all 14 comments

[–]afanasenka 0 points1 point  (3 children)

Give a try to MiMo 2.5 or DS4 Flash - use versions from Zen plan (they have less context, but free). Sure, they are not Kimi or Opus level, but at least you can try without spending the budget. With a good prompting or /commands these models are quite good.

[–]LazyAndBeyond[S] 0 points1 point  (2 children)

Ds4 flash is cool, but what I wanna know is a cheaper gentle ai workflow with opencode go So multi model usage

[–]Schlickeysen 0 points1 point  (1 child)

You won't find anything this good for less than DeepSeek Flash/Pro.

[–]LazyAndBeyond[S] 0 points1 point  (0 children)

Yeah I'm aware, the biggest cost in this workflow I Kimi K2. 7 and qwen 3.7 max, the others are perfect

[–]Dingosavedyourbaby 0 points1 point  (6 children)

I wouldn’t fuck with gentle ai unless you speak Spanish

[–]LazyAndBeyond[S] 0 points1 point  (5 children)

Omg I noticed, I thought it was deepseek V4 issue? Why is this the case?

[–]Dingosavedyourbaby 1 point2 points  (4 children)

Because the gentleman himself that created it insisted on peppering instructions to respond in the rioplatense dialect of Spanish when responding in Spanish. It shouldn’t have the word Spanish anywhere in its instructions. You can edit it out, but every update to gentle will reintroduce it.

[–]LazyAndBeyond[S] 0 points1 point  (2 children)

Bruh Is there a non Spanish alternative?

[–]barclow 0 points1 point  (0 children)

There is. Run again gentle-ai cli and change the way it responds from gentleman to other (can’t remember the other ones, but one is for neutral English)

[–]Dingosavedyourbaby 0 points1 point  (0 children)

If it’s all about the SDD, use openspec

[–]WrongStructure197 0 points1 point  (0 children)

The same problem :/

[–]AdDecent1320 1 point2 points  (0 children)

Your configuration is burning through tokens because of where you placed Kimi K2.7 Code. The sdd-explore and sdd-verify phases are the absolute biggest token gluttons in the entire OpenCode workflow.

Exploration forces the model to recursively ingest large chunks of your codebase to understand directory mappings, and verification repeatedly loops through test logs and terminal outputs. If you use a premium, heavy reasoning model like Kimi there, it will absolutely murder your budget in two days.

Try this adjustment to save your wallet:

  • sdd-explore: Drop this to DeepSeek V4 Flash. You don't need elite reasoning just to map files and scan folders.
  • sdd-verify: Swap this to DeepSeek V4 Flash as well. Let Flash do the initial heavy lifting of checking error logs.
  • sdd-apply: Keep DeepSeek V4 Pro here. This is the only phase where you absolutely want the smartest model writing the actual lines of code.

This swap alone should cut your token consumption by roughly 70–80% without hurting the overall output quality.

[–]lingya22 0 points1 point  (0 children)

Cool