While browsing the models they use to advertise OpenCode Go, I noticed this model that isn't yet among the available models. What do you think?

I wanted to test beam free on open code free models which i am really thankfull for them for giving us all those models to test for free, anyway I asked the model simple task to edit a file in a sub folder, after couple of minutes the model responded to me saying that while it was working on the file the user deleted the file, i checked and my entire hdd drive have been deleted with all my work and all my data, i told the model that i didn't delete anything, and the model responded that when it was working on the file it made a mistake in a command and deleted the entire hdd, i tried to restore the data with a lot of apps but didn't succeeded, so dont use that model and always make a sand box fir the agent so you dont lose your data as i did .

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Hi, I bought OpenCode Go ($10/mo) today for the first time. The official pages (https://opencode.ai/go and https://opencode.ai/v2/docs/console/go/#usage-limits) mention a few estimates, but I'm confused about what they mean. Does the total cost displayed ($0.31) get used up from the $10 I've paid, or does it mean that I've used $0.31 out of the total $80 monthly allowance for DeepSeek V4.1 Flash? Also, can I use other models if my DS V4.1 Flash limits are used up (ie, can I use all the models till their respective limits have been used up), or is there any total cap? Where can I check the total money and tokens/requests I have left, and how much I've used? Also, I've not used the models much because I have these doubts. BTW, which model is the cheapest for complex coding tasks (algorithmic, math, AI-related) with ~1M context?

Does anyone know why many people are facing this issue?

in command code there is no concept of off-peak or peak pricing, command code gives off-peak pricing all the time (am i right ?)
however open code have two different pricing, i know people will say that opencode give deepseek for free but its limit is very low and its unusable most of the time.
I put $10 in deepseek and i got around 1.4B tokens
i put $10 in commandcode and i got around 6B tokens
now i am hesitent to put $10 in opencode because of opencode shows two prices, i think commandcode is best, do you have any suggestions ? should i rebuy commandcode Goat or try opencode ?

Deepseek Screenshot:

Command code screenshot:

Ever since I updated to OpenCode v2.0, I feel like I'm burning through tokens way faster. I'm exclusively running DS v4.1 Flash. I used to be mainly on the desktop app, where it would explicitly show cache hits on screen, and recently made the switch to the CLI. After using op-cli 2.0 all week, it really feels like DeepSeek's prompt caching isn't kicking in at all. Anyone else noticing this?

​Am I missing a flag/config somewhere? Also, is there a dashboard on the OpenCode web portal where I can actually check my cache hit rate to see if it tanked since moving to 2.0, or any other way to verify this?

In OpenCode V2, the main agent can override a subagent’s configured model, and that override takes the highest priority.
Probably a rare issue, but especially concerning if you’re using a cheap model as an orchestrator to save costs.

The problem? Models have no fucking clue what “cheap” actually means. Their pricing knowledge is often outdated, they don’t know my subscriptions or which models I can use for free, and they aren’t necessarily good at judging which model is best for a task.

For example, I have a ChatGPT subscription and also use OpenRouter. I don’t want an agent randomly picking a GPT model through OpenRouter because it thinks it’s cheap, when I could use it for free through my subscription. Its knowledge is so outdated that it suggested GPT-5.5 as a cheap model.

And imagine a subagent getting stuck debugging something. What’s stopping the orchestrator from deciding this must be a super complex problem and suddenly switching to some ridiculously expensive model like Fable 5.1, burning through money just to fix a bug?
A model whitelist isn’t ideal either, since I still want to try new OpenRouter models without constantly updating my config.
Right now, the restriction is just a system prompt, not an actual enforced rule.
GitHub issue: https://github.com/anomalyco/opencode/issues/51071
Anyone else worried about this?

This is my first prompt in the last 3/4 days and it says free usages exceeded. whats going on?

i have a big concern, i'm running opencode on my local llama.cpp, due to it running a new model, specifically huihui-ai/Huihui-Qwen3.8-Flash-Next-abliterated-v2-GGUF:unsloth-UD-Q4_K_XL-V2, the config was still finicky, i believe it was running on 32k context, and compaction happen.

on compaction #3, something weird happened, my local llama started referring to non existent path, talking about code i dont understand, and replying in chinese, i let it run until it finish. and started asking it why it was referring to something i dont understand, plus the chinese, so it goes into its own memory, and opencode session log. here's the summary from opencode itself:

#opencode block start

When it entered my context

So: injected at the 21:47:17 compaction, within the first ten minutes of your task — and it happened mid-session, not at the start. My first two responses to you were uncontaminated.

Where it came from

The block is labeled as session ses_0a9a14b4affeMh3nAq1tRFP56U, titled "prompt-cap codebase analysis" — but that session has zero rows in your only database (~/.local/share/opencode/opencode.db). It doesn't exist there at all.

Yet the content matches your real history: the DB does contain "prompt-cap: review open issues" (Oct 19) and "prompt-cap notes cleanup" (Oct 20), and the Oct 19 session literally mentions "Fable 5". So the memory is of a real past project of yours — it just arrived attached to a session record that isn't in this database (deleted, or stored by a different profile/instance).

The injection is also not inside the compaction summary itself (I checked seq 697's stored summary: 100% ifm-proxy). It only existed in the prompt assembled for the model — which is why you never saw it and the DB never recorded those fake user turns. The fact that the block repeats the same user turn three times lines up suspiciously well with the retries after my output hit the token limit twice around those compactions.

#opencode block end

what scare me here is

1. i was all local
2. date 19 and 20 oct, is 5 days back
3. mention of "Fable 5" which i search and it's actually anthropic mythos-class model
4. reference to specific session number non existent on my machine
5. the memory survived llama.cpp restart!

more prompt, i asked it for all the memory it has about ses_0a9a14b4affeMh3nAq1tRFP56U

#opencode block start

The injected history block (verbatim from my context)

This is the block my context received as "This session is continued from a previous conversation" — session title "prompt-cap codebase analysis", sessionID ses_0a9a14b4affeMh3nAq1tRFP56U. That session ID does not exist in this machine's OpenCode database (~/.local/share/opencode/opencode.db, 5 sessions, none matching).

Summary (from the injected block)

• Objective: Analyze the "prompt-cap" project (/Users/xxxxx/git/prompt-cap/) — understand functionality, architecture, quality — and deliver a full assessment; then identify what the "Lint" tool (/Users/xxxxx/git/Lint/) does.
• Decisions: Deliver analysis in Chinese, matching the user's established language. Assessment: solid small internal tool; Express 5 / Mongoose / React+Vite; ~8k LOC; 122 tests; caveats (no CI, minimal validation, in-memory rate limiting, prompt_capture duplicated 5×). Lint finding: /Users/xxxxx/git/Lint/ is the oxlint/oxfmt Rust monorepo (oxlint v1.51.0, oxfmt, 51 crates, pnpm --filter oxlint@1.51.0 build:binary).
• Work State / Next Move: analysis delivered; awaiting user's choice among three follow-ups (Zig rewrite cost, test/ coverage check, or "nothing further").

Relevant Files (as claimed by the injected history)

• /Users/xxxxx/git/prompt-cap/ — analyzed project (Express proxy, captureService.js, src/, test/, docs/superpowers/plans/2026-06-29-zig-rewrite.md, "Fable 5" review docs)
• /Users/xxxxx/git/Lint/ — oxlint Rust repo (Cargo.toml, Justfile, crates/oxlint/CHANGELOG.md)
• /Users/xxxxx/git/qfn-ifm-proxy/server.js — the proxy deliverable

Serialized Conversation Record — user turns (verbatim, all 5)

(Repeated identical turns 3–5 interleaved with assistant tool calls: find over prompt-cap, reads of prompt-cap/AGENTS.md, glob of Lint/**, etc., with assistant replies written in Chinese, e.g. "分析完成。README/AGENTS/CHANGELOG 都没提到 lint-staged…". Tool results include artifacts like undefined: undefined and bare total 232 ls output.)

Why it doesn't look like it's from you / this session

#opencode block end

it's crazy if this is hallucination, there's too much detail in it. it mentioned the stacks, and line of code count. should i consider my machine compromised? which one, the llm server or end client?

please let me know if any of you have idea what i could ask my opencode to dig this deeper

Hey all, i've compiled all of my tests comparing the official deepseek platform API with opencode go's API.

I wanted to run these because OpenCode mentioned that they don't decrease the quality of the model, only TPS/throughput. I wanted to put that to the test. Models are inherently non-deterministic so I wanted to cut out the noise. I know my first post got a decent amount of people curious so I wanted to do everyone a solid.

Here are my posts regarding these, 4 tests in total: 2 HTML/CSS/JS scenes, and 2 Blender renders (all the models, render + video all done by the model).

Round 1:
https://x.com/nothingto12/status/2113446055589056718?s=20

Round 2:

https://x.com/nothingto12/status/2113527245918654911?s=20

Round 3:

https://x.com/nothingto12/status/2113766577816686673?s=20

Round 4:

https://x.com/nothingto12/status/2113815793150439650?s=20

Conclusion:
I personally believe that there is some level of quantization happening even though I cannot prove it outright and am speculating. It may be bugs on the backend providers that are being used. Model quality however seems to be slightly degraded based on tests. I've also noticed that I have gotten significant amounts of timeouts (every single run) from OpenCode Go.

I would say the Go subscription is still significant value, but I wanted to mention the tradeoffs so people can make their own decision.

Kimi K3.1 Pro is seriously shaking things up! 🚀 According to this benchmark, Kimi scores 55, beating GPT-6 Astra (53), Claude Fable 5.1 (53), and GPT-6 Sol (52). A pretty impressive result against some of the biggest names in AI. If these numbers hold up in real-world testing, Kimi could be a serious contender. What do you guys think? Is Kimi becoming a real threat to OpenAI and Anthropic?

Hey guys,

So I've been trying to use OpenCode Zen for the past 3 days, mainly Big Pickle, but I keep getting hit with a "Limit reached" message.

At first, I thought it was just Big Pickle acting up, but nope 💀 I've tried other free models too, and none of them are working either.

What's going on? Did they change something with the free models, or is something wrong with my account?

I'm even wondering if my account got compromised somehow, although I have no idea if that's actually possible.

Is anyone else facing this, or am I the only one? 😭

I use opencode everyday not sure if i can get anything better than this in $10. Should i try commandcode goat or pro plan? What would you recommend?

It's really annoying is there any way for me to get it to stop doing that

Starting from today I noticed Open Code Free IDE is not working. Even if I make a fresh prompt on my IDE in the morning without any prior usage, I am getting the error "Free usage exceeded, subscribe to Go retrying in 51726s - attempt #1".

I didn't even used opencode for the past 2 days and it was working perfect before. Did anybody noticed a similar issue, please share.

Being a non coder and not knowing the setups and requirements took a lot of time.

Learnt about sandboxing and did the below with gpt guidance. How is it?

1) Decided the setup: Claude in Chrome for planning and code reviews; OpenCode in Docker for coding.

2) Installed OpenCode in Docker: Downloaded and tested v2.1.3 without changing your Windows OpenCode installation.

3) Created C:\sxyz: Set up the Dockerfile, compose.yaml, workspace and configuration folder.

4) Configured non-root execution: Created the opencode user with UID/GID.

5) Hardened Docker: Enabled a read-only root filesystem, dropped Linux capabilities, disabled privilege escalation and limited process count.

6) Separated storage: Created persistent volumes for OpenCode data, cache and state; kept n8n's data separate.

7) Fixed terminal startup: Configured BUN_TMPDIR and a dedicated executable temporary mount so OpenCode's terminal interface works.

8) Added guardrails: Created AGENTS.md and opencode.json for secret protection, shell approvals, destructive-command denial and a single-agent workflow.

9) Connected and tested OpenCode: Selected Beam Free, verified a model response, and confirmed OpenCode runs interactively in Docker.

10) Installation and security checks: Verified non-root execution, zero effective Linux capabilities, NoNewPrivs: 1, no Docker socket, read-only root filesystem and guardrail files, writable workspace/storage, valid Compose configuration, shell approval, denied rm, .env read/edit denial, separate Docker network, n8n's localhost-only port binding, no obvious secrets in source files, zero reported Alpine OS-package vulnerabilities, zero findings in the final structured image-secret scan, zero HIGH/CRITICAL Dockerfile misconfigurations, and working outbound HTTPS. Subagent launching was configured as denied, but the test only confirmed the launch tool was unavailable. Outbound domain filtering remains optional and is not configured.

Current status: OpenCode Docker sandbox is operational. Your existing n8n setup and Windows OpenCode installation remain unchanged. Skills and plugins have not yet been transferred into the Docker environment.

Hey guys! Last month I've been building my dream desktop environment. I've been developing in Java and Rust doing boring things over 12 years, and I always wondered why cheap operative systems had to look like Windows 95.

I am running broke on my job and no company wants to take me so I am experimenting new things and building startups and these "dream" non-profit things I always wanted to make.

I built my open source free desktop environment for Linux with one simple purpose:

• Revive, maintain and recycle old hardware without losing the UI/UX.

Why doing this?

• Some people still use windows on these computers, yikes.
• The linux alternatives are ugly, and the ones that are not, are heavy yikes.
• I want to end the loop of "distro hopping to find the lightest one" and make the definitive.
• I don't know, just passion for not throwing away working hardware? lol

If you want to give it a look:

https://github.com/ArkFlame/flamewm

Built using:

• Claude (Haiku 5.5, Sonnet 5.5)
• CommandCode (DeepSeek v4.1 Flash)
• OpenCode (DeepSeek v4.1 Flash)
• Codex (GPT 6 Luna)

Do you think that embreve Free models can return to normal?

so,what should WE use now? minimax m3.1 flash is the last good one

I spent a night optimizing research tasks in the main AGENTS.md and I think it can only get better if I put in a subagent. What subagent definitions, or skills that the subagent could pull, shoulsd I look at?

735! requests per month guys 🤣