can be made for glm 5.2 for very demanding styling needs as both my picks are only good at it at, but outside top claude or glm you wouldn't get a meaningful improvement.

https://www.designarena.ai/leaderboard/code

Other argument can be made for a smarter unblocker or planner if needed, but still your choice would be a gpt sub or glm 5.2 in go / zai sub. Claude and gemini doesnt support integrating and they are worse value too, and others don't offer a big enough upgrade to justify it, but if you have very demanding intelligence needs constantly with clear roi then I guess the big codex and claude subs would be your choice. Most you have heard of don't have a model problem, they simply need a competitive deal against the best offers on the market. Currently almost no one makes their deal better or after they made it worse as a correction, but in general they stay the course and usually the release of a new model is dunk day, and say that their new guy is few percent away from top 1, then week later we see that it's not, so seemingly these 100 dollar lemonade stands are still more driven by investor hopes than market realities.

I'm not even halfway through the context window, but I'm wondering - what happens when the context window fills up? Is it opening another session? Is context loaded into this session? Is he starting to forget his chat history?

Anyone have issues with open code? It was fine earlier and the Zen works, but when I switch to Go i get 400 errors 401 and 403 errors. Im using it through Hermes and have rotate keys and tried different models but I still get errors. Im at 0% Rolling usage, 55% weekly usage and 47% Monthly usage with monthly resetting in 22hours.

I have been using opencode go for a month. Really good , started using GLM 5.2 this month and oh boy realised it is far expensive to use, my limits got exhausted so quickly and i have to survive for a month using this, Just wanted to know what other models are there in go that are relatively good or equal to it. Thanks

https://preview.redd.it/g432odiy2lbh1.png?width=1423&format=png&auto=webp&s=592ff05a0978901f17fe2761c0bcd6cd92a2313b

Fable 5 is now back! Here are some of the prompts you should run until the usage window closes:

1. Review all the code that was written after the date Fable was banned. Look for optimizations and improvements you can make

2. Walk through every major user path in the app you're building using browser control. Write a report on where users can get confused and what I can do to improve the UX

3. Make a checklist of every task you do from now until tonight. Then feed that task to Fable and ask what it could automate for you

4. Feed it all your goals, ambitions, interests, skillsets, and assets. Ask what simple businesses it could help build for you over the next few weeks o you can make your first dollar online

5. Connect to the X MCP and find 5 extremely helpful use cases other people are using Fable for that would be relevant to your workflows

6. Connect it to the X MCP. Have it read your last 100 posts. Come up with 5 SaaS ideas you could build

7. /loop it every 24 hours to do a security check on all your API endpoints in your existing apps

8. Use the Unreal 5.8 MCP to build incredible, in-depth, 3D games

9. Go to Sonnet 5 and ask based on what it knows about you, what would be some incredible prompts you can give to Fable tonight

Leverage Fable 5 to the fullest 🤖

I went deeper on this today because the Reddit threads were starting to blur together, and I had a feeling people were describing the same symptom but not the same cause.

After testing across multiple request shapes and multiple accounts, I’m pretty confident there are 2 separate problems getting lumped together:

1. Client fingerprint / header issue
If you hit OpenCode Go with a generic OpenAI-compatible client, you can trigger Cloudflare 1010 / access denied type failures.

So yes, there is a client-side layer here. Some requests are getting blocked before they even meaningfully reach the model backend.

2. Actual upstream/provider 500 issue
Once I adjusted the request shape to look like real OpenCode traffic, I could get some models to work normally.

But that’s the important part: some other models still returned 500 Internal Server Error on the same accounts.

That means the “just fix the headers” explanation is incomplete.

If headers were the whole story, then once the request fingerprint was corrected, everything should have recovered. That’s not what I saw.

Why this matters
Because right now a lot of people are probably talking past each other:

- one group is hitting the client/header/Cloudflare problem
- another group is hitting the real server-side 500 problem
- both groups report “OpenCode Go is broken”
- then everyone starts arguing over fixes that only solve one layer

What I don’t think it is
At this point I don’t think this is just:
- bad key
- bad account
- bad local setup
- random user misconfiguration

Not when you can make one class of models respond normally and another class keep throwing 500s under the same general conditions.

That points much more strongly to an upstream/provider routing issue inside OpenCode Go for certain model paths.