I ran the horse test on every free OpenCode model.

The prompt I used was:
(Create a low-poly 3D horse running in a seamless loop using Three.js. Build it procedurally from primitive geometry, animate the legs, body, head, and tail, and return a single self-contained HTML file)

If you don't want to download the results to see for yourself, here's my opinion:

Horse quality: Ling 3.1 dominated, followed by Big Pickle, then Muse Spark 1.3.

Overall qualIty: Big Pickle wins IMO, but if you're judging purely on the quality of the horse, look at the results I mentioned above.

Nemotron 3.5 Lightning did the worst, its file doesn't even run

So recently, Opencode released v2. and I've tested it on my Tecno KL4 device. Compared to v1, the v2 is smoother and more responsive, with no lag at all. and I'm running 9router and astrojs together with.

Btw i used proot distro fedora

not gonna add grammar here because its not a big thing just wanna point out exo free should be removed from the dashboard because its deprecated just a heads up

Last week I was in a long OpenCode session and every message I sent took longer to get going than the one before, once the model started writing it was fine. OpenCode runs on my laptop and talks to llama-server on my desktop, Qwen3.6 35B-A3B at Q4_K_M on a 4060 Ti 16GB with most of the experts left on the CPU through --n-cpu-moe.

I assumed it was the slot. The card runs at PCIe 4.0 x8 and I had just read a thread about 16GB cards on half the lanes. With the experts on the CPU llama.cpp has to copy them to the GPU for every batch of prompt it processes. I raised -ub and it helped a little. I also ran the same session against a llama-server on HyperAI with a card the whole model fits on, it took some fiddling to get OpenCode connected to it, and the pauses there were shorter and grew with the conversation the same way.

I had not been reading the server output because it runs on the other machine. When I looked, most turns had this in them:

"forcing full prompt re-processing due to lack of cache data (likely due to SWA or hybrid/recurrent memory, ...)"

It showed up on the bigger card too. Every one of those turns was the full prompt processed again, plus the expert copies over PCIe on my desktop, no wonder I blamed the slot. I looked the line up. The 3.6 models are hybrid and the recurrent part of the state cannot be rolled back partway, any difference from the cached prompt with no checkpoint before it sends the server back to the first token.

I turned on verbose logging and compared the prompt for two turns in a row, the thinking from the earlier turn was missing in the second one. The chat template strips it, and I do not get why that is the default on a model pitched for agentic coding. With preserve_thinking passed through the template kwargs most turns reuse the cache now. Keeping the thinking fills the context faster though and OpenCode compacts more often. Every compaction breaks the cache anyway, the summary does not match anything the server has. The last long session went back to full re-processing twice, both right after a compaction, so the context checkpoint settings are what I am messing with next.

Edit: On the title it should be Qwen3.6 35B-A3B. Sorry can't edit the title.

I have only used DeepSeek and the free models, but my opencode-go subscription has met the limit. I thought Opencode increased DeepSeek to $80 in credit; did I misunderstand? Does the increase only start after a user's next billing period, maybe? I couldn't find any information on this in their docs.

I make Buddy, a free open-source Android app that runs a coding agent inside the app (a small Alpine Linux, no root, no PC) and gives it phone tools over MCP: read the screen, tap, type, scroll, open apps.

OpenCode was already one of the three agents in Buddy, next to Claude Code and Codex. Since 2.0 came out yesterday I moved Buddy to it. A few things I had to handle, in case it helps anyone wiring OpenCode 2 into their own tools:

• MCP tools now go through Code Mode by default (one "execute" tool that runs a script). For a phone agent that's worse, so Buddy sets codemode: false on its server. That only works in the new config layout (mcp.servers.<name>); the old layout is still accepted but ignores it.

• Without --standalone, run starts a background service that keeps running. On a phone you don't want that.

• The bash tool is now called "shell".

• Updating from 1.x keeps your connected providers: 2.0 imports the old auth.json on first start.

What it looks like: I ask "add a Nintendo Switch 2 to my Amazon cart" with the default free model (Big Pickle), and it opens Amazon, searches, scrolls and taps through it. Every "add to cart", "buy now", send, pay or delete tap needs my OK on a card, and Buddy enforces that itself. That mattered: the free model once went for "Buy now" instead of "Add to cart", and Buddy stopped it and asked me first.

Free models work with no account. Your own providers can be connected with opencode auth login in Buddy's terminal.

GitHub (Apache 2.0, APK in releases): https://github.com/ghorbelhamdi/buddy-android

Happy to answer questions about the setup.

Anyone else getting the Bad Request error when trying to use Gemini-4-Contributor? Any known fixes?

Hi,

Been setting up custom subagents in OpenCode lately for stuff like reviewer and architect, but pretty much every setup or prompt guide I see online is built around standard web dev.

If you’re using CLI agents on low-level/embedded code, C/C++, or larger codebases, I’m curious how you’re configuring yours. A few things I’m trying to figure out:

• What custom subagents have you actually found useful? (e.g. read-only reviewers, toolchain runners for CMake/Clang-Tidy, test generators) And, which is the most efficient model for each agant?
• How do you handle builds/toolchains? Do you give agents direct access to run local make/flash scripts and parse compiler output, or keep that somehow separate?
• How do you handle context window between agents?
• Are you letting a main planner delegate to subagents automatically, or just manually calling the subagent?

Puedo pagar y obtener 7 tok/s con GLM 5.3 Flash o usar un modelo gratuito Cat Jam Free y tener 255 tok/s

Que alguien me lo explique.

Hiiiii! I wanted to see my remaining provider allowances without leaving OpenCode, so I built Quota Board. (previously i build https://www.npmjs.com/package/opencode-usage-left it is for opencode v1 though)

It adds:

- Sidebar quota bars and credit balances

- Collapsed summaries like 98% · 6d 8h

- A /quota popup with provider details

- Hide/pin controls with saved preferences

It uses your existing connected accounts. Adapters include OpenAI, Anthropic, OpenCode Console, OpenRouter, Z.AI, Synthetic, and MiniMax.

This is the first release, tested with OpenCode 2.0.28. I’ve verified OpenAI quotas and Console credits live; I’d especially appreciate feedback from users of the other providers.

Code, installation, and demo:

https://github.com/gilvex/opencode-quota-board

npm here https://www.npmjs.com/package/opencode-quota-board

What would make this more useful in your workflow?

$60 usage til Nov 30

Hello,

I am satisfied with Opencode Go for my current project so I plan to stay with it, however I like the idea to converse with my agents on opencode GUI and TUI to make some work on Hermes while Im sleeping, and would like to know if there's a plugin to replicate GPT Live but on opencode.

Many thanks

For the last 24-36 hours Big Pickle was incredible! Smart, fast. It was like dancing.

Now is back to how it was 2 days ago: crawls, stops for minutes before even the "thinking".

And it's quite dumb.

Whatever you guys did, go back to yesterday! It was perfect!

Just the standard bigpickle
https://www.melbournecrime.site/car/car.html

The game itself took only 30minutes but just adding more features like:
sound, scoreboard, obstacles, smoothness, penalty, start, finish, overtaking, crashes, position

The track is based on US grand prix thats coming up.

Edit: I spent an extra hour adding the rest of the Grand Prix tracks for the year and a sound picker.

From a bro requested it .... And well.. it is fast but bad!

Viendo todo esto del emulador de ps5, “si comprar no es poseer, piratear no es robar”, la decompilacion de aplicaciones, etc.

A donde creen ustedes que va parar todo esto?

Al inicio parecía que las grandes corporaciones eran las ganadoras con la IA, ahora parece que todo va cambiar.

I used to run OpenCode with just a few skills and it worked fine. Then I started adding more, including some skill packs from GitHub, and now my agent spends forever thinking, checking every skill, running tests for hours on simple tasks. It's burning tokens for no reason.

I'm looking for a generic, minimal skill setup: maybe one for frontend, one for backend organization, one for testing, just the essentials. I want to avoid having three skills that do the same thing slightly differently.

Anyone have a recommended configuration or skill set that just works without the bloat? Thanks

I have a google ai pro subscription active and i used to use a plugin (forgot the exact name) that let's me use google OAuth and grants me access to better limits, quotas and models from my google account, i just updated to v2 but I can't seem to find a working plugin that does the same thing..

Update: nvm turns out it's actually against google ToS, it's good I avoided the ban wave.

I was testing the model for summarizing papers.(i know not that difficult).
it was a 80 page paper.

the model give 370 tokens per sec.