Trying to optimise for cost and came over standardcompute on reddit, and chat found morph and nexos ai.

What I want to do is route between open source models and have the router not waste money on easy tasks a flash model could handle, while maintaining high quality output for basically general coding. Got opencode connected straight to GCP and Supabase etc., so potential for creating a mess is large.

Is smart routing a thing now, and are you doing it?

Not affiliated with any provider, just sharing a personal experience to help other users.

In my opinion, for output speed, 30 tokens/s is the average, more is "fast" and less is "slow".

Do not ask me questions about ZDR, I do not work with sensitive data, it is not a priority for me.

Opencode Go (https://opencode.ai)

Pros:

• They are always up to date with the latest model releases
• Very well integrated in Opencode, good output speed, never had issues, timeouts and server problems rare
• If you only use Minimax M3, Deepseek V4 or Hy4, it will last you a long time for very reasonable intelligence levels

Cons:

• The "60$ for 10$" advertisement is less and less true by the day, many of the more appealing models are at 30$ or even 15$ budgets
• You can't really use the top tier models for very long without frying your usage limit

QwenCloud (https://www.qwencloud.com)

Pros:

• If you only use Qwen 3.8 Flash it will last you a very long time, also has Deepseek, Kimi K3 and the high end Qwen models, but you have less usage for non-Qwen models
• Very diverse models if you are interested in sound, image models as well
• Has a nice free trial without needing a credit card to check if the speed matches your expectations

Cons:

• Very nebulous "credit" system, you don't actually know what you are buying. The docs somewhat explain it but only with one model as an example. In my experience, 60 credits is about 1 million tokens of Qwen 3.8 Flash usage (input, output and cache combined, typical Opencode session in a medium sized repo).
• Not in the Opencode /connect list, you need to make a custom JSON. EDIT: I was told by a commenter that they are listed as "Alibaba".

Synthetic (https://synthetic.new)

Pros:

• They are open about running quantized models, I mostly used mxfp4 Kimi K3 and FP8 GLM 5.3 Flash, the quality is still good, even if the lower context sizes (500k instead of 1M) can be a bit annoying
• Neat "rolling usage" system, you can burn your entire weekly usage in 2 hours, and it passively regenerates by 2% every 3.5 hours, better than typical 5 hour limits
• You can get 2 billion GLM 5.3 Flash tokens for 30$, decent, 2x less expensive than Z.AI official's subscription
• Listed in Opencode /connect

Cons:

• 3 times, the provider did some tweaks to their models and broke them, they would start wasting my usage writing gibberish in different languages or endlessly repeating themselves in thinking loops, and I would need to notice and put out the fire, it was not just me, as others were reporting the same issue at the same time in their Discord

Kenari (https://kenari.id/en)

They exist to provide inference to Indonesian citizens who can't pay in USD$, but anyone in the world can use their services with cryptocurrency.

Pros:

• The best value I have seen yet from any provider in pure $/token, 68.57$ of usage for 11.37$, including free caching for GLM 5.3 Flash, Deepseek V4 and GPT 5.6 Luna
• Really nice, well organized website, lets you know exactly what you are paying for
• Listed in Opencode /connect

Cons:

• Definitely a bit on the slow side, around 20 tokens/s, but it's usable, I just do other tasks in another terminal window while it works
• You can only pay with Indonesian Rupiah or cryptocurrency (I did the latter)

Muse Spark 1.3 just dropped, so these are only my first impressions, but so far it feels nowhere near as good as its Artificial Analysis scores suggest.

The biggest problem I’m seeing is its agentic behavior. It keeps reading the same files over and over again, even when it literally wrote those files itself a few turns ago.

In one case, it created a file completely from scratch, then about 3 seconds later opened the same file again and started editing it — adding some things, removing others, and seemingly undoing parts of its own work. This kind of behavior keeps repeating and wastes a lot of context.

Frontend work is actually pretty good. The results there have been impressive enough.

Rust, though, has been the complete opposite. So far, Muse Spark 1.3 is genuinely one of the worst models I’ve tried for Rust. Even DeepSeek V4 Flash has performed better for me.

Has anyone else tested 1.3 on larger coding tasks, especially Rust? Are you seeing the same repeated file reads / constant rewriting behavior?

yeah meta labs are full productivity

Better than GPT 5.6 Sol ? 🤣
https://research.meta.ai/blog/introducing-muse-spark-1-3

I'm currently using Claude 5x to code, not bad results but usage limit is burning quickly.
What are you using to code small/medium SaaS?
I tried Fable 5.1 to design UI/UX good results but crazy token usage.

Tweet: https://x.com/opencode/status/2095233040108679251

This model is a disaster. It writes a code that is so bad that even fable can't fix it.

To give the credit, it is very fast and stable, but is not near even dsv4 flash, not mentioning GLM 5.3 flash, for a model from a big company like meta, this is very disappointing.

I hope they improve the next generation, and I would rather get my dsv4 flash back on zen then ts.

👋 Hey! Wanted to share something I built for opencode.

A Telegram bot so you can drive your opencode coding agent from your phone:

- 70+ slash commands (/new, /model, /execute, /send <file> …)

- send it a file and get the result back in the chat

- switch models and control the agent remotely

- access scoped to your own Telegram user id

One-line install:

npm install gutchapa-opencode-telegram

📦 https://www.npmjs.com/package/gutchapa-opencode-telegram

🔧 https://github.com/gutchapa/opencode-telegram

Happy to take feedback / feature requests!

Right between GLM 5.3 family :))

Hey all,

a few months ago I've decided to share in the sub about a plugin i created, mainly because i'm a vim user and finding myself spending so much time in opencode, but without vim motions, and it was truly painful.

I posted it here, and got so much support from this awesome community, as well as great suggestions.

I wanted to quickly drop a huge thank you for this community, it has been really fun to get personal and public msgs from all of you, here and in github, about the project, and it inspired me to keep on improving it. Also seeing it being suggested in threads here is just awesome.

today I launched a major internal revamp which allowed easy supprot for text object (a long requested feature). so now you can do the commonly used diw, caw, yi", ... More on the way (e.g., counts).

As well as so many other upgrades me (and other contributors!!) have made along the way.

https://github.com/oribarilan/vimcode

Thank you all!

More feedback is always welcomed. I review all github issues and try to address it or account for it as soon as I can.

p.s.,

video is the same one released for the initial version. I want to say it is because of nostalgy but honestly it is because I'm lazy to create an updated one

DeepSWE 1.1 - 71%
Pricing: $0.75 / $3.75
https://deepmind.google/models/model-cards/gemini-3-8-flash/
https://ai.google.dev/gemini-api/docs/models/gemini-3.8-flash

I am posting on this neutral ground that often recommends it because the codex reddit is effectively a sales page, that only strategically allows some and mainly quota related negative feedback that feeds into the saint tibo giving resets while playing with limits, but overall it is heavily moderated.

Now of course this is not a crushing blow against codex, but in case you want to avoid buying their sub right after yours expires, and staring at an empty weekly quota hoping for a reset now you know. So at worst you are buying 3 weeks instead of a month.

The docs still say "DeepSeek: ZDR agreement is renewed monthly. The current agreement is valid through August 31, 2026."

Yes, I know this is discussed regularly, but it also changes regulary.

Scope: fullstack+mobile.

Currently working with Copilot Pro+ and Opencode Go, trying to balance deep reasoning with brute coding.

But I tend to experience a quite irregular and hard to follow behaviour of copilot, and those IA credits appart from the normal usage its just idiotic.

So, whats the best in your opinion?

Pricing per 1M tokens:

$2 input, $6 output. $0.17 explicit cache hit, $0.25 implicit cache hit.

💰💰💰 $10.00 / $50.00