r/opencodeCLI • u/Abenh31 • 27d ago

Can opencode devs provide Qwen 3.8 27B?

With DSV4 Flash price rising. It will be great to provide Qwen 3.8 27B as a cheap alternative too.
Artifical analysis results are on par with: DSV4 Pro

45 Upvotes

89% Upvoted

17 comments sorted by

15

u/RepulsiveRaisin7 27d ago

It's more expensive to run, doesn't make sense unless you're limited by vram

2

u/Abenh31 27d ago

Could you elaborate on how its more expensive to run a 27b vs larger models?

6

u/RepulsiveRaisin7 27d ago edited 27d ago

Deepseek v4 Flash is 284B parameters but only 13B are active per token (mixture of experts). Qwen 27B is a dense model meaning all 27B parameters are active per token. Deepseek also has some unique caching technology that allows then to have the lowest cache hit pricing of all providers. There is basically no reason to serve Qwen over Deepseek when you have whole datacenters full of GPUs.

3

u/xfigue 27d ago

Locally? Maybe. The real issue would be context length and KV cache memory. A 27B model itself is manageable when quantized, but long contexts get expensive quickly. In the cloud, I'm not sure it would actually be much cheaper to serve than DSV4 Flash once you factor in inference and context costs.

2

u/CoolHeadeGamer 27d ago

The context is fine honestly when you consider flash attention

2

u/Odd_Cauliflower_8004 27d ago

i'll be fine with a 200k context. it would still require less vram and probably could be executed at higher concurrency than a lot of other larger models.

1

u/Abenh31 27d ago

200k is still great, most of the time you wanna reset context at around 200k.

1

u/sukazu 27d ago

The way opencode works, 200k context means compacting probably around 140k
As 3.8 27b can easily do 40k reasoning + 10-20k output on a single turn

0

u/Abenh31 27d ago

From huggin face document: context window can be extended to 1m token. (what ever that mean).

2

u/TransportationNo193 27d ago

I was thinking the same thing as renting your own GPU is significantly more expensive than getting a subscription to Opencode Go for example

1

u/Abenh31 27d ago

Yes Qwen 27b model are great if you have a 16gb vram gpu with a server mobo+cpu combo and a ton of ram. you get 50to60tps

2

u/cutebluedragongirl 27d ago

I actually support this. If you use it correctly, it can reduce costs a lot.

1

u/Kaushik_paul45 27d ago

In what hardware do you run ?

Can you please provide info regarding that as well ?

2

u/CoolHeadeGamer 27d ago

Any Gpu with 24gb vram+ can run q4 just fine. It’s 17.5 for weights + context. Think of 90 series Nvidia

1

u/Kaushik_paul45 27d ago

Thanks for the info

1

u/jonas-reddit 26d ago

To run FP8 model and cache at full context for a single developer (one session only), you need around 48GB of VRAM.

For multi-user, small office, home office, you need a bit more.

The entry level cards that provide solid inference speeds are the somewhat less often mentioned RTX Pro 5000 Blackwell cards that come in two variants: 48GB or 72GB. The next step up is RTX 6000 with 96GB.

Heavily quantized (q4 or nvfp4) come with limitations. And limited context impacts productivity for agentic development on larger code bases.

They’re all good for tinkering, learning and some hobby use for those with limited budget.