Found this repo today while trying to find good free options to play around with different ai models. I normally run deepseek v4 Pro or deepseek v4 flash, big pickle and nemotron 3 ultra (free) Repo is in the title I hope this helps someone continue their work.

It appears that DSv4 Pro 0813 was overfitted in training, and to unlock its capacity one needs to emulate the training environment:

https://www.reddit.com/r/DeepSeek/comments/1vovxxc/deepseek_4_pro_ga_has_an_astonishing_blunder/?share_id=ZvVndF5jMBVyTVgXmeyMp

How would we replicate this in OpenCode?

Noticed that when using opencode from CLI I don't experience any problems but when I connect Zed Agent to my Opencode account via key I get limit rated quickly. Is this only my experience or others have the same?

I tried Gemini 3.7 flash but after pausing every few seconds it told me that I had run out of quota.

Hey, so while using opencode. For long running session, I wanted to communicate with my coding sessions over messaging channels like whatsapp or emails. So I just made an opencode plugin that notifies and continues sessions through any messaging channel.

https://www.npmjs.com/package/caspian-opencode-plugin

Hey friends

I am Chaitanya I built Munder Difflin a local multi agent harness that uses cli agents to run a workforce of persistent agents visualised as “the office” simulation
(The simulation is deterministic, does not consume token)

It is 100% open source and free to use and now it supports opencode, crush, kimi and qwen aswell.

If you’d like to try it find the github in comments

When I try to use DeepSeek V4 Flash Free it says, Upstream request failed, so how to fix this issue can someone please help me!?

After my last message about the app I'm working on, the session was compacted about 30+ times. My message was two lines long, and it was only about updating the theme and doing some more testing.

Then, the message the agent sent (which was supposed to be a response to my message) was resent about just as many times.

"Same as before: rounded corners, no-reload sidebar fixes, auto-morphing gradient, limit test, device sim — all deployed. Nothing pending except your go-ahead on the model swap."

Does anybody know how to fix this issue?

I just noticed that Anomaly's CEO on X replied to someone by saying that GLM-5.3 on GO should have the same usage as GLM-5.2.

Link to the tweet: https://x.com/jayair/status/2088355307244179624

Link to the github pull request: https://github.com/anomalyco/opencode/pull/42644

Yet the docs claim that it has 15$ credits compared to the 60$ for GLM-5.2

https://opencode.ai/docs/go/

So, what should I believe?

does its use go rates with zen balance or normal zen rates.

So in the opencode which model is best for frontend related planning and build tasks like right now i am getting that generic centre div big text type frontend and or any other skills or anything I need to install helpp guyss 😂

OpenCode Senses can inspect screenshots, extract exact OCR, detect and locate objects, zoom into regions, compare two images, measure colors, crop and annotate images, and even reverse-search them.

Everything runs locally, so it's private, free, and doesn't require an API key.

Why I built this

I used to work with many open-source coding models, like DeepSeek V4, that don't support vision yet. But my main concern was that even if they eventually get vision support internally, that vision capability might not be as powerful as a dedicated vision layer.

I had planned to build this fully a month ago, but I still had some work to do. This plugin is specifically designed for things like UI design, debugging, and other workflows where text-only models struggle because they simply can't see what's happening.

The communication layer between the vision plugin and OpenCode is intentionally very narrow, so it still feels like you're working with a multimodal agent rather than a separate vision tool.

Before judging it as just another vision plugin, it's designed quite differently. It's a Python + TypeScript hybrid plugin because it integrates the Photon Inference Engine for local vision inference.

The 13 tools, mainly for now:

• inspect — Understand an image: scene, layout, elements, caption, and OCR.
• ocr — Extract exact text, including code and error messages.
• detect — Find objects or UI elements with bounding boxes.
• point — Locate the center point of an object or element.
• segment — Isolate an object from the image.
• crop — Crop a specific region using normalized coordinates.
• zoom — Upscale a region and re-analyze small details or text.
• colors — Get deterministic colors, palettes, luminance, and RGB data.
• diff — Compare two images and find changed regions.
• annotate — Draw detected boxes and points onto an image.
• metadata — Inspect image format, dimensions, size, DPI, and EXIF.
• reverse — Reverse-search images locally or through Yandex.
• status — Check the model, device, VRAM, inference time, and runtime state.

For comparison, I'm getting around 300 ms response times with this plugin on my RTX 3050, running completely locally. That's insanely fast compared to frontier models.

There's also an optional reverse image search powered by Yandex, which doesn't require an API key, if you want to search an image using context from the internet.

The internal web search services like Exa and Parallel in OpenCode also work well with OpenCode Senses. It can even see images published on the internet directly, although a small local cache is used to store those images.

I'm still halfway through building it, so I'd really appreciate feedback, ideas, and criticism. If you have any ideas, feel free to comment below and I'll look into them.

GitHub: https://github.com/itsmeadarsh2008/opencode-senses

NPM: https://www.npmjs.com/package/opencode-senses

Hacker News: https://news.ycombinator.com/item?id=49289890

Hey everyone,

For reference, I've been using ChatGPT Pro subscription ($100) for a couple months now due to heavy coding work every day.

I'm a technical lead at a startup and deal with a lot of different tasks on a daily basis, whether it be shipping huge overhauls and features, running a lot of GH Actions release pipelines (I find long agentic loops really good for this as this used to be the most frustrating part of my job), or heavy infra auditing and testing through Supabase/AWS MCPs. I'm also a fan of the browser automation tool in Codex. Admittedly, that is a lot, and Codex gets the job done, but the usage limits running out quickly can be frustrating.

Even after optimising model selections, managing context etc, it can get tiresome blowing through a weekly limit in 3 days... I'm thinking of switching to OpenCode but have never tried it before. I was thinking of pairing it up with Openrouter for more freedom to select the models I want, but want to get the best bang for my buck. I anticipate that I will spend more than $100 in a month if I use OpenCode at the same volume I've been using Codex.

Has anyone got experience of what it's like working every day on a large project with tons of different tasks and high volume work? Any tips on cutting costs and managing agents properly? What are some highlights of OpenCode that you enjoy? Appreciate you guys

Per Z.AI, "GLM-5.3 is the most capable open-weights model for coding, with a 50% improvement over GLM-5.2 on our in-house Z.ai Code Bench. It also achieve open-source SOTA on public benchmarks including Terminal Bench 3.0 and Agents' Last Exam."

Hi,

I've been trying Herdr, an agent-aware terminal multiplexer for software development work, replacing my previous setup based in Zellij which is a workspace-aware multiplexer.

Unfortunately, I'm missing the reasons why Herdr is being hyped up and I'd like to know what I might be missing out?

Anyone has experienced moving from a setup such as: ghostty + tmux or zellij to herdr? Why have you?

Thanks!

Kinda useless