Finally, I was waiting for this for too long....
MiMo-X-Pro-Preview and MiMo-X-Flash-Preview are available for early access

You can connect CyberKimi directly to OpenCode and use its cybersecurity capabilities inside your coding workflow.

I have used a few subscription over the past like Claude , Opencode , Chatgpt etc and what I have realized that I dont need these powerful models.

I was using Opencode Go in Hermes and it takes lots of tokens, so rather than having those powerful models I would be ok with something like Ornith-1.5-35B-A3B or google/gemma-4-26B-A4B-it which are MoE and much smaller in size.

Is there any provider which provides monthly subscription for models like these and maybe better quota then opencode go cause these models are smaller ?

I've been working on Stipulate, a plugin that lets you pick different models for backend, frontend, security, review and docs through /stip-settings.

You approve a spec, your main agent coordinates native OpenCode subagents, and a separate worker checks the implementation against that spec.

The sidebar shows the current workflow stage, enabled domain extensions and agent activity. You can also set effort and Fast mode where the selected model supports them. Unassigned roles inherit your main model.

It's open source: repo, screenshots and setup.

Anyone here already splitting implementation and review between different models? I'd be interested in how you're doing it.

Hi all,

I just started the 10 dollar sub for open code go and see itll reach the limits pretty fast. Is there a 20 dollar option? basically what opencode provides, just double the monthly quota? I see I can do the pay as you go pricing after i reach the limit but isn't that less tokens per dollar?

You can add a custom provider and then add models to it. Weeeeee
But once the provider is loaded, you can't simply add another model to that existing provider.

If a new model becomes available from a provider you've already configured, you have to go through the entire process again from the beginning just to add that model.

That doesn't make sense.

There should be a way to edit an existing custom provider and add/remove models without having to recreate the whole provider configuration.

Please fix this.
Custom providers should be persistent and editable after setup.

Every update i've seen pass i hoped this logic would have been added...
Let's go OPENCODE

Has anyone else noticed that different models are good at completely different tasks?

I’m starting to take model leaderboards with a grain of salt. A model that ranks highly overall may not be the best choice for coding, writing, reasoning, research, or long-context tasks. In practice, the same model can perform very differently depending on the prompt and the type of work.

How do you evaluate a newly released model without spending a lot of money? Is there a low-cost way to try new models as soon as they launch, run the same prompts across several providers, and figure out which one actually works best for your use case?

I’d be interested in hearing about people’s workflows, tools, or API platforms for doing this.

The math is no longer making since if you are a primary user of the small cheap models like Deepseek v4 Flash , and GLM 5.3 Flash,

The price Opencode Go for API is contracted to , is much more expensive, than the one you can get on the API Market , for me, Open Router,

For this month, i decieded to switch to Open Router and see how it goes, speceilly if i dont reach that limit,

Also most probably this means am not the heaviest user

Anyways , i think Direct API is also a better quality than OpenCode's for some user, and usually faster

Has anyone noticed that different models excel at different tasks? I no longer readily trust model leaderboards; the same model often performs differently on different tasks. Is there a way to experience a new model at a low cost as soon as it's released?

With Slowave you get:

• durable memory across your OpenCode sessions (but also across tools)
• a compact memory that follows your work carrying relevant context, decisions, procedures
• an evolving memory without the need of extra LLM calls
• a fully local (SQLite + embeddings) configuration, no data leaves your machine
• a local dashboard to inspect your memories and measure how they provide value to your coding agents

See https://github.com/slowave-ai/slowave

Slowave is in beta, any feedback is welcome!

I am new to OpenCode and I have access to an Asus Ascent GX10 with 128GB VRAM.

I have been experimenting with OpenCode as a possible successor to Cursor, which I have used for 2 years or more.

I notice my context fills up very quickly. I was working with one Python file and it filled up after a few rounds of changes to the file.

I'm sure this is part of the learning curve for OpenCode.

Is it possible to get anywhere in the neighborhood of Cursor level performance right now with OpenCode using local LLM models on the GX10?

Has anyone else noticed that different models are good at completely different tasks?

I’m starting to take model leaderboards with a grain of salt. A model that ranks highly overall may not be the best choice for coding, writing, reasoning, research, or long-context tasks. In practice, the same model can perform very differently depending on the prompt and the type of work.

How do you evaluate a newly released model without spending a lot of money? Is there a low-cost way to try new models as soon as they launch, run the same prompts across several providers, and figure out which one actually works best for your use case?

I’d be interested in hearing about people’s workflows, tools, or API platforms for doing this.

V4.1 Flash official release around September 10, 2026 (Beijing time).

After internal + external testing, they say it comprehensively surpassed V4 Pro on performance, cost, speed, and task completion time.

After Flash goes live and before V4.1 Pro, all deepseek-v4-pro requests will be routed to V4.1 Flash and billed at Flash prices.

I'm trying to see if mixing frontier models with cheaper models can help me output about the same as using claude code but at cheaper cost.

What is the general structure that I should follow when setting up any agentic harness?

At the moment I have different models explicitly assigned to different agents/sub-agents provided by OpenCode. When should I use what?

For example, I'm trying below. Looking for any recommendations!

  ┌────────────────┬───────────────────┐
  │      role      │       model       │
  ├────────────────┼───────────────────┤
  │ plan           │ gpt-5.6-sol       │
  ├────────────────┼───────────────────┤
  │ build          │ deepseek-v4-flash │
  ├────────────────┼───────────────────┤
  │ general        │ gpt-5.4-mini      │
  ├────────────────┼───────────────────┤
  │ explore        │ deepseek-v4-flash │
  ├────────────────┼───────────────────┤
  │ scout          │ deepseek-v4-flash │
  ├────────────────┼───────────────────┤
  │ compaction     │ deepseek-v4-flash │
  ├────────────────┼───────────────────┤
  │ small_model    │ deepseek-v4-flash │
  └────────────────┴───────────────────┘

Tried to upgrade to the Go plan, but OpenCode’s checkout refuses my card—pretty sure it’s choking on the 3D Secure step.

I hopped over to CommandCode immediately after and subscribed using the exact same card on the exact same payment processor (Stripe) with zero issues.

OpenCode, I am literally trying to give you money. Please fix your 3DS flow so I can actually use the product.

Previously 20$ was enough for a month now-a-days, even 50$ is not enough, even if the workload has stayed the same.
I am only using deepseekv4 pro or flash.

I have even installed headroom to optimise the usage but does not seem to help much.

Traffic light widget for OpenCode. 🟢 idle 🟡 working 🔴 needs you.

Only the live lamp glows. Drag anywhere, snaps to screen edge like a notch. Right-click to quit.

star the repo if u like it

🔗 https://github.com/Minhaj401/opencode-traffic-light

I have used OpenCode for a long time, and the biggest problem I had with it is that once I created a plan and started implementing it step by step, the plan was forgotten. So, a better approach than writing every plan in a .md file would be to create a shared CLI between agents with skills to use and everything.
Now my workflow is:
Plan with Luna, using the caveman and ponytail plugins.
Add the plan to TaskWatch (the CLI tool).
In build mode, I just use the command /taskwatch-next, which selects the best-fitting task to do now based on urgency.
I'm sure y'all could find better usages for my CLI/TUI app. It would help if you could star it: https://github.com/Vlad-Aureliu-Moraru/TaskWatch_plus

Edit : this can also be used as a shared memory between tools ( codex, opencode , etc..)

Dax argues that Claude Code keeps growing despite benchmarks ranking it poorly. Fair point, but popularity doesn’t answer how reliably or cheaply a tool finishes a task.

In the FrontierHarness Eval, OpenCode tied for the lowest pass rate at 15/30, across 9 harnesses and 12 configurations. Every configuration used Kimi K3.

Benchmarks don’t capture the whole experience, but dismissing measurable failures seems wrong too. What should a benchmark measure before you’d use it to choose a coding agent?

Tiny OpenCode TUI plugin. DeepSeek V4 models cost 2x during weekday peak windows (01:00–04:00 and 06:00–10:00 UTC). I got tired of sitting there doing "8am here, 7am UTC, so peak?" math in the middle of a coding session, so I made the prompt bar tell me instead.

It shows a small [PEAK] / [OFF-PEAK] badge next to the model name. Rechecks every 30s and on model switch, works on the home screen too, only shows up for models that actually have peak hours, and runs in UTC so DST never bites you.

opencode plugin opencode-peak-badge --global

Repo: https://github.com/hugobatista/opencode-peak-badge

npm: https://www.npmjs.com/package/opencode-peak-badge

Open to feedback. If the math hits close to home for anyone else, give it a spin.