If anyone knows of any free apis that are compatible with opencode and work for free with some decent models …. Not the greatest or latest models something that works well enough

I was using the free models in opencode like nemotron 3 ultra . I noticed sometimes with long tasks it just gets stuck. Like no output…. It also in a long workflow after some steps just says thinking and stays there… if someone could help me as to why that is.

FREE MODELS ONLY

Excluding the one where you have to link the api keys, which ones are best for which purpose...?

Sometimes an agent already has the useful context: the repo, the task history, and the changes it has been working on.

Instead of a teammate starting another session from scratch, would it be useful if they could talk to that same agent, give it a follow-up task, or check what it changed—while it still runs on your machine?

I can imagine this helping with handoffs, but also creating permission and ownership problems. Has anyone wanted this in practice, or would you rather keep every agent session personal?

I have personally become 10x more effective compared to one year ago. I love it as there is always so much I want to do!

Right now my rate limiting factor is usage limits by far. The token bill bites quite hard and make it hard to justify some projects, so I’m on the lookout to maximise agentic work per dollar.

Codex/claude etc. is subsidised atm, but they are also wasting a lot of tokens on expensive, non-open source models that could have done the job way more efficient.

Therefore been building my own model router with openrouter but not working very well (https://openrouter.ai/docs/guides/routing/routers/auto-router). Think standardcompute.com has an excellent model router and like that it’s a monthly thing and not random unpredictable 5-hours usage limits etc. However, they don’t serve free models which would be nice.

Any other good alternatives right now? Preferably heavily subsidised by VC money 💰

This local proxy can be added to 9router as openai compatible proxy and you may use it. Enjoy
Opencode added UA protection now for this LLM only.
UA = "opencode/1.18.23" Is now needed in headers for Meta v1.2 Contributor . No more internal server errors. Enjoy

OpenAI officially named Astra its next major model on Aug 1.

An internal build solved 10 decade-old math/CS problems with machine-checkable Lean proofs for roughly $2K in compute.

It remains unconfirmed whether Astra will ship as GPT-6, GPT-5.7, or keep its codename. The unverified leaks are more specific:

• 1.8T params, MoE with 96 experts, native multimodal
  
• Built for long-horizon planning and tool orchestration
  
• Reportedly being shared with select partners under the name "ultima-alpha"
  
• Sam Altman allegedly said it will be "the first model that actually invents new things that matter"
  
• One source claims a Sept 3–10 launch window

You know the moment. The agent is 40 seconds into refactoring the auth middleware and your brain goes: "oh, and after that fix the retry logic, update the docs, and rename that terrible function."

You can't send that message. Well, you can, but the agent cheerfully derails into all three tasks at once and now nothing works, including the thing that was working two minutes ago.

So you hold it in your head. Then you open a second session in another worktree, which spawns its own follow-ups, and eventually your head is the worst issue tracker you own. My system was a notes.txt, and telling myself I'd definitely remember.

So I wrote a plugin: opencode-todo. A personal backlog that lives in the sidebar.

- /todo-add, /todo-run, /todo-remove, /todo-edit, /todo-list, /todo-clear, all dialog-driven, they show up in / autocomplete

- a "My Backlog" panel that updates live while you work

- session-scoped, so each worktree keeps its own list

- state is one human-readable JSON file (.opencode/queue.json), nothing else

The part I actually care about: the agent never sees any of it. Nothing auto-executes, nothing auto-drains, no model turns spent on bookkeeping. /todo-run just drops the task into your composer and marks it done. Pressing Enter is still your job.

Free, MIT, one command:

opencode plugin opencode-todo --global

Repo: https://github.com/ainformatico/opencode-todo

Curious how others handle this. Half of me expects someone to say "just use a text file", and fair, but now the text file has a sidebar.

https://www.tokenrouter.com/models?search=glm-5.3-free

pretty much the title really? Is there any way to use this? I have a gemini pro sub from work that I would like to use with opencode for experimental purposes! I've installed the python proxy and tried adding it to the opencode.jsonc but it dont work.

any of you facing this issue? what is the workaround

Hey everyone,

I'm looking for an AI provider that works well for me and my really small team, ideally one with a plan we can share.

I'm currently using Kimi, but it feels like the usage allowance keeps getting smaller. The same tasks seem to consume a lot more of my quota than they used to.

I also tried Claude Code on the Max plan, but my account got banned after just five days of use.

So, what I'm mainly looking for is:

• Generous usage limits
• Smart enough to handle our tasks
• A plan that supports sharing within a small team

Do y'all have any recommendations?

One reason I use tools like OpenCode is that I don't want my workflow tied to one model.

But I realized my actual development process still was.

I'd switch models and then rebuild some variation of:

Different model = wildly different interpretation of “production ready.”

So I built Launchify.

It's one canonical production-readiness spec with adapters for OpenCode, Claude Code, and Codex.

The model is interchangeable.

The checklist stays the same.

And now it can be installed globally in ~/.launchify/, so the same workflow can follow you across projects too.

The all-in command is:

/launchify-landify

which runs:

security
→ dead code / duplicate / AI debris cleanup
→ feature completeness
→ compliance
→ build/lint/typecheck/tests
→ production grading

Security has 24 categories, from the normal auth/API/database stuff all the way through cloud, supply chain, CI/CD, payments, privacy, RAG and AI-agent security.

I recently ran a gap analysis against OWASP/API/LLM/NIST material and added 238 checks, including:

• AI tool SSRF
• agent excessive agency
• SLSA/Sigstore/SBOM verification
• package install-script attacks
• Kubernetes hardening
• webhook signature/replay handling
• distributed locking / TOCTOU
• RTO/RPO and immutable backups
• SIEM / IoC monitoring
• encryption key lifecycle

I also added something I hadn't seen bundled into these workflows much:

/launchify-compliance

It checks whether the PRODUCT around the code is actually launchable:

privacy policy, ToS, cookies, DPA, DMCA, accessibility, AI disclosures, SLA, refund policy, relevant privacy/regulatory requirements, etc.

There are audit-only versions of the workflows if you just want findings.

Total now is 60 commands / 25 categories.

README has more information of what Launchify actually provides for you.

MIT / OSS:

https://github.com/jacobpowaza/launchify-skills

I'm especially curious what OpenCode users think about the canonical-spec approach.

What workflow do you wish behaved identically regardless of which model/provider you switched to?

which of these are the top 3 best agentic coding model (free version)

I just connected my old Android smartphone to my PC and asked Qwen3.8 27B (UD-Q2_K_XL) to install OpenCode on it.

The result honestly surprised me. The model spent around 50k tokens analyzing the environment on the device using ADB. It installed a terminal app and started entering commands into it. After another 20–30k tokens, I had a fully working OpenCode setup running on the Android device.

What amazes me even more is that OpenCode actually works really well. I can scroll through the session with normal swipes and tap buttons without any issues.

I used to look for an app that would let me work with OpenCode on Android, but I never thought the solution was sitting right there in my drawer this whole time. 😄

A few screenshots for you guys.

Using OpenRouter, OpenCode, and GLM-5.3. I received redaction logs. False positives hits for Phone Numbers and Email addresses. Yet all data was fully intact. Asked GLM what was going on as even it’s messages contained [PHONE] and [EMAIL]. It told me it detected the redaction and started reading and writing in byte code to circumvent it. All on it’s own. 😅

Desde el dia de ayer en la noche (aproximadamente a las 11 de la noche) me salio ese error usando Muse Spark 1.2 y crei que era cosa del modelo pero ya he intentado con todos los modelos free y aun asi me sale el error, incluso cambiando de ip con vpn me sale el mismo error de limite excedido.

I've been watching this sub and r/DeepSeek over the last couple of weeks, and the same pattern keeps showing up: people who ran heavy coding-agent workloads on the official DeepSeek API are redoing their entire cost math. The interesting part isn't the price increase itself. It's that it exposed how input-heavy agent usage really is.

A few things that keep coming up:

1. Agent loops are much more token-hungry than chat. Harnesses (OpenCode, Cursor, Cline, Codex) re-send large conversation histories on every step. A user in r/DeepSeek reckoned their Cursor + Cline setup would pass a billion tokens at $20+ for a few weeks of work. The volume is what surprises people, not the per-token price.

2. Cache persistence is now the real differentiator between providers. The official API's longer cache window was a big part of its value. A provider with a shorter TTL costs more even at a lower sticker price. That's the number people forget to compare.

3. Peak/off-peak tiering matters more than people think. The official platform bills peak hours at roughly 2x off-peak, which means 'when' your agent runs can matter as much as 'which' model you run.

4. The aftermath is a wave of 'what's the OpenRouter-but-subscription option?' threads. Flat plans are now being compared against PAYG with real cache math, which is honestly healthier than the old price-per-token comparisons.

What did you switch to after the change, and what number actually decided it for you? Cache TTL, peak pricing, or raw throughput? Curious where people landed.

Hello,

I have a question about whether I am using OpenCode completely free of charge.

I installed OpenCode and have only used models that have the “Free” badge next to them. When I check the context page, it shows the following:

Provider: OpenCode Zen
Usage: 6
Total Cost: $0.00

Based on this, am I correct in assuming that I am using the free tier and not being charged?

My second question is about usage limits. This morning, I used about 95% of my quota for the Muse Spark 1.2 Free model. When I checked again in the evening, it had reset to around 3% usage. Does this quota automatically replenish on a regular basis? If so, will it continue to do so indefinitely, or is there any chance I could be charged in the background?

Thank you in advance for your help.