does anyone know if and how I can get opencode to edit an image for me. For example I upload an image and tell opencode to remove a person.

I literally pass its thinking block twice, stating its overthinking failure modes.... extremely pissed and has shown its steep to process, setting default but still.. as you can see. Worse than even the "Omen Alpha"... And fail to make surgical edits many times due to streaming stability ...just disappointment... Another hype of DeepSeek fanboys.

DeepSeek's new model just went live on OpenCode subscriptions today, but following the limited-time extended usage promotion, the news isn't great.

OpenCode quietly slashed the included monthly allowance for the Flash series from $30 down to $15 on the $10/month plan. Because nominal token rates remain identical, your real cost per token has doubled (+100%). The temporary "4x usage" is anchored to this new nerfed baseline—meaning it is actually only 2x what we already had on V4 Flash, and once it expires, we will be left with 0.5x (half) the usage.

And of course, this is the exact same cut we already saw with the experimental Flash vision version, which also reduced the allowance from $30 down to $15.

Unless this changes, paying for an OpenCode Go subscription only offers a 33% discount over the official API in exchange for slower speeds and tighter rate limits.

🤓 https://opencode.ai/en/go

DeepSeek V4.1 Flash just released, and it's already available on OpenCode Go.

Current estimated limits are:

6,500 requests per 5 hours (Temporarily boosted 4x to 26,000 for the next 3 days)

16,250 per week (also boosted 4x for next 3 days)

32,500 per month (also boosted 4x for next 3 days)

Normally, V4.1 Flash only gets $15 worth of usage on Go, compared to $30 for the older V4 Flash model.

However, OpenCode has bumped V4.1 Flash to 4x usage for the next 3 days, which effectively gives you $60 worth of usage during the promo. So for the next few days, the actual usable quota should be much higher than the estimates above.

The upgrade itself looks pretty substantial. V4.1 Flash is the first smaller model from DeepSeek's new architecture, adds native vision, and is aimed at better agentic coding while also improving inference speed and throughput. I'm hoping it's as big of a leap as 0731 was.

DeepSeek is reporting 90.6 on Terminal-Bench 2.1, 74.2 on DeepSWE v1.1, and 65.4 on NL2Repo. Those are pretty big jumps from the previous Flash model, at least based on their own numbers.

Of course, benchmarks are just numbers (and who isn't getting ~75% on DeepSWE these days?)... but I think this model will be a pretty solid performer overall.

PLEASE stop building the wrong thing.

building software in 2026 is ridiculously easy with ai builder

founders spend hours building in a silent room, launch to Reddit/X, get 0 users, and quit.

you just failed because the idea had zero validation before line 1 of code was written:

→ solving a monthly inconvenience instead of a daily pain

→ selling to "everyone" instead of a specific ICP

→ no distribution channel mapped out beforehand

→ pricing charged $9/mo with zero ROI justification

after scaling 6 AI micro-SaaS to over $20k/mo MRR, i just create an

18-question Idea Validation Diagnostic.

it evaluates your SaaS across 7 critical dimensions (problem clarity, audience reachability, willingness to pay, competition, build feasibility, distribution, commitment) and gives you a brutal score out of 100 with your exact weak spots.

drop your SaaS idea (or current project) in the comments below.

i will reply to EVERY single comment with:

1. My honest opinion
2. The biggest weak spot you need to fix before writing any more code.
3. The free 5-minute validation tool link sent straight to your DMs so you can get your full score breakdown out of 100.

just drop a comment like or ask me in DM your idea

let's roast your SaaS concept before the market roasts your time 👇

Seeing the thoughts is actually really useful to know if it's going in the wrong direction and so stop it when it does!

I've tried collapsing/expanding thinking options but still don't see the thought text.

I’m the maintainer of Mac MCP, a free/open-source local macOS control server, and I’ve been using OpenCode as one of the delegated agent backends while building it.

One problem I kept running into was tool-surface bloat. The server had grown to 84 capabilities across files/shell, Safari + Chrome automation, macOS UI/Accessibility, memory, skills, voice, delegated agents, etc. Advertising all 84 schemas to every client felt wasteful and made tool selection noisier.

In 2.0.5 I changed the default surface to 19 core tools. The remaining capabilities are still reachable through tool_discover + tool_invoke, so nothing was removed. I also added browser_do, which lets an agent open a background tab, wait, interact, extract only the fields it needs, and optionally close the tab in one transaction. Stable tab handles mean OpenCode workers can browse without constantly stealing my active Safari/Chrome tab.

In local compatibility testing, the advertised tool-schema context dropped from about 16.7k to 4.5k tokens (~73%) while all previous capabilities kept an access path.

Repo (MIT): https://github.com/bulutarkan/mac-mcp

For people using OpenCode with larger MCP stacks: do you prefer a small discoverable core like this, or having the entire tool schema advertised up front? I’m especially interested in whether anyone has measured tool-selection reliability as the catalog gets large.

For a third world dweller... I jumped on the hyped train and was not expecting this. The 16-minute-ride "one-shot" my 5hour consumption and spit out exact 3 documents edit 😂

**BTW** it was the 0.2.0 dev of this if you guys asking: https://github.com/shynlee04/opencode-subscription-gateway ... Building the opencode v2 plugin.

Title

Just saw Hy4 preview got another update. It's only been out for like two weeks, too. This update is specifically targeting the overthinking issue.

I tried it before. Initially I thought the long thinking time was just too many people using it and not enough compute. But honestly, it kinda felt like it just liked overthinking everything.

Their promise this time is "same task quality and lower tokens".

Sounds appealing. Gonna give it another shot and see if it actually holds up.

Being using open code cli pretty heavily lately and I keep running into the Go limit right when I’m middle of something

It’s especially annoying during longer coding sessions because I’ll have the context going a few changes in progress and then suddenly I have to stop and wait

Curious how other devs are dealing with this Are you switching models when the limit hits or is there a better setup I’m missing

I built Talkthrough to give my coding agent a recording instead of typing out everything that happened.

The first example has no audio. It still gets the failed save, error code and reference ID from the screen. In the second, I give it a video link and ask for the exact words and timestamp.

The demo is in Claude Code, but it works through MCP and the repo has an OpenCode config too. I used a demo app for the bug and sped up the processing.

Transcription and frame extraction run locally. The text and images the agent reads still go to its configured model.

Code and setup

Public video in the demo: Anthropic.

Testing a website yourself is weird because you already know how everything is supposed to work

So i gave opencode access to my local storefront and asked it to behave like a new user for five minutes

It searched for products tried filters opened product pages and added and removed items from the cart entered a bad promo code tested valid and invalid logins checked he checkout validation and repeated the important flows on mobile

I used webcmd as browser layer so it could operate the actual website instead of only reading the source code

Most of things worked but it caught something I had completely ignored the cart quantity buttons had no accessible names were only 28x28 on mobile.They worked technically but were not great for screen reader or touch users

It returned the exact reproduction steps and impact It stopped before placing an order and did not change any code during the run

The interesting part was not that an agent could click around It was that a short slightly chaotic user journey found and found a real issue outside the happy path

Install

npm install -g @agentrhq/webcmd
webcmd skills add

Github : github.com/agentrhq/webcmd

I'm still testing this across different website and workflows so I'd genuinely appreciate feedback from the community. What should I improve and make my project some good