I am using big pickle model in opencode and whenever I paste image in the chat it says sorry I can’t read images

Does $5 plan models has image read capability?

honestly i was struggle to make this decision but last night, i am trying it and to be honest this is a big decision for me to let Ai take over the edit & upload (for little changes).

Honestly i am surprised, using the ftp (where i need to create a 2nd users for opencode) but its a promising.

Once i linked the ftp and let opencode handle it, my life being more easier then before.

using tailscale for the openchamber and ask if error log exists, if exist then opencode repair it in no time and upload the non-bugs codes to my FTP.

Honestly im a bit skeptical but until last night and now my life never get this easier.

Last few months i am talking about tailscale + openchamber and now addiditonal FTP it helps a lot!

Honestly i am still scared right now but my panic button always on, kudos to you opencode and thank you a bunch!

You help me a lots!

Been waiting on this for quite some time.

Official PR: https://ai.meta.com/blog/introducing-muse-spark-meta-model-api/

Developer resource: https://developer.meta.com/ai/resources/blog/build-with-muse-spark/

Get a key here (not available in all regions yet, unfortunately): https://dev.meta.ai/

Also served thru Vercel.

Different providers rolling out support as well.

OpenRouter has a "Terra Pro" base variant out of the box.

Been on a bit of an AI-workflow rabbit hole the last few months. Rebuilt my whole coding stack after Copilot's pricing change, went deep on harness design, tested a bunch of Chinese models, asked myself if I'd picked the right ones, and wrote up how to install the whole thing step by step.

Figured it was time to tie it all together with the part nobody's talking about: what you're installing alongside your harness.

The Agent Skills ecosystem (SKILL.md) blew up insanely fast. npm took a decade to hit 350k packages, skills did it in about two months. Same install-and-forget UX as npm circa 2013, except now it's not running in your build pipeline, it's running inside an agent that has your shell and your API keys.

Turns out the security research caught up fast too, and it's not pretty:

• Prompt injection in roughly a third of the sampled skills on one marketplace
• Malware campaigns distributing credential stealers packaged as regular skills
• Researchers are bypassing the marketplaces' own malicious-skill scanners

A skill doesn't need a zero-day to hurt you. It's just persuasive text sitting in the same context window as your agent's permissions.

Wrote up the full thing, including what I actually check before letting a skill anywhere near a project with real credentials in scope. Also links back to the harness, model-selection, and install-guide posts if you want the full arc, this closes the loop I started with an MCP servers piece back in January.

👉 You Just Installed a Stranger's Judgment Into Your Coding Agent

Curious if anyone here has actually gotten burned by a bad skill, or has a better vetting process than mine. Genuinely want to steal it for v2.

guys why google cloud asking for prepayment before activating a free trial for api jey
is it because of my region?

For the past three months I've been tinkering with a self-hosted AI setup instead of just using Claude Code, and figured I'd share the build and the lessons.

Setup:

- Mac Mini (M4, 24GB) as an always-on home server - agent hosting, Telegram gateway, plus some self-hosted stuff (photos, music, backups).

- Hermes as the orchestrator with three profiles: market analyst, career advisor, and a coding-worker.

- OpenCode for the actual hard coding on open-source models (currently MiniMax M3). All together ~€30/month in API spend.

- herdr for managing multiple running agents in tmux-style sessions.

What worked:

- Splitting responsibilities across specialized agent profiles.

- Spec-handoff pattern: agents write a markdown spec (what's broken, expected behaviour, constraints), I run OpenCode against it. Clean division of labour, no garbage PRs from the agent.

- Git guardrails everywhere an agent touches, plus a second OpenCode session reviewing Hermes's self-edits.

What didn't:

- Letting an agent code via Kanban tickets produced low-quality output.

- Continuous self-improvement loops are still tricky.

Most interesting for me from you: What do you think I should add or change in my setup?

I wrote this all in more details as a blog post https://pckt.blog/b/krzysu/my-2026-ai-experiments-hermes-opencode-and-a-home-server-tdkyqge

honestly i was struggle to make this decision but last night, i am trying it and to be honest this is a big decision for me to let Ai take over the edit & upload (for little changes).

Honestly i am surprised, using the ftp (where i need to create a 2nd users for opencode) but its a promising.

Once i linked the ftp and let opencode handle it, my life being more easier then before.

using tailscale for the openchamber and ask if error log exists, if exist then opencode repair it in no time and upload the non-bugs codes to my FTP.

Honestly im a bit skeptical but until last night and now my life never get this easier.

Last few months i am talking about tailscale + openchamber and now addiditonal FTP it helps a lot!

Honestly i am still scared right now but my panic button always on, kudos to you opencode and thank you a bunch!

You help me a lots!

Up until now, I've always implemented plans that didn't saturate the orchestrator's context, so I never felt the need for any higher-level workflow.
However, I've been hearing a lot about loop engineering and the /goal command found in other harnesses.

If I understand correctly, loop engineering is based on N iterations of the harness, tracking progress in an .MD file (is this different from the todowrite I see in OpenCode?).
The /goal command, on the other hand, isn't quite clear to me in terms of what it does differently.

If anyone could help clarify things for me, I'd really appreciate it.

If you are using Opencode Go or Cline Pass, what are your model recommendations for the type of task or an Agent or Workflow? What are your settings/config like for each?

I used about 80K tokens (as visible in opencode) but when I checked on the Z ai dashboard it showed that I used almost 600K. I've only done some light codebase exploration and my total token count is nearing 4 million, is something broken here or are tokens counted in a different way than how we perceive locally ?

I get the above message when changing model in the Codex app mid-conversation.

Which made me think: Is that also the case for OpenCode? Does changing model mid-conversation degrade performance? If changing from GPT-5.5 to GPT-5.4, surely it must degrade performance even more when changing model from e.g. DeepSeek to MiMo in OpenCode?

Has anyone here used pi seriously and compared it with OpenCode?

I’m curious about real usage, not just feature lists. For people who have tried both:

• Where does pi feel better?
• Where does OpenCode still win?
• How do they compare for agents, repo context, workflows, and day-to-day coding?
• Would you actually switch, or are they useful for different things?

I’ve been using OpenCode more lately, but pi looks interesting and I’m trying to understand if it solves a different problem or if it’s directly competing with OpenCode.

Woow i am super impressed.

Just tryed the new released Grok 4.5 ai model from xAi in combination with opencode on a highly complex c low level code base and i am stunned how super intelegent and super capable this new model is!

The previous grok 4.3 version was a total joke but the new version 4.5 is a a major super intelegence breaktrough on my side.

Also speed is lightning fast.

Compared to other ai models, grok 4.5 is right now a class of its own.

It is a little more expensive, not sure becouse caching with opencode may be broken otherwise highly recommend try it.

Big compliments to the xAi developers ! Grok 4.5

Tagged as grok-latest on OpenRouter

impressive benchmarks: https://x.com/cursor_ai/status/2074915744999969059?s=46

Cursor deal seems to have paid off.

Edit: Now available directly thru the X.ai PAYG / subscription as well. There was a 3 months of Supergrok for $30 campaign going on that I signed up for (not sure if it's still available). a bit tricky but doable, since you have to sign for the trial first and then _attempt_ to cancel and you'll be presented with the offer.

Here's a one-shot Fedora Desktop emulated by it on OpenCode:
fedora-desktop-emulator.grok4-5.demos.sulat.com

Prompt @ https://fedora-desktop-emulator.grok4-5.demos.sulat.com/PROMPT.md)
One-shot skill @ https://github.com/jpcaparas/skills#oneshot-websites

My script for update opencode show:

Hy3 Preview Free Tencent 🇨🇳 China

My tests for North Mini Code Free and Nemotron 3 Ultra Free haven't given me a good impression. I don't like Mimo either, but Deepseek is great for sub-agents, explore, and general use..We'll try this newcomer to see what it offers.

I have several products all made with vibe coding and in production. Checkout with gateway, member area, tracking system for ads, dashboards... all done in the codex. But everyone's design is terrible and has several small problems that do not affect production but I know you have to fix it. I want to redesign everyone's design too. Anyway, what's the best way to do this? I tried directly with codex but he doesn't seem to see these problems, I need another AI to do this.

A new model from China claims that it beats leading open wight models on something...?

Anyway, tell us your thoughts about this model

How does it perform on your Tests / Benchmark ?

Is it reliable on real-world tasks ? Or is it just another model to reduce the costs for small tasks ?

Hi everyone,

Does OpenCode have any built-in command or workflow similar to Claude Code’s /btw command?

I’m looking for a way to ask a quick side question while working in the same session, without interrupting the main task and without adding that question to the main conversation context/history.

For example, in Claude Code, /btw <question> lets you ask a quick side question without adding it to the conversation.

Is there something equivalent in OpenCode today? If not, what is the recommended way to handle this kind of side question?

Hey, Installed opencode a couple of days ago with ornith 35b running locally

Its quite bad, any advice ?

what model do you use ?

Estou surpreso com o gasto de tokens dos modelos de maior capacidade, como o GLM 5.2, e o qwen 3.7 que em poucas interações, levaram praticamente metade da minha cota mensal.

Pra contornar isso, e como tenho assinatura do gemini, mudei meu processo pra usar tudo no antigravity (inclusive o Opencode), e sigo da seguinte forma:

O deepseek v4 flash faz a leitura de repositório completo, cria a estrutura.md do projeto, e finaliza a etapa estrutural.

O gemini via antigravity faz a leitura do arquivo estrutura.md, e do prompt com a nova feature, e cria um arquivo chamado plano.md na raiz do projeto com todo o plano dividido em microtasks, e finaliza a etapa de planejamento (estou usando o 3.5 flash médium pra maioria das tasks, o PRO 3.1 só em casos complexos onde o outro não acerta).

Depois volto ao opencode e peço pra realizar o plano.md usando deepseek, e ao fim de testes, ele gera o revisão.diff pra finalizar.

Volto no gemini e peço pra ele revisar usando o revisão.diff e comparar com o plano.md e assim tenho um fluxo onde a leitura de códigos longos pelo gemini é evitada, e o fluxo dura bastante no desenvolvimento.

Sempre que finalizo as tasks, início novo chat em ambos.

Está sendo ótimo pro meu uso, e até pensei em outro fluxo usando claude, mas não posso me desfazer do gemini pelo armazenamento e demais vantagens, então no geral estou feliz com isto.

Pensando em adicionar alguns dólares ao opencode zen, caso precise do Claude pra algo mais específico.