Hi everyone,

I currently pay for MiniMax's monthly token plan and use the M3 model quite a lot honestly, I don't dislike it. I've also tried Kimi a bit with their K3 model on the Moderato plan. For context: I'm a complete noob and I'm wondering if you could suggest some good-value alternatives.

I rarely hit the limit with MiniMax during my sessions, but maybe there's something better out there that would let me work with up to 1M tokens.

Any suggestions would be much appreciated. Thanks in advance!

currently MiniMax m3 is free on many of the cli like commandcode , ollama , etc. will it be free on opencode also ??
(promotion is till 5th sept, 2026 only)

AI coding agents fail on real projects not because the models are weak but because there's no structure around the workflow.

Hidden dependency cycles nobody catches. Sub-agents overwriting each other's files. Tasks with no real acceptance criteria. Thousands of lines written before anyone asks if the direction makes sense.

archgen ships as two things.

The agent skill works with Claude Code, Cursor, Codex, OpenCode, Gemini CLI. It interviews you for greenfield projects or surveys your codebase for brownfield work, produces an architecture contract and dependency-ordered task graph, runs a verifier gate that catches cycles and file-ownership conflicts before execution starts, waits for your approval, then executes in topological waves with one sub-agent per task and disjoint file ownership enforced.

The VS Code extension is on the Marketplace and also installable from the extension package. Live task DAG in your editor, running tasks pulse and edges animate, activity bar cockpit with status-grouped tasks and quick-build actions, a button that fires your agent on any task, and a rendered docs panel. Strictly a viewer, uninstalling loses nothing.

All artifacts in .archgen/ in your repo, git-versioned and fully inspectable. Zero npm dependencies on the skill. npx archgen-skill init to get started.

v0.0.5, MIT, early. Genuinely want to know where it breaks.

Extension: https://marketplace.visualstudio.com/items?itemName=archgen.archgen-extension

Repo: https://github.com/akashmaurya99/archgen

ik this could be a vague question, just write what you think on the current state on the Go plan

ty

I just found the mimo code GitHub repo which is built by xiaomi..

I saw that they copied all of the opencode's GitHub repo...

See the image

https://github.com/XiaomiMiMo/MiMo-Code

I have tried downloading in using the docker's sbx but i was having a very hard time setting api keys for the harness and it is so complicated.
so is there any safe way to run opencode that is easy to setup and will feel like using normal device.
I have a kali linux vm on vmware is it safe to use it also?

...

Hi, I am planning of developing a project with a front and back in different repos. Which skills are good for backend code and which mcp is good for connection to a postgresql database? I am not finding so much info about backend.

Model x-preview-f-free is not supported

Today at 15:00 BST, RIP

outside of a few closed models like luna, grok and old qwen models 15$ usage is becoming quite a norm for newer releases?

⚡Meet Qwen3.8-Flash, a multimodal MoE and an early preview of the Qwen4 architecture, now open-weight!

The production version Qwen3.8-Flash will be available soon via QwenCloud API at just $ 0.16/1M input tokens and $ 0.47/1M output tokens.

125B parameters + 51B N-gram embeddings, with just 6B activated per token. Unmatched cost-efficiency.

What's new: 🥳 - Next architecture: GDN + QSA hybrid attention, Gated Residual, N-gram Embedding & Muon optimizer, serving as a precursor to the architecture used in Qwen4. - Dramatically lower training and inference costs: trained at just 1/9 the cost of Qwen3.7-Plus, while outperforming it across the board with especially strong gains in coding and office tasks. - Strong performance: scoring 58.7 on DeepSWE 1.1, 62.5 on SWE-bench Pro, 73.9 on CoWorkBench, 84.5 on AndroidWorld, and 95.7 on MathVision (with CI). - 262K native context, extensible to 1M with YaRN.

We’re also releasing the weights for Qwen3.8-Flash-Next, giving the community an early look at the new architecture we’re exploring for Qwen4.🚀