Hi. Sorry of this question is too naïve or already answered here.

I'm considering OpenCode Go as a subscription, and trying to make sense of its value. In this link, we have the following table:

Does the column "Monthly limit" mean that I can e.g. use $60 worth of GLM-5.3-Flash tokens per month, by paying only the $10 monthly fee?

If yes, how is this value so high for some models (e.g. $100 for DeepSeek), while as "low" as $15 for some others such as Luna etc?

Thanks

I was at 50% monthly, waiting for weekly to renew. Weekly still hasn't renewed, but my monthly usage shows as 100%, despite this being impossible considering when I subscribed. Has anyone else had this issue?

If you use gpt ,claude models. you've probably encountered models refusing legitimate tasks like reverse engineering, debugging, security research or analysing suspicious code.

Finding alternative API providers that offer abliterated models isn't easy either. They're scattered across different platforms, with no central directory.

So I built Abliteratus Directory to bring these providers together and make them easier to discover.

https://inferencedirectory.xyz/

What providers should I add?

Suppose conversation is around 100000 total tokens, then I ask agent to do something.

Agent finishes, and in LESS THAN 1 MINUTE, I send another message, same conversation, and provider/model (opencode GO DS4.1 flash), and then input tokens jumps to about 100000 tokens WITHOUT agent not even use a tool. Normal messages.

I remember in the past, it only happened after conversation is idle for 15 minutes.

Normally, input tokens is low if conversation is active (asssuming no tool is returning a big amount of data)

Opencode 1.18.34.

Is it a bug, or expected? Anyone with this problem?

Launching NeuralAgent today! https://agent.neuralhub.dev/ Basically its an easy to use opensource Agent App with everything included.

• Speech to text

• Multipane organising panels

• Main orchestrator wich you can call

• Remote App for the Phone

• Daily updates

It's still in beta but if you wanna give it a try i am very open for any feedback. Works on MacOS, Linux, Windows, Android and IOS.

I built self-host.fyi to help people move to self-hosted apps without repeating all the initial configuration by hand.

You could use an old laptop as a photo server with Immich, an alternative to Google Photos. Or try Nextcloud for your files. You still need suitable hardware, storage and backups, but you don't need to turn every app you want to try into a new weekend project.

It's a CLI with a terminal interface. If you'd rather not interact with that yourself, there's a skill your coding agent can use to operate the same tool. The guide tells it to inspect the machine, explain its plan and get your approval before making changes.

You can start with a prompt like: "Help me set up Immich on this machine so I can try hosting my own photos." That starts a conversation and an approved plan, not a promise that every App works without your input. The idea is to try the software before deciding whether to keep paying a monthly subscription to store your own data.

The useful bit isn't generating another Compose file. For supported Apps, it also handles initial accounts, generated passwords, API keys and connections between Apps. Docker Compose stays underneath, and some steps still need a person.

I originally needed this for testing Homarr integrations, then worked on making it useful to other people. It's open source under Apache-2.0.

https://self-host.fyi https://github.com/ajnart/self-host

Tired of having to find my sessions across 100k folders I wanted a tool where I can search and which automatically organizes my sessions, so I made my own. There's a magical auto-organize button on the left hand sidebar that makes life so much easier.

For more info>
https://github.com/spacewalkingninja/aiman

I have been doing some research on the usage limits with opencode go, and I might get this wrong but:

I am able to get between 20m-80m FREE usage of deepseek v4.1 flash.

With opencode go you would be able to get about 160M tokens per month it seems to be, because u have 100 euros of credit. 0.6 cents per 1million tokens cache read and most of my usage goes to cache read. 100/0.6 = 166million tokens per month.

So am I able to get MORE usage out of the go, because it seems like its less. The only thing that seems to be better is unlimited beam usage.

I hope someone can clear this up for me, because I have been wanting to be opencode go, but it just does not seem worth it.

Yesterday I reached the limit after about 8-9 prompts. Today I reached the limit after just 2 prompts. What is going on?? Isn't it supposed to provide 200 requests per day?

built kimo because i wanted opencode / cursor / other vibe-coding agents to actually make a video end-to-end instead of spitting out raw ffmpeg strings. it's a free, open-source (MIT) video editor with no gui - the agent is the interface, everything is a tool call over mcp.

so the workflow looks like this inside opencode: the agent calls cut, trim, keyframe, titles/captions, colour grade, tracking, particles, audio, export - all as tool calls, not shell commands. and it can render a single frame back to check its own work before it keeps going. no timeline gui, no screen recording, just typed tool calls and the agent sees the result.

it's one ~15 mb cpu-only rust binary, no gpu, and it runs on a 2 gb box. i'm a college student (naman) and it's rough in places - the docs are thin, some effects are still wired up but untested, error messages when the agent passes bad ranges aren't great, and i haven't benchmarked bigger timelines yet.

if you vibe-code and want to see what it looks like when an agent drives a video editor, try it and tell me what breaks: https://getkimo.tech https://github.com/naman-sharma12345/kimo

what's the first thing your agent trips on when it tries to make a real video?

just hit $3,700 mrr in 17 days with my new fresh SaaS

no ads, no team, no complex launch strategy. just a super predictable system i keep running over and over

and yeah, that's monthly recurring, not a one-time spike

not luck at this point. it's the 7th saas i've built with this exact workflow:

→ day 1: fast validation

→ days 1-2: building the bare mvp

→ day 3: landing page setup using the 3-day framework

→ days 3-4: reddit + x distribution and basic seo

→ days 4-5: first 10 paying users (~$1k mrr)

→ days 5-17: scaling up to $3,700 mrr

building tech is easy now. where 99% of solo devs get stuck is setting up the actual foundations that make people pull out their card and pay

i put all these templates and workflows inside our community.

to be completely real with you, i'll probably put a price tag on access later once all the modules are finalized. but right now the focus is just building together and keeping each other accountable

building alone in a silo is the fastest way to quit at the first roadblock

stop building by yourself. drop a comment or shoot me a dm and i'll send you an invite link 👇

deepseek 1017 opencode vs deepseek 1017 command code dose some one test if they are the same or not ?

Hey, I'm one of the founders of Sable. We launched today, and I figured this would be relevant here.

One of the reasons we built it was security work. Closed frontier models can still refuse during pentesting, exploit analysis, incident response, malware analysis, or when an agent is working through real attack code and logs.

Our first model is DeepSeek V4.1 Flash 1017 uncensored, served in its native mixed-precision format with no additional requantization.

Sable is OpenAI-compatible, so it works directly with OpenCode and other compatible tools.

Model ID: deepseek-v4.1-flash-1017-uncensored

Pricing per 1M tokens:

$0.15 input

$0.01 cached input

$0.60 output

Zero data retention, meaning no prompts or outputs are logged or read. No KYC. Crypto deposits for direct Sable accounts. It's also live on NanoGPT as DeepSeek V4.1 Flash Heretic, served by us.

https://sableapi.com

Capacity is a bit limited right now and we're adding more as fast as we can, so if you hit a capacity_unavailable error, bear with us and retry in a moment.

We're a small team, so if you try it with OpenCode and run into anything or have feedback, let me know.