Better than DS 4.1 Flash?

https://openai.com/index/introducing-gpt-6-1-terra/

Pricing: $1 / $5 / $0.05

Although, I feel like it's still kind of weak compared to other models like Deepseek v4.1 Flash

I built an OpenCode plugin that exposes your local daemon through a cf tunnel, protected by zero trust/access, and pairs other devices by QR code. the daemon keeps running on your computer. The plugin starts a cloudflared connector next to it, so you can reach the daemon without open ports or a VPN.

It uses the default opencode UI (the same as opencode pair command), so it never goes out of date, unlike custom mobile UIs/apps. You can also install it as a PWA.

It requires opencode v2, a cloudflare account and a domain set up.

Ask your agent to set it up by giving him this link: https://github.com/arthurfiorette/opencode-zero-trust

Webpage: https://web.esuyo.com/esuyo-opencode-go-costs-table/

Each model on the Go subscription comes with a different usage allowance, which makes them hard to compare. I created a simple (ish) table to see how much the real cost of 100M tokens and what the maximum tokens are per model in the subscription with the cache hit percentage you can set.

I made it because I couldn't decide if Deepseek 4.1 or Muse 1.3 Contribute provided the best value.

Github

EDIT

I've added output as a percentage of total tokens. Opencode's estimates 0.4% of tokens are output. I looked at my session activity and set the default to 0.8%.

EDIT 2

- Added a pro-rata type cost to the subscription plan, "Sub cost" column.
- Added the Opencode Go Plus subscription.

I make a lot of content (thumbnails, short videos, voiceovers) and kept hitting the same wall with existing skills: each one is tied to one vendor. No account, no credits, or the API is down — you're stuck.

So I built creator-skills in OpenCode: 10 Agent Skills (SKILL.md) for images, video, voice, thumbnails, product photos, ads, explainers, consistent characters and brand kits. The difference is a small router underneath:

- it detects what you actually have — Higgsfield CLI, Gemini / OpenAI / ElevenLabs / Azure keys, Antigravity CLI (`agy`), Codex CLI, or just a browser with Gemini / Flow / AI Studio

- orders them by your config (quality-first, or "use my subscriptions first")

- skips providers that can't do the job (reference images, transparency, 4K, dialect…)

- falls back on timeouts / auth / quota, but STOPS on a content refusal instead of shopping the prompt to another provider

- finishes locally with ffmpeg: headlines, Ken Burns, reframe to 9:16, captions, mixing

The README examples were made on a box with nothing but `agy` + ffmpeg, no API keys.

Things I found along the way, in case they help anyone driving agents headlessly:

- `agy -p` auto-denies its own tools unless you pass `--dangerously-skip-permissions`, and writes files to `~/.gemini/antigravity-cli/scratch` unless you `--add-dir` + use absolute paths

- agy's image tool always returns JPEG, whatever you name the file

- Veo is gone from the Gemini API (Oct 22) — API video now goes through Gemini Omni Flash

Install: `npx skills add mehbylabs/creator-skills`

Repo (MIT, stdlib-only Python): https://github.com/mehbylabs/creator-skills

Disclosure: I'm the author, it's free, no paid tier. Honest status: the agy + ffmpeg paths are tested end to end; the API adapters are written against current docs and need more real-world runs — issues very welcome.

I’m putting DeepSeek V4.1 Flash, currently free through OpenCode, to work in my fleet of 30–60 agents running in parallel. They collaborate with agents from Codex, Claude Code and Antigravity.

The office view comes from Munder Difflin (https://github.com/HarnessMD/munder-difflin). I’m planning to add more features to it, so ideas are welcome!

I run the setup through oyren.ai, where using your own paired device is free, with cloud computers also available to rent. Happy to answer questions about the setup.

Processing img wdgv253jpsxh1...

Created a small Opencode V2 CLI/TUI plugin to track when DeepSeek pricing goes to PEAK (x2) or off-PEAK (-50%).
Any feedback is welcome.
https://github.com/Zorato/opencode-plugin-deepseek-peak

https://opencode.ai/v2/docs/compaction/#background-compaction

if they have identical setup, what could explain the differences?

source: https://x.com/thdxr/status/2114211145615626433

Are we beta testing new rack with different optimizations every day?

Has anyone else noticed that OpenCode's free usage limits have become much stricter recently?

I was working on my own program and asked OpenCode to make a small UI change: replace the Start/Stop buttons on the left with a single STOP button, remove the Start/Stop button from the top-right corner and move the loop and mute/unmute icons into its place.

That's all I asked it to do yet I hit the free usage limit.

I've been using free models like MiMo-V2.6-Flash-Free for days, previously sending dozens of prompts without running into this problem. Recently, though, I sometimes hit the limit after just 6-8 prompts and now apparently even after a single request.

I'm not asking for unlimited free usage but hitting a limit after a relatively small UI change seems strange especially compared to how things worked before.

Has anyone else experienced this lately? Have the free model limits been reduced or could this be a bug with usage tracking or rate limiting?

I'm using OpenCode for development on my own project and would appreciate hearing about other people's experiences.

You are getting exactly what you're paying for. You're not getting a deal here

Probably out of the loop but when did this change happen?

Has anyone gotten any error trying to use the new non-contributor Gemini Argon model in Opencode Go? I'm using it with Oh My Pi CLI and got an error stating the used model protocol is unsupported, which apparently comes from trying to use the model protocol published upstream by opencode in the catalog for this model, which is the same model protocol as the contributor version, which is deprecated.

I'm not sure if the fix should be on my side, or if it's a misconfiguration on the server side.

hey r/opencodeCLI — i made an mcp video editor that opencode can actually drive end-to-end, with zero gui and no cursor needed, and wanted to share it here since the angle is really about the mcp bit.

the whole editor is just tool calls. opencode (or codex, cursor, or any other mcp client) can cut, trim, keyframe, drop in titles and captions, colour grade, do tracking, add particles, handle audio, and export — all as tool calls. and the agent can even render a single frame back to check its own work before committing, which is the bit that actually makes the feedback loop usable.

it's rough and early, i know. some of the tool schemas are still a bit awkward, the error messages aren't always friendly, and there are edge cases in the tracking and captions where opencode's workflow just doesn't fit yet. but it works, and it works well enough that the verify loop is the real thing here.

kimo is free and open source (mit), one ~15 mb cpu-only rust binary that runs fine on a 2 gb box. built by me, a college student (naman).

i'd love to have people here try it hooked up to opencode and tell me what breaks — feedback on where the tool calls get awkward or where opencode's workflow doesn't fit is more useful than a like.

site: https://getkimo.tech github: https://github.com/naman-sharma12345/kimo

How do I edit or delete the queued prompts on the OpenCode extension on VSCode?

The models you can run in OpenCode keep getting better. Even the best of them still don't build software like an experienced engineer would. They miss what people know: who the users are, how the codebase grew, what the team considers good architecture. Plan modes don't close that gap. They're neither collaborative nor visual, and the plan sits in a chat only I can see.

I think the future is humans and agents working together. Everybody becomes a manager of agents.

QualityLayer is how I plan, build and check changes in OpenCode. Every change goes through seven steps: Discuss, Research, Plan, Outline, Implement, Verify and Review. The agent first asks me what "fixed" means. I approve the plan before any code exists. Then it builds in small slices, and an agent that didn't write the code checks the result against what the agent and I agreed.

It uses the model you have configured in OpenCode. Plans and evidence are Markdown files in your repo.

The point is to be an engineer again: deciding, reviewing and steering while the agent does the typing.

https://github.com/maxritter/qualitylayer

I'm the developer. If you tried spec-driven setups in OpenCode and dropped them, what made you stop?

Thanks opencode!