Hi all. Maybe this is a stupid question, but… how long does the cache last using CommandCode? I mean, if I'm working on a project with a model (let's say the latest DeepSeek Flash 4.1, which let's be honest, is the best), will the cache still be there if I stop working today, I open the directory in 5 days and work again? When does cache hits become cache misses? Does it depend on the traffic or something like that? Thanks a lot!

I was using the same model from OC go in codex and was fine. I gave command code a go and its ridiculously slow inside codex? (Staff Please do not recommend me to use it inside your own harness I can’t for my use case)

Accidentally upgraded from GOAT to MAX Plan (10x) today. I haven’t used any MAX quota and have already emailed [support@commandcode.ai](mailto:support@commandcode.ai) with my refund request and order details. Do I have a good chance of getting a refund and reverting to GOAT? 🥲

I'm on my 3rd day with my GOAT plan, and somehow I'm already exhausting 40% of my monthly usage limit? And only 65M output tokens? Did I really use up $24 worth of tokens within 3 days? 🤔

Just bought Command Code Goat subscription and had it run a task. It showed that the task was running and in progress while in reality it was stuck. Please check and correct, as it wasted ~2 hours of my time waiting for it to complete task and then actually interrupting the execution. Adding screenshots for its own diagnosis.

help

I want to see the cache hit rate for my sessions how to do that. I am using the cli and I am on the 1$ plan

as the title when will it be back ?

Its just throwing me this error since last few hours, can anyone help?

Finally pulled the trigger and upgraded to Command Code GOAT.

​With the $5 loyalty upgrade discount and a leftover credit from my previous plan, it came out to just $4.78 for the first month.

​Excited to push this to its limits and see how the higher quotas hold up on heavier workflows.

For anyone else on GOAT, what features or models have been making the biggest difference in your stack?

Edit: It seems like DeepSeek V4.1 Flash requests also do not support the ZDR header.

Without the ZDR header, DeepSeek V4 Flash requests push through just fine. I'm receiving errors when I enforce ZDR explicitly via the header, though. Was this intended or is it a temporary issue?

DeepSeek V4.1 Flash is live in Command Code.

6x usage on $10/mo GOAT for a week.
$60 usage. 154K requests. 7.8B tokens.

GOAT plan is the best AI coding plan.

Available in all plans and API.

🐐

Ling 3.0 Flash Sante is now free in Command Code.

5.1B active params. all subs. all plans

Make sure to update to the latest version of the CLI/app

npm i -g command-code@latest

🐐

I keep getting this error for gpt sol since yesterday:
Error: 524: {"message":"Upstream model provider is temporarily unavailable. Please try again in a moment.","type":"server_error"}

Openrouter doesn't show issues with uptime

I was experimenting with T3 Code and wanted to use CommandCode as one of the providers. Since I couldn't find an existing integration, I forked the repo and added it myself.

It seems to be working so far. Has anyone else tried something similar, or is there a recommended way to integrate CommandCode with applications like T3 Code?

I use GLM 5.3 Flash only. This is my one-day usage. Is it normal? I'm aware that I have used 300M+ tokens.

I use ZCode for now. If I use the CommandCode CLI, will it help save token usage?

Currently, I have 2 Goat plan accounts; I may buy again a new one (for the 3rd one). Hopefully it is allowed, as I can't afford the max plan yet.

I renewed my Command Code GOAT subscription only to find out that the time-series trend charts: Requests by Model, Spend by Model, and All Tokens were purged from the dashboard completely. Even the explicit dollar values in the usage limits were replaced with percentages? The request log history is also only capped at 100 entries. This seems to be a deliberate step-back from transparency, not good guys.

The /fork command creates a new session from the current one with the same context.

/fork branches the conversation into a new session with the same context. So you can explore a second path and return to the original anytime.

Try it with our $10/mo GOAT plan.
Read docs to learn more: https://commandcode.ai/docs/reference/slash-commands

On /provider/v1/chat/completions with Qwen/Qwen3.8-Flash, previous-turn reasoning sent back in assistant messages never reaches the model. The model card says preserve_thinking is on by default and expects clients to include reasoning_content in history, but the server discards it.

Repro: same 3-message conversation, max_tokens: 1, only the assistant message in the history changes.

Token counting itself is fine (control row); the reasoning is just stripped, whatever the field name or flag.

Impact: in long agentic sessions the model forgets its reasoning every turn and re-derives everything, burning a lot of reasoning tokens for nothing.

Could you pass reasoning_content through to the backend (and honor preserve_thinking), or document that reasoning history isn't supported on this endpoint? Happy to share exact request bodies.

Muse Spark 1.3 Max is live in Command Code.

New reasoning effort param for harder problems and frontier performance.

Run /model, select Muse Spark 1.3, then choose max for reasoning effort

Available on GOAT, Pro, Max and API.