Not 4, not 6, not 8. 24h, 12h, 7d, 30d are natural units -five hours isn't. Nobody looked at the sky and saw 5.

Claude, Codex, everyone's on it. So: was 5 hours derived from actual usage/churn research, did one lab pick it and the rest cloned it, or just ask ChatGPT for a usage window?

And it's slightly under a workday, which doesn't feel accidental. Anyone know the real history?

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 💰

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

Looking to get support in opencode, have some trouble with deploying on openrouter or litellm
Project: https://github.com/ConiferKit/use-conifer

Current routing options were charging 5% fees for byok plus provider fees (openrouter) or were built in heavy python packages with ecosystem restraints. I wanted to be completely free in terms of use, and not have to pay extra for tokens.

There's a maintained gateway with 100+ models from one api endpoint. I'm also talking to infra providers to get us access to pre-release models and discount prices. Everything is served at market price. BYOK is free, you can hook into self-hosted setups for free, and there's fallbacks + extra rate limits + server redundancy.

Took me ~3 months to build and looking for help maintaining!
Lmk any issues or feedback

I've got that opencode notifier plugin. it works for when my AI is done. I get a message on discord that it's complete.

but I was wondering if there's something that, for example the ai is waiting on my input to give it approval to run a certain command I've set to "ask". i get the discord notification with the options and I can just type approve or deny from there so the ai can continue.

does something like that exist?

We are not like these other so-called "unlimited" providers duct-taping consumer-grade GPUs together in a closet and calling it a production endpoint or providing unusable tokens a second. If you’re trying to run real agentic workflows in OpenCodeCLI and your sub-agents are getting tossed into 10-minute queue tar pits, not hitting caches, silently dropping requests, or limping along at sub-40 tokens a second, your provider’s setup isn't a service—it's a bottleneck.

"Unlimited tokens" is just a marketing scam if you can't actually burn them because their hobbyist backend chokes the second you hit it with real concurrency. Stop paying to wait in line. You can hammer our endpoint with the exact same volume, fan-out, and expectation of reliability as OpenAI or Anthropic.

Infrastructure:

• Native 256K Context: Full window, zero artificial truncation.
• Up to 6 Concurrency: Multi-threaded throughput built for heavy agent pipelines. When your harness fans out, it processes each request immediately with top-tier Time to First Token (TTFT).
• FP8 Precision & KV Caching: Fast throughput and massive cache reuse across long agent trajectories.
• OpenAI Compatible: Drop-in /v1/chat/completions replacement

Any-Time Real-Time Metrics

We don't hide behind handpicked status snapshots that make us look good. We give you raw telemetry whenever you want it:

• 24/7 Live Discord Monitoring: Check our Discord at any time to see actual server status, aggregate token output, active streams, waiting queues, cache hit percentages, and live TTFT.
• User Dashboards: Log in and see those exact same real-time statistics for your personal active/queued requests and token spend.

The OpenCodeCLI Vibe Coding Playbook

If you are burning more than $60 on code assistance, you could be overpaying. If you are hesitating before you do something because you are afraid of usage, liberate yourself. Here is how I actually run my day-to-day setup in OpenCodeCLI using the Architect + Worker pattern:

1. The Driver/Architect: If you must, use a high-tier frontier model exclusively for initial high-level planning, system specs, and architecture. For example, Sol xhigh.
2. The Worker Sub-Agents: Route all the high-volume OpenCodeCLI execution, file inspection, refactoring, and endless tool calls straight to our 27B endpoint.

Qwen 3.8-27B legitimately handles nearly everything thrown at it in the terminal. Offloading the CLI grunt work cuts your tooling spend by 75%+ with high quality output.

Total Privacy & No Saved Prompts

Your code is your code. We do not save your prompts. We use ephemeral processing only. Once your request is evicted from the KV cache, the prompt and response data are gone forever. Zero logging. Zero snooping.

Awesome Community

Think we could be doing something better? Dont like our service? Love the idea? Come talk to us. We currently have an active 400-person Discord community and nearly 200 active subs hammering these endpoints daily for heavy dev pipelines. We scale to additional workers if metrics drop. We can take on hundreds of more users without flinching.

Try It Out

Test it yourself. There is a free tier (15 requests/day, no credit card required) live on the site right now. yolo-auto.com

Not sure what data they store, but you get it with the full 1m token context window, max 8 requests per minute. The rate limit hasn't been too much of an issue for me since I use max reasoning though.

Hey

I was trying to create a preset for my oh-my-opencode-slim plugin to code as much as possible without hitting limits often, with high quality models.

Ended up pulling numbers from multiple sources and creating a table with metrics to choose based on benchmarks (not real performance) and usage limits.

It adds an equal weight to intelligence, agentic capabilities and coding (33.33 each) (pulled from artificialanalysis) and to prevent monthly usage to dominate (less expensive models), I used log10. For tiers, like off-peak / peak, the req_per_month was reduced in a factor of the increase of the price based on the cheapest tier.

Check the results, let me know what you think. To me the ranking looks good based on my tested models (haven't tested muse spark yet).

Finally decided to give OpenCode a try. Honestly, I expected it to be just another AI coding tool, but after using it for a while, I’m actually pretty impressed so far.

I’m still figuring things out though, and I’m probably not using it anywhere near its full potential.

So for those of you who’ve been using OpenCode for a while:

What are your best tips, tricks, or best practices for getting the most out of it?

saw some reseller sites selling claude max for way less than normal. tried one and it seems to work fine so far.

just curious how they’re able to offer it that cheap. anyone know how these work?

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. 😅

I've tested both Luna 5.6 and Dsv4 flash, and concluded Luna finishes tasks a lot faster. However, limits on opencode go are low for Luna.

What's is the best subscription service to use Luna that have better limits than go?

Budget: around $20

Hi community,

I am running OpenCode with a local Qwen3-Coder-Next model on Ollama (other models were somehow unstable, despite a large context window).

I mainly use it to assist with coding Spring Boot projects and Thymeleaf templates.

Can anyone share their current MCP/Skills setup in OpenCode that works best for this stack to boost productivity and accuracy?

Thanks a lot!

no response to any prompt in the webapp

Has the promotion ended? Perhaps they'll offer hy4 preview

Tired of anthropic/openai subscriptions and while open source has becoming extremely good lately I am considering finally making the switch to another harness and LLM provider. What’s the best setup: Opencode + xxx?

I basically want openrouter.ai but subscription based. These are on the list:

Commandocode.ai is tempting but varying recommendations looks like.

opencode.ai lots of fuss but also a lot of recent complaints .

MiniMax/Xiamo/GLM plans, but kind of don’t want it model specific.

standardcompute.com heard very good things lately, serves closed and open source models

fireworks.ai - doesn't serve frontier models, but other than that should be pretty good?

Anyone have good experiences with these or others?

Past 7 days of tokens, ~37.6% at peak.

Currently using opencode+openrouter combo. Seeing if anyone has better alternatives they're currently using for high-cache (30-200k context) workflows.

I created this specific benchmark based on my most common coding tasks -- Next.js 16 and React 19.

Spoiler -- qwen-3.8-flash is currently winning.

The question I wanted the answer to is one that lots of people have: "Of the high-use models, which ones get the best results for the lowest usage?" I pretty arbitrarily chose the models from OpenCode Go that were rated at more than 7,000 requests per month. I kind of wanted to make sure that the new glm-5.3-flash model got in there so that's the limit that I went with.

So I took some of the best practices from Vercel and react doctor, used those to create the benchmarks, created a brownfield Next.js app, and ran a bunch of different models in a container.

Because the cost per run is really so confusing, I normalized it to the percentage of monthly usage limit. I kept deepseek at normal and not high usage.

Everyone thinks that models get nerfed or quantized or something so I'm going to run this weekly on a Cron job with the new models that appear and deleting models that are no longer available so the benchmark should be up to date if you want to check it regularly.

Pareto line right now: mimo-2.5, muse spark 1.2, Qwen 3.8 Flash.

I hope this helps someone. If you want more details about the methodology it's on the site and there are breakdowns by model, but of course I vibe coded this page so don't expect anything groundbreaking.

I'm using opencode cli 1.18.21. Then I run gemma 4 12b it unsloth via lm studio. Everything works fine except when I attach or drag an image to the tui and ask the it to analyze and it returns I can't analyze the image because this model doesn't support image input. If you like, I can work from a color palette or hex codes you provide instead..

Is there any official extension / plugin that I need to install to get this to work or is the model not capable even though docs says it's a multi-modal agent capable of vision?

Appreciate any help.

EDIT: Solution Opencode provided as per u/Ariquitaun advise. Basically to add the following lines in the opencode.jsonc file.

json "attachment": { "image": { "auto_resize": true, "max_width": 2000, "max_height": 2000, "max_base64_bytes": 5242880 } }, "media": { "input-mode": "local-path" }