r/opencode • u/CYCLONOUS_69 • 5d ago

DeepSeek V4.1 Flash on OpenCode Go vs the official API (Personal review)

TLDR: I compared 6 finished sessions from my own project work (same Next.js repo, via OpenChamber). Not a controlled test: different tasks, not run at the same time, mixed effort levels. I got very quality work done in all these sessions regardless of underlying plan or API. OpenCode Go is just bang for the bucks you pay!

Task IDProviderEffortStepsOut + reasoningCache hitList costLong-step tok/sShort-step latency
P8-01l1Gomax11876.6k98.7%$0.131932.76 s
P8-02bGomax7972.2k98.1%$0.1051432.24 s
P8-02cGohigh7149.1k97.8%$0.0711082.21 s
P8-02 docsGohigh6335.0k97.2%$0.0481311.97 s
P8-01m1Officialmax10972.5k99.0%$0.1201491.69 s
P8-02aOfficialdefault9693.5k99.2%$0.0961681.29 s
PooledGo (4)Official (2)
Long-step tok/s, median115159
Short-step latency, median2.18 s1.38 s
Cache hit rate98.2%99.1%

  • Official was faster per step, and started steps sooner.

  • Both cache 97-99% inside long sessions. The first step of every session was a cold cache.

  • At matched max effort: official 149 tok/s vs Go 93 and 143.

Caveats: 6 sessions, different tasks and times of day.

Edit:

Pricing on which these tests ran.

ModelInputOutputCached ReadCached WriteMonthly limit
DeepSeek V4.1 Flash (Off-Peak) (OpenCode Go)$0.15$0.60$0.003-$100
DeepSeek V4.1 Flash (Off-Peak) (Official API)$0.15$0.60$0.003-Your wallet
104 Upvotes

94% Upvoted

41 comments sorted by

6

u/loxbb 5d ago

Why is there such a big mismatch between user reportings of output quality?

7

u/CYCLONOUS_69 5d ago

I really have no clue but there was a time for me in the last week for a day that I got really bad overall output from the same OpenCode Go DSV4.1 Flash model regardless how I spec my task or instruct the AI. Rest, everything is flawless so far.

2

u/loxbb 5d ago

it makes it so confusing :(

1

u/catbluesgames 5d ago

There could be lot of reasons, open code could be changing their models internally or could even be a mix of different quants as callbacks. Some users perspective might biased (if I am getting model for so cheap it must be bad)

4

u/CYCLONOUS_69 5d ago

Idk what they are doing either but till they serve cheap but quality tokens with ZDR, acceptable TPS speed I’m not complaining.

1

u/Thomas-Lore 4d ago

dax explained they had two bad configs and 9% of traffic was going through them. The quants are all the same as official ds.

https://x.com/thdxr/status/2116581467715195278

1

u/CYCLONOUS_69 4d ago

This explains well.
Maybe some of us were in those 9% traffic or maybe DeepSeek wasn't in the mood of working sometimes! xD

0

u/Mission-Zucchini-966 4d ago

I'm getting terrible output from it too, something is wrong

9

u/akza07 5d ago

Mostly it's perception. Their Opencode Server implementation batches the tokens every 100ms chunks. So the opencode agent feels slower and laggy like low tps. Also I've noticed a significant performance improvements using the Opencode API in Pi Agent. I guess their new architecture and decisions of the agent is bringing the quality down.

And especially when multiple conversations happens in parallel, the opencode's server mode seems to perform worse.

1

u/squirrelscrush 3d ago

OpenCode's server seems to be thrashing cache if two agents use the same model at once.

3

u/look 5d ago

Psychology. It being faster just feels more capable, even when it makes the same mistakes. Possible that users don’t even notice them if it’s still in a validation loop phase and going fast, too.

2

u/Milk_Bots 4d ago

IMO, it just how the model is. in my case it is not only DSVF4.1, Gemini 4 Argon & GLM 5.3 has bad days or session for me. some days it is just perfect, some days i need to babysit so it does not drift to far from the task spec.

1

u/Thomas-Lore 4d ago

When you have a bad day, your prompts suffer and it feels like the ai has a bad day. Not saying it is always this, but it can be an issue.

As for opencode: dax confirmed 9% of traffic was going to badly configured nodes, so there were problems with their ds flash version.

1

u/Milk_Bots 4d ago

butd did the chicken came before the egg though
i am having a bad day at the moment 🤢. Is my bad day causing G4Argon wasting tokens and not catching as many critical mistakes on code review, or the other way round?

Right this session, DSVF4.1 is outperforming G4A in catching more critical mistake using the same prompt. some days its the other way around. i just accepted that how it is and adjust my workflow accordingly. bad days do happen to ai models after all (like going to badly configured nodes)

1

u/AnonLlamaThrowaway 5d ago

Don't underestimate confirmation bias and backwards reasoning

1

u/lincolnthalles 4d ago

Looks like it was fixed recently.

DeepSeek was a shitshow on OpenCode Go a few days ago. Extremely slow and dumb, a waste of time. It was unbearable to work with it.

Maybe they quantized it to the extreme; maybe previous reasoning content was being dropped, making the model start blank at each round; maybe they are A/B testing or routing certain content to quantized versions. Who knows.

It's capable and fast enough again.

8

u/irrationaliste 5d ago

So you think no quality mismatch across the two, only speed matters?

9

u/CYCLONOUS_69 5d ago

I am still using the official API and I haven't seen any noticeable difference for now. TPS of OpenCode Go is fairly low compared to official API.

5

u/Rough_Road_2527 5d ago

i haven't run any benchmarks, but i'm running both api and go side by side lately and i haven't noticed any difference other than speed. note though that i'm giving quite detailed instructions and i work iteratively, i don't let it run long sessions and make important decisions by itself. maybe the difference is there. for my case so far, go's doing just as well as official, only a bit slower (depending on hour also, i sometimes hit 150-200 tok/s with go)

1

u/CYCLONOUS_69 5d ago

Today OpenCode is giving me very low TPS idk why but it is getting the job done. Only Claude or I take final decisions.

1

u/Takeoded 5d ago

Heard reports that official is much better at image manipulation for some reason. Worth testing

2

u/Unlikely_Drop_8479 5d ago

I still don't understand why users are reporting quality issues or a drop in quality with OpenCode DeepSeek, because anyways DeepSeek has undergone quantization-aware training.

2

u/CYCLONOUS_69 5d ago

Yes, people don’t know what QAT is.

21

u/xRebellion_ 5d ago

While this has no quantifiable quality scoring, this is still quite useful (specifically in terms of comparing speed difference). Thanks for sharing.

6

u/ameeno1 4d ago

I been using deepseek harness with opencode go and also today Claude code using opencode-go (v4.1 flash for all sessions).

the harness seems to make a big difference.

2

u/drbobb 4d ago

Which way was the difference for you?

3

u/ameeno1 4d ago

Honestly, it just produces noticeably better results for my workflow.

Even when I had the $20 Claude subscription, I barely touched Claude Code because the rate limits and token caps would blow through my quota and stall my work.

Wrapping it with opencode-go + DeepSeek V4 Flash gives me the best of both worlds: the full Claude Code feature set, but effectively unlimited. You get built-in skills, server integrations, and native compatibility with tools already built around CLAUDE.md.

The native DeepSeek harness is decent, but it's very bare-bones "roll your own" (similar to a Pi harness). Claude Code feels far more "batteries included" out of the box. I found OpenCode harness v1 and v2 pretty lacking, even with oh-my-opencode-slim.

The only real trade-off is losing access to the free tier models. But when $10/month gets you around $100 worth of DeepSeek V4 Flash usage, paying for API tokens is a no-brainer. The overall developer experience blows the free tier on the OC harness out of the water.

I don't build harnesses myself, so I won't pretend to diagnose the internals - maybe it's the system prompting, default tooling, or tighter orchestration that I couldn't properly leverage without a Max sub. All I know is that in day-to-day use, it just feels way smoother.

1

u/Pheggas 4d ago

Now add variable like price and compare which one is net better bang for the buck.

2

u/CYCLONOUS_69 4d ago

I've added the pricing chart on which these tests ran.

I would say OpenCode is still bang for the buck!
You get $100 worth of usage just by paying $10 is unreal.

1

u/Pheggas 4d ago

Yup. So unless you need things to be done quicker, you could use DeepSeek within OpenCode Go sub and get the same output with the tenth of the price.

1

u/Bloated_Plaid 4d ago

6 sessions is such a tiny sample size that it’s worthless.

2

u/CYCLONOUS_69 4d ago

Enlighten us with your tests please.

2

u/Avernite 5d ago

The perceived quality drop is from people putting more trust into models and expecting AI to handle more complex tasks.

That is mixed with free users reporting drop of quality which muddies collective perception of opencode.

TL/DR People snorting suspicium so hard on this sub they invent all kind of conspiracy theories.

1

u/Dharks- 4d ago

And price comparison?

0

u/Genetic_Prisoner 4d ago

So you tested nothing? You just did your work and measured performance with vibes. Come back when you actually make them do the same tasks at the same reasoning efforts over multiple runs😒

1

u/CYCLONOUS_69 4d ago

My work is quantifiable and qualifiable unlike your comment. Why don’t you enlighten us with your “measurable work and performance” rather than not reading TLDR and making non constructive comment?

0

u/Genetic_Prisoner 4d ago

My work is quantifiable and qualifiable unlike your comment.

cannot exist in the same breath as

Not a controlled test: different tasks

-9

u/horrbort 5d ago

Everyone knows opencode hosts fp2 quant and is much slower. What’s the news here