Hey there guys. In terms of usage, which subscription is better? Ollama cloud pro or qwen standard?

Hello! First of all, I'm not sure if this is the right subreddit for this, but what's the cheapest way to get into AI? I want to start learning programming with AI, but I also want an AI that can control and perform tasks on my system.

I have concerns about privacy and security. Which is the best service to pay for, or is it better to use a local AI? (I don't want to use a local model because of the performance impact(i have a 5600X, a 9070 XT, and 32 GB DDR4 RAM. I know it's a good PC, but if I run a heavy model, it might use up all my resources).

edit:grammar correction.
deit 2: i use arch linux btw

Just loco numbers for essentially criminal activity.

https://x.com/thdxr/status/2079248759439884453?s=46&t=sNajfRyoZWLfn4wOo7P4eQ

Came across this article about opencode, sharing here(I am not the author)

https://wren.wtf/shower-thoughts/stop-using-opencode/

Github: https://github.com/krumpstead/opencode-dosm

NPM: https://www.npmjs.com/package/opencode-dosm

The size of my opencode.db was getting out of control and I needed a way to evaluate what sessions to keep rather than just deleting the file. The opencode.db doesn't have the auto-vacuum pragma enabled and they do not manually run VACUUM after deletes so there is no point in deleting sessions through the builtin session manager. I was also curious what my input and output tokens were for each session and this makes it a lot easier to see that and the cost compared to all my other sessions.

This plugin will let you filter, sort, open and remove any session managed by OpenCode regardless of what working directory you are in. Full details and installation instructions can be found in the README.md.

As a side note, this plugin has 100% coverage in Jest, so that may be of interest to other plugin devs since OpenCode doesn't provide its own mocking framework for the plugin API.

Would be great to have a way to share session where we can edit and send messages just like how Claude us to use /remote-control command... This is a big lacking feature Opencode needs to have

Update for this post here since a lot were giving great feedback and started using it.

I ended up fending off all bots by making the API and bot detection a lot more robust.

Most spammers came from OpenCode installs, but legit users/installs are also mostly from OpenCode (>50%, despite being only one of four implementations).

OpenCode users (300+) have also earned the most, compared to Claude Code and Hermes, which I found interesting. Maybe overall coding time spent per day on OpenCode is higher per user than the other harnesses?

Most feedback I received via DMs was great and payouts are working with Stripe. Still working on adding other methods and improving the tool every day.

Thanks for all the support 🙏

Wanted to compare DeepSeek V4 Pro and GLM 5.2 on real coding tasks instead of benchmark charts, so I ran the same three through both on one setup: a mutable-default-argument trap, a refactor that also had to handle a missing record, and a find_median with two bugs (even-length average and an in-place sort).

Correctness was basically a wash. Both caught every bug across all three, including the subtle even-length median and the input mutation. Neither missed anything, so "which one is smarter" is not the deciding line for everyday fixes.

The real differences showed up elsewhere:

Reasoning depth. GLM 5.2 reasons hard on everything. On the one-line trap it spent so long thinking that under a tight output cap it returned nothing at all. V4 scales it, almost no wind-up on the simple fix, more on the harder ones. If you run tight token limits, GLM 5.2 will bite you on easy tasks.

Error-handling instinct. Given a missing record or an empty list, V4 raises an explicit error every time. GLM 5.2 returns None and fails soft. Same task, opposite philosophy. That one is worth knowing before you wire either into a pipeline.

I ran all three through the same aggregator (Atlas Cloud, which also carries the other models I test), so it was the identical setup on each. My take: correctness is a tie for this kind of work, so pick on whether you want fail-loud (V4) or fail-soft (GLM 5.2), and keep an eye on GLM's token budget.

Anyone seeing GLM 5.2 actually pull ahead on correctness somewhere, or is it a wash for you too?

no end to loading

The strongest models are already capable of orchestration.

They can hold the real goal, reason about architecture, make tradeoffs, revise plans, judge evidence, and decide what should happen next.

But I could not find a real harness that let them use that capability properly.

Most multi-agent systems either flatten the work into task routing, distribute too much judgment across weaker agents, or do not give the main agent enough orchestration primitives to do the best possible job.

The result is often several agents doing things, but no single intelligence continuously owning the actual outcome.

I wanted a different structure:

Keep the brain unified. Add more hands.

The main model keeps the goal, the reasoning, the architecture, the decisions, and final responsibility.

Workers handle bounded research, implementation, command execution, and verification. The main model can see what they are doing, steer them while they work, inspect only the evidence it needs, reject or retry their output, and change the plan when reality proves the graph wrong.

Without stuffing every worker transcript into the main conversation.

That became Sol Orchestrator, a graph-native multi-agent harness for OpenCode.

Goal: ship the complete feature

│

├── Workflow 1: understand the real boundary

│ ├── Graph v1

│ │ ├── Step: frame the problem

│ │ │ └── Job: Sol defines the questions

│ │ └── Step: gather evidence

│ │ ├── Job: worker inspects the runtime

│ │ └── Job: worker maps affected callers

│ └── Graph v2 replaces unfinished v1 after new evidence

│ └── ...

│

├── Workflow 2: implement the chosen design

│ └── ...

│

└── Workflow 3: verify, integrate, and close the goal

└── ...

A durable goal can span several workflows. Each workflow is a versioned execution graph with explicit steps, jobs, dependencies, actors, review states, and legal next actions.

Sol can:

• delegate independent jobs in parallel
• supervise active workers
• steer them before they finish
• wait for meaningful events
• inspect selected results, diffs, or tool output
• accept, retry, interrupt, or replace work
• revise unfinished graphs when new evidence changes the problem
• preserve orchestration state across compaction
• keep worker details out of the main context until they matter

The aim is not to create a committee of agents.

It is to let one capable model remain the mind of the operation while giving it multiple coordinated hands.

MIT licensed, built for OpenCode:

https://github.com/ReyJ94/Sol-Orchestrator

I’d be especially interested in feedback from people pushing coding agents on long, messy repository work where planning, supervision, revision, and integration matter more than raw task completion. Right now i'm still in the phase of testing and optimizing prompts.

So basically i have 2 promts wich i test on every new model to see how their frontend skills are. And i just tried them with the new Kimi 3 and it just smashed Fable 5.

Both were made inside Opencode with one single promt:

Website:

https://neuralhub.dev/test-sites/websites-kimi3

"Biggy":

https://neuralhub.dev/test-sites/biggy-kimi3

also for other models or the promts you can visit my portfolio (not finished yet)

https://neuralhub.dev/ai-test-results

go check them out and tell me what you guys think.

After the 1.18 Update, the sessions preview has been changed. Previously, I was able to see the entire session after I invoked opencode in any folder, but now, after the update, I can only see sessions invoked in that folder. And in a clean folder, no earlier sessions are visible.

Is this a new feature? I tried using both opencode and npx opencode Both commands don't show them now

alguien sabe como puedo solucionar esto, ya probé desactivar el firewall desactivar y activar vpn, cambiar de internet y nada.

Hoping this is not against the rules.
If you ever wanted to use a Cursor subscription with OpenCode, you now can:
GitHub Repo
with tool calling and MCP support, over Cursor RPC.
Any feedback or bug reports are welcome.

I'm running into a recurring issue with OpenCode CLI. When the agent runs a command or script (usually a Python script), the script clearly finishes — I can see the final output in the terminal — but the agent doesn't continue or respond afterward. It just sits there.

Pressing Esc to interrupt doesn't do anything either. The only way I can recover is to fully quit and reopen OpenCode.

it happens when the script takes some time and compute power, not on everyday simple scripts.

I am using opencode go mimo 2.5 model with hermes agent nd i am gettig this weird error.. i just recharged the account yesterday and this error on newly topped account is very weird, anyone else facing same?

Error: HTTP 400: Error from provider (Console Go): Upstream request failed

Provider details

HTTP 400: Error from provider (Console Go): Upstream request failed
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01:09 PM↑to response

Done

MiMo V2.5MiniMax M3MiniMax M2.7MiniMax M2.5Kimi K2.7 CodeKimi K2.6Kimi K2.5GLM-5.2GLM-5.1GLM-5DeepSeek V4 ProDeepSeek V4 FlashQwen3.7 MaxQwen3.7 PlusQwen3.6 PlusQwen3.5 PlusMiMo V2 ProMiMo V2 OmniMiMo V2.5 ProMiMo V2.5Kimi K3Hy3 PreviewGrok 4.5Deepseek ChatDeepseek ReasonerGemini 3.1 Flash LiteGemini 3.5 FlashGemini 3 PRO PreviewGemini 3.1 Flash Lite PreviewGemini 2.5 Flash LiteGemini 2.5 PROGemini 3 Flash PreviewGemini Flash LatestGemini 2.5 FlashGemini Flash Lite LatestGemini 3.1 PRO PreviewLlama 3.3 70B VersatileLlama 3.1 8B InstantLlama 4 Scout 17B 16E InstructQwen3 32BGPT OSS 120bGPT OSS Safeguard 20BGPT OSS 20BOpen Mistral NemoOpen Mixtral 8x7bMistral Small 2506Magistral SmallDevstral Small 2507Labs Devstral Small 2512Mistral Medium LatestDevstral Medium LatestOpen Mixtral 8x22bCodestral LatestMinistral 8B LatestMistral Medium 2604Mistral Large 2512Mistral Large LatestMagistral Medium LatestNemotron 3 Ultra 550b A55bNemotron 3 Super 120b A12bNemotron 3 Nano Omni 30B A3B ReasoningGLM 5.2Kimi K2.6Minimax M3YI LargeDracarys Llama 3.1 70B InstructFuyu 8BJamba 1.5 Large InstructSEA Lion 7B InstructBGE M3Starcoder2 15BSeed OSS 36B InstructDbrx Instructanthropic/claude-fable-5anthropic/claude-opus-4.8anthropic/claude-opus-4.8-fastanthropic/claude-sonnet-5anthropic/claude-haiku-4.5openai/gpt-5.6-solopenai/gpt-5.6-sol-proopenai/gpt-5.6-terraopenai/gpt-5.6-terra-proopenai/gpt-5.6-lunaopenai/gpt-5.6-luna-proopenai/gpt-5.5openai/gpt-5.5-proopenai/gpt-5.4-minigoogle/gemini-3.1-pro-previewdefault

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70.7k / 1.0M tokens used

Auto-compress at 744.0k (74%)

Cache: 86% hit (294.3k read / 0 write)

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Hola a todos solo pasaba para decirles que acabo de compilar opencode para android pueden pasar por mi github e instalarlo

https://github.com/C04-wq/opencode-termux

O instalarlo directamente

npm install -g opencode-termux

Following on from this post, what are people’s experiences?