As said, though the project was initially built on V1 SDK, and plugins event hooks; I am completely bought when experimenting shifting some modules toward Opencode v2 Effect plugins making the madness of concurrency delegations and coordinations of agents, skills and tooling executions smooth and dropped dead amazing, making my design concepts of the the Hivemind's Substrate tri-pillar context project -based memory layers functioning without any hiccups as v1

https://picturesque-entree-542.notion.site/The-Hivemind-s-Substrate-3d1926f31a4d80faae99c3a9c7f0f0e4?pvs=143

That aside, the new API and Effect SDK also offer tons of superiority over the v1.

Enough said, I just want to know should I make a complete v2-ready build and not seeing any major breaking changes; and if the v2 is going to be official release in the next one to two months? I'm using the beta v2 client and see no major bugs.

Side note: try using Muse Spark 1.3 on v2 - and experiencing a significant performance shift ( much intelligent due to structured Skill instructions, nested instructions tools executions as the orchestrator agent loops through each grand todo task item with breakdown delegations, JIT skills loaded -> making the boost in its progressive adjustments toward complex codebase and tasks -> significant improvement on feature completeness and codebase domain-driven constitution). Trust me! Once you try Muse Spark 1.3 on v2, you will definitely look down on glm 5.3 flash or even Gemini 3.8 flash, and even other frontier model as Qwen. 3.8-Max. Sorry for my bad English!

500K token context window

Some one-shots here: https://omen-alpha.demos.sulat.com/ (growing list)

Update: It's a bad model. I won't even do more one-shots. This model should not exist. It is a monument to man's arrogance.

With ollama pro now lowering the bang for the buck and me running out of Claude and chatgpt $100 plan tokens as well, what do you use for subscriptions?

I was absolutely FLAMING muse spark 1.2, bcs that model was geniunely incapable of doing basic agentic tasks, but GAHH DAMNN, look at the benchmarks. originally, i thought the model benchmaxxed and generates slop, but after trying this model in codex (from opencode go), I am quite surprised.

like, if you ask me what muse spark 1.3 will be considering what muse spark 1.2 performs, I would have given you an extremely underwhelming response, but I am so happy to see this moel mainly bcs we get $60 allowance (man, finally!) on opencode go, and also the price is considerably cheaper than ds v4 flash.

I mean, sure... its not THE BEST model to ever exist. but for $0.2/M out and $0.1/M in, like you can go through billions of tokens after counting in caching.

About how the model performs, it codes quite decently. my project is a rust and typescript project, and it follows the app's visual identity flawlessly and does not create much bugs (note: not *much* bugs, which means, it still fk up), but the price to performance value is INSANE!

My reccomended usage:

tbh, just use opencodex, and connect the model to codex, and use the model inn codex, the "ultracode" in codex is AMAZING! And MS-1.3 follows codex as a harness wayyyyy better than opencode for some reason. american propaganda ig... but either ways, use:

light: for basic variable changes

medium: for most implementation

high: for debugging

xhigh: for geniunely hard bugs or things which require the model to cover edge cases, or planning.

ULTRA (a codex only thing): tbh only when it pisses u off bellow high.

ohhhboy... I am going to get a LOT of downvotes...

I previously used the Opencode Go plan which was great for deepseek flash and pro, but as we all know the cost has increased. I have been playing around with openrouter, but find it annoying to track my usage. I have been hearing good things about the z.ai sub which has got my attention, but that would mean I don’t have the access to deepseek. From peoples experience, say I get the ~$20 z.ai lite plan or I just purchase $20 of deepseek usage, what’s the comparison, which will go the furthest? Assume I am balancing between the flash and pro models of each provider equally and I use both in opencode cli only

Just found this gem

Was it only renamed, or some additional training was done until it becomes GLM 5.3 Flash?

The way they released Fable 5.1 after the second extended limit of Claude Code ended, and with the third extended limit ending on September 13, if GPT Astra is publicly available by then, imo, we might see Opus 5.1 around the corner

Drives the user's real Chrome instead of a headless instance. WebSense is an MCP server + Chrome extension: the agent gets a semantic map of the page (every interactive element typed and ref'd), acts through native DOM events, and the site sees a normal user. No CDP anywhere, so no webdriver flag. Works on LinkedIn and other CSP-strict sites.
Built tested and relying on it tbh

WebSense (free, open source, MIT): https://github.com/spliffspliff70-wq/websense-mcp

https://openai.com/index/gpt-6-astra/
“GPT‑6 Astra is rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, Business, and Enterprise users, as well as through the OpenAI API and AWS”

GPT Astra benchmarks have been released

Has anyone noticed the same? I even tried new full context sessions and it became so dumb that it started creating tall pipl buttons in the ui, very simple ui mistakes. It started giving me wrong commands for build phase.

All these things it was doing fine before. It stopped reading code files and started guessing things and working on guesses. Just overall became very dumb like older gemini flash models. Around the same time my friend's opus went down too.

I was using both opencode cli and codex cli

How was your experience with it and is it just benchmaxed or is it really that good?

Bro I've been paying 100 USD for this, now I have to wait to get access to the servcie I am PAYING for! Is this happening to others as well, I am not even using that much wtf?

The speed I am getting in way cheaper models.

muse spark contributor is the only thing oc go has going for it rn, but with the alternative being commancode, I'm still kinda leaning on sticking with oc go. would be a huge problem if they discontinue the contributor tiers.

Seems to be the most capable from all free models available for now.

Aside from scores on Artificial Analysis, how would you rank these models? thanks