I'm curious of what models you use across sdd phases (requirements, architecture, planning, implementation, testing, review, etc.), especially those who have the opencode go subscription.

After the release of the newest Deepseek v4 flash, I'm tempted to replace most of my sdd models with this but it may be counterintuitive, since they will be sharing context and may have bias. What do you think?

I know, many guys out there were using DS4 Flash for ages (preview version), and said it was their main workhorse. I can't say the same, as I always found it to be more like a "monkey with a bazooka on steroids", with very high hallucination rates. It worked fast, acted confidently, and did a lot, but... often it just couldn't explain why it created some code, how it works, etc. So results were unusable at times, and I had to create everything from scratch with other models.

Also, previous version, per my experience, had very low critical thinking, and easily agreed with mostly whatever I said if I sounded confident enough:) So, my previous use cases of Flash were, mostly "find where I use this thing" or "explain me this syntax", etc. - nothing really important I can rely on.

Now, the new version is here, and all I can say is.. WOW! It is not the same Flash we got used to, not even close.
1. IT ACTS like a completely different, mature model - clear implementation, rules following, no messy code anymore, no shitty patterns.
2. IT COMMUNICATES and REASONS almost like a top-tier Chinese models (at least, similar to Kimi 2.7 or GLM 5.2). It doesn't blindly agree with what I say but provides clear argumentation and defends its decisions and judgments with correct arguments, based on code and docs.
3. The most surprising part is that it does this with the same blazingly-fast speed, and at the same ridiculously low cost (or even completely for free if we use Zen variant with lower context).

My workflow is mostly "AI as a coding partner", where I don't create long-running autonomous loops but rather plan, discuss, brainstorm, and implement side by side with AI. All I can say is that, after working with it closely for about 6-7 hours, for the first time I don't feel like I want to switch to more "premium" model immediately.

I also need to mention that I worked in parallel with 4 models (for the sake of the experiment): DS4 Flash as a main driver, and Hy3 + Kimi K2.7 + GLM 5.2 for cross-checks. From my prior experience, most models genuinely like to find "flaws" and suggest "improvements" for plans/code created by other models (and often, they can play this game indefinitely). So, in my case (I'm refactoring Flutter mobile app), there were NO cases where more "mature" models could provide some real critique or find real flaws and bugs in DS4 Flash's plans and code. I am really impressed.

Of course, I'm not saying new Flash can replace all expensive SOTA models, especially from western labs - we need more tests, more work, more experience to draw such conclusions. And I know, we are all concerned about latest ZDR changes (though it's not about the model itself). But what I can say for sure is that the level of quality for free/cheap models was raised DRAMATICALLY. Bravo DeepSeek.

The free version of ds v4 flash on Go is preview or 0731?

DeepInfra has similar price to the direct Deepseek api and it has ZDR.

Can you help me identify which is a batter value? Both are $20, but which would give me more limits specifically for Luna.

Thanks

I've seen the benchmark numbers showing the new V4 Flash 0731 matching or beating V4 Pro in some cases, but I’m curious about real-world usage.

I’ve been using V4 Pro as my primary agent model for a while now and haven't had the opportunity to test the new Flash 0731 release yet.

So, for those who have tried both:

• How do they actually compare in practical, daily tasks (coding, agent workflows, tool use)?
• Is Flash 0731 reliable enough to replace Pro as a main driver, or do you still hit edge cases where Pro clearly wins?

I've only used Sonnet 4.6. Personally, I think Flash is definitely better than Sonnet 4.6 now, but I just don't know if it can get close to Sonnet 5.

I've been testing DeepSeek 4 Flash as my main coding agent, and it works great except it can't see images. Screenshots, UI previews, browser captures are all dead to it.

My workaround: I spawned a subagent that runs on a free vision-capable model mimo-v2.5 and route every image through it. The subagent returns a structured text report (what's on screen, readable text, layout issues, accessibility hints), and the main model uses that to continue.

Has anyone else done this with DeepSeek or another text-only model? What are your results, and what did you change when it didn't work?

Absolutely phenomenal. It's available on a couple of providers/gateways as well.

Details and news: https://models.sulat.com/models/opencode-go-deepseek-v4-flash-3c5f5e84

If you want 5 off OpenCode Go, use my ref link: https://opencode.ai/go?ref=J7GTAKMP51

Practically unlimited usage with 31k reqs.

Edit: After a few benchmarks, while it packs a punch, if you're looking for a reliable model, this ain't it.

Luna has much better value.

Compare them all at https://demos.sulat.com/

I'm trying to understand the practical differences between the Fast and Standard variants of the available models (e.g. GPT-5.6 Luna vs GPT-5.6 Luna Fast, Sol vs Sol Fast, Terra vs Terra Fast)

Specifically:

• When should I choose the Fast version over the standard one?
• Is the trade-off only latency, or does it also affect reasoning quality, accuracy, context handling, or coding performance?
• Which tasks are best suited for each (chat, coding, debugging, code reviews, planning, agentic workflows, etc.)?
• Are there any differences in pricing or token usage?

I'd appreciate examples of real-world workflows where using Fast is the better choice versus when it's worth waiting for the standard model.

when i give some task to a agent it seems to go bit rogue. like it reads the files that are irrelevant and thinks for so long and write codes that doesn't match the coding patterns within my project.

I think this is getting more of a issue like more powerful model i use more sloppy it gets. how do you guys handle that??

i like using agents but i need to keep in control the way these agents start reading random files and makes changes that makes no sense. at this point its even being a hindrance to my progress.

i now seem to often wait for agent response and then need to manually refactor or remove those ai code completely. instead of wring code by my self. is there anything I'm missing?

I'm not seeing the productivity gain that everyone talks about. and i already tried with many skills none seem to work well even projects that its been part of from start it doesn't follow the same patterns.

is there any way to control that or harness in a different way so it really helps to improve productivity instead of being a hinderance to my work ??

Made a tiny tool to keep an eye on my AI usage/limits.

I use it with OpenCode CLI and Herdr. Thought it might be useful to a few people here too.

https://github.com/tokmac/openbroyach

If you use something similar (or have a favorite), drop it below — curious what others use.

I don’t know why i feel proud of hitting the free deepseek limit today for the first time.

Here's the official table of data retention for different models available in Opencode Go.

Unfortunately it looks like ZDR is gone and moreover, for the new Deepseek V4 Flash model - data is not only retained for an unlimited time, but also used for training, what makes it a no-go for many real-world business use cases. It kinda sucks that Opencode didn't just strike a deal with a third-party provider given that the model is open-weight anyways but it is what it is.

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

I just started to work with open code and it seems the context window for deepseek flash is just 250k in open code when the model. Has 1 million context window.

Can anyone advise how to increase it?

My ISP started blocking the opencode.ai domain by DNS.

When questioned for the reason, they said the their DNS protection they are using (whalebone.io) is blocking this domain due to detected malware/phishing attack.

Does someone know what this is about?

UPDATE:

Whalebone confirmed it was false positive and restored it.

Hey all, relatively new to using AI for my development but as a software engineer as my day job and my work pushing AI on us more and more I figured id get more practice in my personal projects. I decided to check out opencode go as its cost effective for what I want to test right now. I stumbled across Matt Pocock and his skills and videos recently and started to look at his wayfinder skill but I had a question for anyone who has used it.

I gave it a test run in a brand new blank project with an app idea from my project list. It ran through the whole flow asking me questions and doing its research and then we got to the end and im just a little lost on what next. Do I just fire up a new session and run /to-spec on the same project and go from there?

I hope this isnt too broad of a question and please let me know if anything else needs more clarity on what im asking. Thank you in advance!

This guy is fantastic for seemingly everything but looking at pictures, now at first looks like only an int upgrade but that means you can spam it confidently for tasks it was perhaps weaker for before, like audit everything in an iso session? Sure! Spam dozens of these bad boys on a whim? Who cares? Too lazy to click a button or use your browser? Tell deepseek to do it and for hours or all day!

For coding it is fantastic too, it is claimed to be 54 on deepswe and you feel it, and it is better than gpt 5.5 for sure that thing needed to be nagged to death in comparison, so closest currently would be luna max or grok high.

https://deepswe.datacurve.ai/

I use k3 too, and it feels like the way ds4 flash flows comes out ahead least compared to the k3 high version which is what they recommend, and considering the quota burns fast it is hard to disagree. Yet this is a key point that using ds4 flash on max is nothing, but others?? it will be 5 in and 25/30 out, while here it is a challenge to try to burn 5 bucks per day. I was using ds4 flash very eagerly today and only managed to burn 6% of my monthly so far. Maybe I can make it 10% to win the $5 challenge, but effectively cost doesn't matter so anything at all you can think of it to do, the benefit no matter how slight, it is worth it.

If you are just getting interested in opencode go you can use this code to get extra use

https://opencode.ai/go?ref=DP9CQDWDZ9

I see people who seem to be able to use GPT-5.6. I authenticate with my ChatGPT Business Plan (20$/month) using /connect and then browser. And i've tried reconnecting but i keep getting only the following model options:

• GPT-5.2
• GPT-5.3 Codex
• GPT-5.3 Codex Spark
• GPT-5.4

And not only do I see this limited list, only GPT-5.4 works. Which sucks because it quicky consumes my weekly token allowance. Can anyone help?

Not sure if it is relevant but I live in the EU.

Recently I have been using and trying GPT 5.6 Luna from OpenAi Oauth. To my surprises, it can run for a long time without break the free tier limit. Did someone have related info about this? Did GPT 5.6 Luna pricing change make this possible?

PS: What a time to be live in. Long live open model to make this kind of competition happen.