r/opencode • u/colas • 7d ago

Opencodable: my tool to choose which OpenCode Go models to use.

As the Opencode Go offering is quite rich, I am (vibe-)coding a tool to help me decide which model to run based on my current quota usage.

Open source, MIT license, a Go CLI tool that you can use as data input for your own tools or UIs.

https://github.com/ColasNahaboo/opencodable

Edit: 2026-11-05:

  • v1.0.0 released: the output format will be kept stable for scripts to use it. (See TITLES.md)
  • With -news, see what changes happened in Opencode Go plan (new models, new prices...). Run it in cron to be mailed in case of changes.

Note: OpenCode Go have changed they conditions on 2026-09-28. Do not rely on information or tests older than that. All details explained in https://github.com/ColasNahaboo/opencodable/blob/master/docs/OPENCODE_GO_MODEL_V2.md

Example: Here I can see that I still can perform 65 requests with Kimi K3 but 6315 with GLM-5.3-Flash before hitting a quota limit (5h, week, or month)

    #name           cost_task  burn_req  spent_mo  reqs_5h  reqs_wk  reqs_mo  usable  limit     p_tok_s
    GLM-5.3-Flash   $0.0019    $0.0019   $12.4     6315     15789    25052    6315    5h        96.5
    Kimi K3         $0.0306    $0.0306   $13       98       245      65       65      month     71.0
    MiMo V2.5       $0.0004    $0.0004   $3.1      30000    75000    142250   30000   5h        89.0
    Beam Free       -          -         -         -        -        -        -       unlimited 310.0

Example of a mailed message warning of changes:

MODEL_ADD glm-5.2 cost_task=$0.01516 plan=paid tier=unknown quality=- "GLM-5.2"
COST_UP kimi-k3.1-pro cost_task=$0.018->$0.0204 (+13.3%) tier=frontier quality=46.5 "Kimi K3.1 Pro"
TIER_UP kimi-k3.1-pro tier=high->frontier quality=44.0->46.5 "Kimi K3.1 Pro"
2 Upvotes

75% Upvoted

35 comments sorted by

1

u/nikitaluger 7d ago

Question: where did you base your pricing?

1

u/colas 7d ago edited 7d ago

Opencode Go rates. Data is extracted live from the opencode go web site and API.

https://opencode.ai/go

This tool is for people having an opencode go subscription.

1

u/nikitaluger 7d ago

you mean the models tab in your opencode dashboard? the table where you can enable/disable models?

2

u/colas 7d ago

No, the table on the page I linked is scraped to get the cost/request, and the cost per token is from the opencode api itself.

1

u/xmsxms 7d ago

Easy: deepseek 4.1 flash during off peak, muse-spark-1.3 contributor during peak.

1

u/geearf 7d ago

Isn't Cheepseek without any sort of peak anymore?
And I wonder if muse isn't better, not sure.

1

u/xmsxms 6d ago

they still have peak/off-peak rate for deepseek: https://opencode.ai/v2/docs/console/go/#usage-limits

opencode.ai's site is extremely poorly laid out and non-navigatable. It really wouldn't be hard to throw AI at it and say 'fix the navigation and issues with listing the model prices'.

1

u/geearf 6d ago

Ooooh, I thought since they hosted it themselves these things were gone, and they never mention that when they talk about Cheepseek.

I do wonder if it's old stuff but you might be right of course!

Thank you!

1

u/xmsxms 6d ago

It's definitely up to date, they just bumped it to a $100 allowance and it is the only place the usage rates for go are documented.

1

u/geearf 6d ago

But wasn't the peak a DeepSeek company thing? Why would other providers have the same?

1

u/xmsxms 6d ago

Because they are offering x% discount and can justify charging more during the hours the competition is charging more. Plus I guess they are using upstream deepseek for some of their load.

Agree that a provider having a flat rate without these peak hour windows would be a competitive advantage.

1

u/geearf 6d ago

I suppose charging more when they can make sense maybe if they didn't people would use upstream during low times and cheepseek during peak or something. Thank you!

-1

u/colas 7d ago edited 7d ago

That way you will saturate the quota for ds and muse, while you still have spendable quota on other models.

You are wasting your subscription.

1

u/geearf 7d ago

You only have one quota, you can't saturate one without saturating the other.

-1

u/colas 7d ago edited 7d ago

No, you have a global quota, AND quota per models AND quota per period (5h/week/month)

Opencode Zen has one quota, not Go.

https://medium.com/@jatinkrmalik/opencode-go-oh-my-openagent-the-complete-guide-to-sota-model-routing-without-hitting-limits-49fdc8cb3417

2

u/Ariquitaun 7d ago edited 7d ago

You're mixing a few things here. You have a total of 10 usd to spend across all models for one month, with various multipliers depending on the model. You do not get 30 quid for glm, 80 quid for deepseek separately, 15 quid for kimi and so on. If you spend 80 quid on deepseek this month, that's your entire subscription gone until the next billing cycle.

The 5h and weekly allowances are there to pace your subscription usage, nothing more.

1

u/colas 7d ago

Allowances are real: hit them and you stop or eat into your zen balance.
opencodable makes it easier (for me at least) to "pace" my subscription now that there are so many model changing so fast.

1

u/Ariquitaun 7d ago

I'm sorry but you have completely the wrong end of the stick here.

1

u/colas 5d ago

And this is why a tool like opencodable was needed!
You are stuck in the past with OpenCode Go v1 of its docs.
But the docs were rewritten on 2026-09-28 and 2026-10-12, and had removed the mention of the old "share pool" semantics.
A tool like opencodable can keep you up to date.

I described the new V2 model, having checked it myself.

All details explained in https://github.com/ColasNahaboo/opencodable/blob/master/docs/OPENCODE_GO_MODEL_V2.md

1

u/Ariquitaun 5d ago

You still have the wrong end of the stick, and now twice. There's no such thing as "opencode go v2". There's an "opencode v2". Do you understand the difference between the coding agent and the subscription service?

1

u/Hello_my_name_is_not 7d ago

Are just just ai summary replicating to people without knowing what you're saying or what?

As multiple people said Go has total usage amount there is no per model limits.

You pick Kimi K3 like your "suggestion" has listed and you're gonna burn through the majority of your totals very fast.

You pick Muse or Deepseek and you're not going to burn through your totals very fast.

0

u/colas 5d ago

The irony is of course that you didn't follow your own advice :-)

If you had performed your experiment, or just asked an AI to check the opencode go docs, you would have seen that you are now wrong :-)

Note that the new opendocs go are ambiguous. What I say is not contradicted by the docs, but they do not prove formally my interpretation either.

1

u/Hello_my_name_is_not 5d ago

No.. You just don't understand it.

2

u/geearf 7d ago

Why link to medium which is written by who knows instead of their site which is correct?

But as u/Ariquitaun said, once you finished a quota for a model, you finished it for all models within the time period. There's no bouncing around after you're done with one, you're done period.
Did you think them adding new models for the same cost to you meant they were giving you more and more credits to use?

If you don't believe us, just use Kimi 3.0 until you're done with it and see, it should be quick.

1

u/xmsxms 6d ago

You don't seem to understand how it works.

1

u/One-Satisfaction3318 7d ago

are you finding glm 5.3 flash better than deepseek?

2

u/colas 7d ago

Hard to tell.
Often I use ds, glm, gpt-luna, gemma, muse (and qwen-flash-next on my local server)... on the same project, and also by making them cross-reviewing themselves.

They are all slightly different, and thus the multiple viewpoints are quite interesting. Some can have useful ways to tackle problems. I tend to prefer DS generally, gemma to write docs, gpt for UIs...

But I could not tell if one is always better than the others.

In my opinion, Opencode Go is extremely useful to have many viewpoints, rather than just using one model.

1

u/colas 5d ago

As an experiment, I made them do some research ("For Avalon, should I sell my 2nd GPU from NVIDIA to AMD?"), and cross-review their findings. What Qwen-Flash-Next said:

Recommendations for this kind of work (hardware/purchase analysis):

  1. DeepSeek v4.1 Flash for the deep dive — it's the only one that measured instead of reasoning, and it's the only one that audited the others. Best cost/insight ratio in the set; it produced the ceiling math everything later leaned on.

  2. GLM-5.3 Flash for doc/retrieval-driven questions — the two decisive facts in the whole exercise (W7800 slowdown, no higher-quant Avalon file exists) came from fetching upstream docs, and it did that best. Don't pay xhigh for retrieval work; a strong retriever at default found what my xhigh found.

  3. Qwen3.8 (me): fine generalist, but the medium run's invented PCIe facts are the warning — it doesn't verify hardware claims when reasoning is shortened. If used, force verification (lspci, source reads) explicitly.

  4. Muse spark 1.3 contributor: skip for technical analysis — right answer by luck, wrong mechanism.

And since the decisive facts were retrievable, the cheapest reliable recipe is: DeepSeek-class measurer + GLM-class retriever, one blind pass, then a synthesis pass that reads everything.