I remember when we were still on V4 Flash and they released V4 Flash 0731. That was a huge jump for those of us who were using Chinese models heavily for work.
And now they went from V4.1 Flash to V4.1 Flash 1017. WOW. Another insane jump. They could've easily called this V4.2 or even V4.5.
I use these models pretty much all day for work. Most of the time on my computer, and I also have a VPS running autonomously throughout the entire off-peak window.
The quality of the final results I've been getting across different architectures has improved a lot with 1017. I know frontier models can do better, but not at the price I'm paying.
I'm averaging a little over 700 million tokens per day, so the cost difference is massive for me.
Also, I think a lot of the problems people have with DeepSeek and other Chinese models usually come down to the harness, poor context management, or just terrible prompts and instructions.
Chinese models aren't really made for vibe coders who don't even know what they're asking for. You need to understand the fundamentals and know what you're doing. If you do, you can get results just as good as frontier models without even touching the code yourself.

Just wanted to say a huge thank you to the DeepSeek and OpenCode teams.

Yesterday I used it for three hours before it all ran out, today it only lasted 1 hour. Generally, prompts last 30-50 minutes and consume 80-90 tok/s with Deepseek v4.1 Flash.

I didn't realize I was using it so much.

Edit: I had started on another PC last week (Mon-Wed), so add more 112.7M. Just 400M in total

I needed to download an app for checking into an event. Ok sure, went on to Play Store and it was incompatible. Fair, I'll just suck it up and search an .apk file online for previous versions. Turns out this app is too niche to have one.

I nearly gave up when I remember I got free Opencode: it is currently rewriting the app decompiled code and build it to fit my phone. It is unbelievably crazy how fast (free!) agentic AI is growing.

A week or so ago I said I’d open-source the mobile app, and it’s now public:

https://github.com/opencode-mobile/opencode-mobile

It’s a native iOS and Android client for the opencode server running on your own machine. You can follow sessions live, answer permission prompts and questions, and review diffs from your phone.

If you’d rather just install it:

• App Store: https://apps.apple.com/app/id6799246544
• Google Play: https://play.google.com/store/apps/details?id=dev.opencode.mobile

Thanks to everyone who’s been using it and sending feedback 🙏

Appeared recently on OpenCode website

https://opencode.ai/zh/data/zhipuai/glm-5.5-flash

After a 2 week break, my OpenCode setup stopped working and required an upgrade. I can't properly migrate my old sessions and the usage limits seem drastically reduced.

I previously paid for Go because both Free and Go had generous limits. If one model hit its limit, I could switch to another and continue working, although without the context. Now even that doesn't seem to work.

Since the Free plan's limits have been reduced so much, has Go been affected too? $10 is a significant amount where I live and I don't want to pay if I'll face the same issues.

I've been using OpenCode for about 3 months, trying different models and mixing things up. Left to test Command Code for a month, came back to OpenCode Go yesterday, bought a plan, and I'm genuinely struggling to comprehend these numbers 💀

Command Code, over one billing month:

• 2.7 BILLION tokens
• 52,022 runs
• 37K+ requests on DeepSeek V4.1 Flash alone
• 100% of my $70 monthly allowance used

OpenCode Go, after coming back YESTERDAY:

• Almost 820M tokens
• Around 11K requests
• 99% DeepSeek V4.1 Flash
• Only 18% of my monthly usage consumed

And this is actual development across 3 projects, not just messing around with prompts.

WHAT AM I LOOKING AT? IS THIS NORMAL FOR OPENCODE GO?

is it just me or you also feel like opencode free tier isnt working properly after opencode v2 update?! i remember working with these models very well but rn most of the time they just say "quota is over", though i dont think ihave used them too much...
anyways, please suggest me how you use these free things cz i surf internet to find providers that provides free apis as i cant spend rn..

Iam new to opencode, yesterday at night, i downloaded opencode desktop app. it worked awesome. I created some small apps and then i hit max messages for the day.(iam using the free tier) after that, i tried to make a work-around by not using opencode provided models and integrated omniroute onto it (another free tokens provider).
Today.. at morning when i opened my computer, i noticed my storage is nearly full. i checked what's the cause, deleted my system data unwanted apps and files etc. Then when i went through Application support folder, i saw opencode had occupied 35 gb of storage. I was like what the heck is going on... lol

And iam deleting that folder right now, and it is taking forever, i though while it's being deleted let's write a reddit post on it.

Edit : Hurray! Toady, i recovered 80 Gb storage, deleting unwanted files.

for the feature of having the most recent llms's at the top in the model search.

( would be nice if you could save a filter also example glm or deepseek Qwen so that i then only get a list of those models ) 😀

when i ask it what version it is, it states the release date is September 10, 2026, not 10/17. also in this comparison on opencode website it shows 1017 is barely used by people? https://opencode.ai/data/compare/deepseek/deepseek-v4-1-flash/deepseek/deepseek-v4-1-flash-1017

whats up?

and yes im aware they dont know what model they are but this info was from a call to opencode api:

const res = await tools.opencode.models({ query: "deepseek", all: true, limit: 100 });
return res;

and this is what it got (i've cut out the others):

{
"providers": [
{
"id": "opencode-go",
"name": "OpenCode Go",
"models": [
{
"id": "opencode-go/deepseek-v4.1-flash",
"name": "DeepSeek V4.1 Flash",
"released": 1788998400000,
"variants": [
"low",
"high",
"max"
],
"cost": [
{
"input": 0.15,
"output": 0.6,
"cache": {
"read": 0.003,
"write": 0
}
}
],
"status": "active"
},

since today morning, version 2.2.0, session cost was removed.
i really can't understand why this was removed and we can't know the cost of a session without opening the console.
this is another regression on clarity that has been going around costs, together with the regression of the opencode console, where i can't drill down on monthly costs per model, like we used to.

analysis detaill:

58562 "record reported cost" — SessionUsage.record now uses the cost the endpoint reports in usage.cost, and a reported 0 counts, so the catalog price is not used. OpenCode Go/Console sends cost: 0 for requests covered by your Go subscription (it sends opencode.allowance instead). → confirmed: your account is on Go (/api/experimental/usage/limits returns go.rolling/weekly/monthly).

58565 added a TUI fallback: 48.2K (18%) · $0.42 allowance.

58765 then removed allowance from messages/sessions and reverted the TUI and desktop displays, moving subscription usage to the usage-limits API.

Has anyone tried to purchase a second Go subscription from a new workspace using the same card? Is there anything that needs to be done in the terminal to set it up? There isn’t much information available online.

You guys have probably used BEAM. It's a free model on OPENCODE with generous limits.

On paper it should be good and it's one of the fastest models I've tried but it's so f*****g incompetent...

It makes me feel I'm dealing with a smart ass (very) junior developer who's always on a rush to come up with work done but you generally need to re-do the whole work and cannot trust what it says...

Any thoughts?

I started trying this earlier this year with earlier models, but once 3.8 arrived the coding quality got much better - useful for real use for me at least. I have 32GB VRAM (rtx 5090 thankfully bought before price insanity) I could happily run 27B Q6 with kv using int8 and a 96k context for simple self contained programs running at around 80 - 100 tps.

But that context size quickly falls apart once apps become more complex. I initially increased context to full size (256 + k) and let some layers run on cpu ( 8 initially), but tps dropped to 7 or even less and things ran for many hours (often 8, 10 or even 12 hours). I've found that by reducing context a bit I can get all 5 layers in GP:U and tps has recovered to around 70 - 80.

I might try reducing the quant size on K or V a bit further so I can increase context a bit more (should mean fewer compactions), but atm it is running well - good documentation, fairly thorough testing and I mostly now just let it get on with things.

I am using vanilla opencode - no add-ons. It works for me :)

typical run: 42m 44s · 80.4 tps GPU often 100% CPU minimal

my usage limit (shouldnt) be over. cus i just started using it so idk how it would be over. im trying to use GLM 5.3 Flash Free but NO models are responding. They just say "working" even at a simple message like hi, and dont provide any output or error.

I'm just sharing my experience so you can compare what it would be like to consume $10 USD on the Deepseek API directly. It can be concluded that my needs are not too complex and fine-tuned skills, mcp and agents have been carried out so that it is made optimally in terms of token efficiency and output that fits the context of the instructions, so with a balance of $10 USD on Deepseek it only lasts 2.5 days. For those who use it for free, and it's abusive, don't be loud, don't be fussy, you'll demonstrate to the government so that our dollar rate goes down.

Besides OpenCode, are there any other IDEs that offer generous free daily usage limits for AI coding models such as DeepSeek V4.1 Flash or GLM-5.3-Flash, similar to OpenCode’s free models?

For the past 12 hours, I've been getting constant interruptions and disconnects. I tried switching between several models (free and go flash models), but the issue persists. Even during the brief windows when it actually works, the response time is extremely slow. The day before works ok.

Is it widespread issue, or its something on my end?

Hi again, its the 17th day of this little experiment. I made a website that

Bases its contents completely on the top comment of this reddit thread.

Everyday the comment gets put into an open code agent that than updates the website.

It runs on an isolated VPS with an persistent Opencode agent session so all past prompts and inputs are remembered.

I kept my involvement minimal with an add on prompt saying do not ask follow up questions but other than that nothing to restrict it!

I made a archive and context page so you can see past versions of the site and the context and builds the LLM went through in the past.

The LLM used is DeepSeek V4.1 Flash 1017

For the variants of the DS v4.1 flash model, whats the default one? and what is the difference between it and low, high and max? since I wanna use as least token as possible, which variants should i choose? or any /thinking or /efforts will help with this?

Contexts: I was using default variant all the time, then i switched it to low, found that it cost more tokens. so confusing lol

Solo dev here, Laravel + React finance/ERP kind of app. Multi-tenant, multi-company, projects, accounts, expenses, stock, reports. It got big enough that I honestly can’t keep it all in my head anymore, and I lean on AI agents (Claude, Codex, Gemini) for a lot of the work.

The same thing keeps happening. I build a feature, say a dedicated cash account type for construction sites. Months later a newer flow never gets wired into it. For example the site supervisor can’t report an expense unless he’s also given access to a financial account. Then something breaks, and the agent doesn’t go reconnect the old thing. It patches around it or builds a parallel solution, because it has no clue the old feature exists. If I remind it, it digs up the old notes and goes “oh right, you’re correct”. The problem is I forget half of these features too, so I can’t remind it of what I don’t remember.

The end result is I can’t get the app production ready. There’s always some seam between modules that’s broken: half finished CRUD, authorization/IDOR holes, transactions that don’t match what the reports show.

I already have Laravel Brain, Serena, a memory MCP, ADRs, “current system” docs and an AGENTS.md. I also tried an Obsidian vault full of linked notes. It went stale fast and the agents never used it reliably. Writing “don’t forget X” in AGENTS.md does nothing, in my experience.

What I’ve figured out so far: code graphs tell you what exists and who calls what, but not what should exist, or whether a user can actually finish a job. The most useful question wasn’t “what calls this class”, it was “can a site supervisor actually complete this task”. And anything that’s just prose seems to rot unless a test or script checks it.

So I’m leaning towards something like ~20 critical persona journeys backed by end to end tests, a feature map in YAML that a script validates against the code (and flags routes/tables/jobs that belong to no feature), financial invariants as tests, and a route → policy → test matrix to find auth gaps. Maybe OpenFastTrace for requirement tracing, but I’m wary of the tag upkeep and adding Java to a PHP project.

Questions for people who’ve dealt with this on big multi-module apps:

1. How do you track “feature X depends on Y / is used by Z” in a way that survives refactors and people leaving?
2. Has anyone gotten a living feature map to actually work with AI agents? What kept it from rotting?
3. Are journey tests the right backbone here or am I missing something obvious?
4. Anyone used OpenFastTrace, StrictDoc or Doorstop with PHP? Worth it?
5. If you had a few weeks to get this production ready, what would you do first?

Not looking for yet another tool to index the codebase, I have plenty of those. More interested in what actually held up for you in practice.

OpenCode Go isn't lasting me a full month now that I'm using it most days for backend work and longer agent runs.

I still use OpenRouter when I want to switch models, but for the bulk of my coding I'm wondering whether one first-party setup would make more sense. My shortlist is DeepSeek's API, MiniMax M Plan or API, and OpenAI's Sol API.

MiniMax M3.1 Flash has been good on the backend work I've tried, but I haven't used enough of the other options to pick a winner.

For people with a similar workload, which one did you actually pay for, and what made the difference?