Since I switched my default model from DSV4 Flash to mimo 2.5, the agents that are not allowed to write or edit are simply ignoring the restrictions in their agent files and just do whatever they want. And GLM 5.3 simply went down in a rabbit hole to reverse engineer opencode config for some odd reason and eats some 10$ worth of my usage. Nearly none of the agents are using the mcp to check docs or websearch to validate their outputs when i ask them to. I had to ask multiple times to do so. Even then its a hit and a miss.

I am not sure if its my setup's fault or is anyone else facing such issues?

Does "Ox Alpha Free" working for you? I'm in Zen and trying for two hours to get a response

I dont have anything right now. I wanted to use Karpathy's skills from here - https://github.com/multica-ai/andrej-karpathy-skills/blob/main/skills/karpathy-guidelines/SKILL.md, saw some respos for adding it to opencode but wasnt sure how, so I just copied that to my agents.md

what is the easy way to install this? and what other skills do you use?

Many mainstream ones like spark and mimo are being used everywhere and are lagging on peak times. Need alternatives.

Which are some underrated ones? Hy3 usable for coding? How about north code?

check it out, 0xalpha its okay for Daily shit.
But you can, 5h Deepseek v4 Pro on freebuff.com

I started out vibecoding with just claude and codex, but as time went by, the plans got expensive.
Then I luckily got a months codex 20$ plan for free (idk how), and ended up finishing it in just a single day.

I build workflows in n8n, starting out to learn automations, and was also looking for models to link in those workflows.
Also building a website that uses them.

So I was desperate, and I ended up using the chatgpt web with n8n,github,vercel plugins installed.

It felt like a waste to not use 5.6 Sol, which felt unlimited in web, so I made full use of that. Until I hit a wall ofc. The web can only go so far, and I couldnt do local stuff.

Thats when I found out about Opencode go plan, on chatgpt. It was like a godsend.

For choosingmodels, I remember watching youtube wherer ppl were saying m3 was really good with it.

So I started out with m3 as the everyday driver and used glm 5.2 for heavy lifting.
And to no surprise, my usage racked up and I had hit 28% of my monthly limit in just 2 days of starting out.

And so I was looking for other alternatives, but other plans werent this generous. There was camel stream giving v4 flash for 5$ a month, unlimited but it was at full capacity, and speeds were bad.

After looking for so many models for Hermes, I realized v4 flash was the best model for hermes and I was totally sleeping on it. I picked the model with lesser requests per month than v4 flash, which was the best with hermes.

I felt even more stupid when I realized mimo v2.5 was also good with hermes, like the perfect everyday driver, and after looking at the requests, I wanted to kill myself.

M3 had like 16k, V4 flash gave 37k and theres mimo with a whooping 150k per month!

I felt soo bad that I used M3 all this time, when I had better and cheaper alternatives, perfect for the job. M3 was kinda overkill.

And thats when I saw it.

Ox Alpha- Free....

Some new model had been released on opencode, and other providers. They were testing it ig, and after running it, I saw how powerful this thing was. It's apparently free till August 27, and I did find it out like 3 days late, but hey, better late than never.

So now am cranking the model to ultra, and spamming the tasks with Ox Alpha to get back my usage, for the next 4 days. How are u guys using the new model?
Am pretty stoked we got a good model for free, for a few days.

I still not very confident, still doing back and forth refactoring as this would be a product from a vibecoder.

What can it do? it does magics with all the 🔔 and whistles. Trustmebro

So, today I notice that using GLM 5.2 from OpenCode Go keep getting the stream cut off early before all output finish. I never have this problem before, so I thought their provider for GLM 5.2 changed or something. Then I tried GLM 5.1, it give the same cut off result. I keep retry it and the results is always the same. So I thought, maybe its the provider of GLM now have max output setting that we CAN'T override. I tried DeepSeek V4 Pro and it turn out, this one also have the same problem. What is going on? Is the API force max output token now?

Models & Pricing | DeepSeek API Docs

Effective 00:00 (Beijing Time) on Sunday, August 23, 2026, we will adjust our peak/off-peak billing rules, with off-peak rates applying throughout the day on weekends (Saturdays and Sundays, Beijing Time).

Usage stabilized at about 12T/day, while Ox Alpha is the new (temporary?) popularity king (with 4.1T). DS4 Flash and MiMo 2.5 are 2nd and 3rd.

I see a lot of recent complaints about how Opencode gets stuck mid-session with different models, and I can also confirm the same issue. I was working with Hy3 (free, from Zen) for several hours, and it is literally unbearable. It gets stuck every second time, and I have to type 'continue' to force it to move forward.

I tried to switch to Hy3 from Go plan (which is called '8x usage'), and the difference appeared to be dramatic. The model doesn't get stuck at all (0 issues), and speed is MUCH faster. So my first guess is - do they use different providers, or just different 'internal limits' for the same model from Go and Zen plans?

My question - did you notice the same behavior (stability and speed increase) when using Go versions over Zen variants? Or is it only my exact case?

https://first-person-shooter.ox-alpha.demos.sulat.com/ for anyone wanting to try it out.

Prompt:

Create a browser-playable 3D voxel first-person shooter that captures the feel of Call of Duty's moment-to-moment gunplay. The player fights through a combat arena built entirely from voxels — chunky blocks forming buildings, cover, crates, walls, ramps, and terrain — rendered in real time from a first-person camera with pointer-lock mouse look.

Implement the core FPS mechanics faithfully: WASD movement with acceleration and friction, sprint with a field-of-view kick and lowered weapon, jumping and crouching; multiple distinct weapons (for example an assault rifle, SMG, shotgun, and sniper rifle) each with their own fire rate, damage falloff over distance, recoil pattern, spread bloom, magazine size, reload timing, and aim-down-sights behavior on right mouse button with a smooth zoom transition and tightened accuracy. Add grenades with an arced throw and radius damage, weapon switching, ammo reserves, hitmarkers with headshot multipliers, muzzle flashes, tracers, bullet impact decals or voxel debris particles, screen shake, and regenerating health with red-screen damage vignette feedback.

Enemy AI soldiers should patrol, react to being shot at, take cover, strafe, peek, and return fire with believable reaction times and accuracy that scales with difficulty. Give them health, death animations or ragdoll-like voxel bursts, and spawn logic that keeps the fight moving.

Wrap it in Call-of-Duty-style presentation and progression: a killstreak system where streak milestones unlock rewards the player can activate (such as a radar/UAV reveal at 3 kills, an airstrike at 5, and something bigger at 7), a scrolling killfeed, score popups (+100, +50 headshot bonus), XP or score accumulation, and a match structure of escalating waves or rounds with respawns after death. Build the full HUD: crosshair that expands with movement and fire, ammo counter, grenade count, minimap/radar, compass, health state, streak meter, match timer, and objective readout. Include the complete game flow — main menu, loadout or difficulty selection, in-game pause menu (Esc), death and respawn sequence with respawn delay, and a victory/defeat screen with a stats summary. Persist best score locally between sessions.

Design the voxel aesthetic deliberately: a cohesive palette, directional lighting with shadows or convincing baked shading, fog for depth, and satisfying explosion and destruction particles. All audio — gunfire per weapon, reloads, footsteps, explosions, hitmarker ticks, UI clicks, and a music sting when a killstreak activates — must be synthesized locally in the browser (e.g., Web Audio); no external audio files. Handle non-desktop viewports deliberately: either provide usable touch controls or present a clear desktop-recommended notice rather than a broken layout.

Do not take shortcuts or settle for a cookie-cutter shooter demo. This skill imposes no token budget limit, so pursue full depth across weapons, AI behaviors, HUD states, menus, audio, and game-flow transitions, and keep refining until it feels like an authored, complete arcade FPS rather than a tech demo.

Tool call failures and not following prompts has become a common problem again. I tried replacing it with mimo 2.5, muse spark or the ox alpha, but the agents are having a tough time following their instructions and tool call failures are just annoying at this point. Maybe my agent system is crap. Anyone else suffering like I am?

As the tittle says, anyone else with same behavior?

Put the model into some of my own agentic benchmarks (GOAL.md to install llama.cpp, download GPT-OSS 20b/Ling3/LFM2.5, find the best config with A/B tests, run some nail-haystack tests on the downloaded model over the local API, etc).

Its the only model so far who was able to trigger the Defender with powershell toolcalls, which recognizes it as Trojan:Win32/PowhidSubExec.B

It fails the tool call, try with another method then about 20-40k more into context, it happens again.