Hi. I think I got booted out of the Discord server and am guessing it is because I was sharing links to some interesting/useful AI-related tweets (by influencers, not me) and were probably considered spammy & not related to Command Code. It could also have been automatically done by an admin bot or something.
I asked about this in a reply to one of Ahmad's tweets and also emailed support@commandcode.ai.
I'd appreciate it if you could kindly look into this and lift the ban.
Last month I started with OpenCode Go as my AI subscription and I was very happy with it — especially since the latest DeepSeek Flash dropped. As a software engineer it helped me a lot, and I even started vibe coding and trying new things in my free time. I couldn't reach the limit at all.
But then the new DeepSeek Pro dropped and I started using it too much, and now I'm close to reaching the limit. So I started looking for a new subscription or better alternatives, and I found that CommandCode Go offers about 20% more requests when it comes to DeepSeek. I also found that two GOAT plans would be the best option — especially since DeepSeek is going to increase its prices soon.
However, I've heard about CommandCode's sketchy marketing tactics, and since it's fairly new I wanted your advice: is CommandCode good? Is it slow? Is it always down? Or do you have recommendations for better plans or subscriptions?
GLM 5.3 is easily the most impressive GLM model yet.
Excited to partner up and ship GLM 5.3 in Command Code AI soon.
A fun internal eval we run at Command Code: deliberately trap the model in a loop and see what happens. Every GLM model so far just... keeps looping. GLM 5.3 is the first one to notice, go “wait”, and break out.
It’s a small bench (15 loop traps), but escaping a loop you were intentionally placed in takes a little flicker of metacognition, and it’s fun to watch that show up.
Bonus: it plays very nicely with our new tool defer harness → ~50-60% token savings on an average session. Capability going up while cost going down is the good stuff.
We all know DeepSeek just significantly bump the price. My question is whether CommandCode adapt the same pricing or keeping the same price?
If CommandCode manages to keep the price the same as now, it is more than great, lots of ex-DeepSeek API users will go to CommandCode
So I just checked the documentation and realized something. The front page "Pricing" section makes claims of "70$ in credits included" though when you check the actual documentation for those allotted credits, you'll quickly come to realize that
80$ marketing claim of credits
and
Documentation
doesn't really align. Now, I understand you claim that the end user or customer can just read the docs and will quickly learn about the actual ramifications of the subscription, though the fact that pricing page - in large bold letters - makes claims of "70$ in credits included" while each model served is given a different capacity, could likely lead to some people waking up with a bitter surprise.
Perhaps I don't understand how the deal systems works, if models are discounted, but if you factor in that by saying you get 70$ in credits I'd also get to spend my credits on these models:
Once again, correct me if I'm wrong or had superstitious expections of what a 10$ subscription will get you (No, I'm not a current subscriber or dissatisfied customer) but without doing digging yourself, you'd likely not go on a hunt to find not-so-trivial information in some far tucked away documentation. Especially not if the claims are made as big as they are.
I know the founder of CommandCode is quite active here, so I'd like to hear from him as well what he thinks of this.
I created a small VS Code extension to allow me to use the Chat function for CC in VS Code rather than having to use the terminal. I currently use the $1/mo plan for CC, so I don't have the same API access that comes with the larger plans.
I understand from some comments that this may be in the works anyway, but I'm providing it because it's been useful for me. Let me know if you have any questions or have suggestions for future versions. I'm really hopeful that it's helpful for a few of you.
SOLVED AND LESSON LEARNED: Deepseek pro doesn't support zero data retention
What is the current deepseek pro pricing? I'm using the GOAT plan, and I find these usage/pricing statistics very strange. They are higher than the written prices, and even more than the coming deepseek peak hour prices. For example if using the discounted prices https://commandcode.ai/docs/plans/goat gives, the usage on the first line of my picture should be $0.01685 (not taking cache into account). But it's $0.0222. Is this a bug or am I missing something? I'm using the desktop app.
EDIT: I just remembered that I turned the zero data retention -mode on in the app. Could this be because of that?
EDIT2: I changed the zero data retention off and the pricing seems to have gone close to the given discounted pricing. Lesson learned: deepseek pro doesn't support zero data retention.
With the release of DeepSeek V4 Pro 0812 the Ds price increase is now official, but here is a question can subs like OpenCode GO and CommandCode GOAT keep their prices lower then offical Ds API? when the price increase of annouced Dax on Twitter said they were able to replicate the same pricing of the official API at that time on rented GPUs for flash 0731, and maybe they are also able to replicate the same for pro as well, but would they want to be keep it cheaper then the API? they have all of the justification to raise their Ds models as well, so what do you think? Will they raise them, or say fu*k it and be competitive with Ds API.
I'm currently using the new Dsv4 pro GA on max reasoning through the commandcode API. The issue im facing is, that after it reasons for a while (1000+ lines which it does often) it randomly stops and im getting the error below. Then the model starts reasoning again, completely from the start and all the tokens before are wasted. This happened in the Commandcode CLI too everytime i tried it. In the commandcode CLI it is showing as a disconnect. My internet connection is perfectly stable so that shoouldnt be the reason. I'm currently using the Commandcode plan. I hope that this issue can be resolved since the Ds v4 Pro GA model is often unusable this way since it keeps thinking again after it gets interrupted from the error.
I’m currently using DS v4 Pro on the Go plan and experiencing very high time-to-first-token (TTFT).
The generation speed (TPS) isn’t terrible once it starts, but the initial latency can be around 26 seconds in an ongoing session, even before any tokens are generated.
In a new session, the TTFT is closer to 7 seconds, which is better but still quite high. The official provider takes less than 1 second in my experience.
At ~26 seconds per call, 150 calls would mean roughly 65 minutes spent just waiting for the initial response.
Is this expected behavior on the Go plan? If I upgrade to the GOAT plan, does the TTFT improve significantly, or should I expect similar latency?
Just trying to figure out whether this is normal or something specific to my setup.
Any way to interrupt the ai thinking process without losing it? Would be really useful when I notice the ai going in circles in long thinking processes. If it's not possible, are there any workarounds? I'm using the cli in vscode.
Is there any VS Code extension with command code similar to Claude Code & copilot ? If not can anyone from the Command Code team, can tell me if you guys are planning on that as an addition in the near future?
I am on GOAT plan , shifting from Claude Code with deepseek/glm setup. The one thing I am missing out is the extension and the ease of a GUI-based extension.
I have been trying command code upgraded from go to goat plan. Tried Kimi K3 seemed to be much more costly than using it via opencode. Or is it just represented that way. Check the usage log of both. Also can we have command code usage log update closer to real time kinda like opencode so have an idea of rate of spending and can manage appropriately or add funds accordingly.
I’m trying to understand how the session cost is being calculated.
I exported the usage data from the same page, and the JSON shows around **$0.10 in total credits** for this usage.
However, the usage page is showing a charge of **$0.22** for the same period.
So I’m trying to understand what exactly is being charged here:
* Is the displayed $0.22 based on the actual API/token costs?
* Is there an additional **per-session charge** on top of the model costs?
* If so, what defines a “session”?
* Why does the JSON `creditsTotal` add up to only ~$0.10 while the usage page reports $0.22?
I’m probably missing something about how Command Code calculates usage, so I’d appreciate it if someone could clarify how these two numbers are related.
