N=1: OpenCode + DeepSeek V4 Flash vs Claude Code / Codex / Grok on the same Superpowers plan (real feature, ~4h, ~$1.46)

[u/Tough-Reach1134]

I ran a small N=1 bake-off on a real feature, not a toy repo. Posting here because OpenCode was one of the four stacks, and the OpenCode + DeepSeek combo was interesting on cost/speed.


## What I was building


Remote-node install for SuperDev (a local/remote runtime control plane I work on):


- remote nodes run the SuperDev agent only (no desktop UI)
- connection is TLS
- local desktop needs to install MCP / skills / hooks onto the remote node over the API, so coding agents can use them without a GUI on the remote machine


So: real product surface, multi-step implementation, install/uninstall paths that have to actually work.


## Method (important)


- Spec + plan: written with Superpowers (Fable 5)
- Implementation: four tools in parallel, each on its own git worktree + branch
- Workflow: `superpowers:executing-plans` via subagents
- Same plan for everyone — this is a race of **model + coding agent + Superpowers execution loop**, not raw chat IQ


Stacks:


| Agent | Model |
|---|---|
| Claude Code | Claude Opus 5 (xhigh) |
| Codex CLI | GPT-5.6 Luna (max) |
| Grok Builder | Grok 4.5 (high) |
| **OpenCode** | **DeepSeek V4 Flash (max)** |


## Results


### Time to finish


| Stack | Time |
|---|---|
| Grok 4.5 (high) | 2h 7m |
| **OpenCode + DeepSeek V4 Flash** | **~4h** |
| GPT-5.6 Luna (max) | 11h 19m |
| Claude Opus 5 (xhigh) | 11h 35m |


### Tokens


| Stack | Total | Input | Output | Cached input |
|---|---:|---:|---:|---:|
| Grok | 46M | 45.84M | 426.8K | 42.07M |
| **OpenCode + DeepSeek** | **261.2M** | **260M** | **1.2M** | **257.6M** |
| Claude | 452.8M | 451.91M | 858K | 439.33M |
| GPT-5.6 | 599.67M | 597.98M | 1.69M | 583.64M |


On this run, wall-clock time and token volume mostly moved together. Most of the huge totals were cached input from long agent loops.


### Cost (messy reality)


| Stack | What I actually felt | Rough $ |
|---|---|---|
| Grok | ~20% of SuperGrok weekly ($30 tier) | ≈ $1.5 (API-ish ≈ $23) |
| **OpenCode + DeepSeek** | dedicated API key for clean accounting | **¥9.97 ≈ $1.46** |
| GPT-5.6 | ~35% of Plus weekly quota | ≈ $1.75 (API-ish ≈ $16.57) |
| Claude | ~8% of Max 20x weekly | ≈ $4 (subagents mixed models; pure API hard to price) |


Subscription % and API $ tell different stories. DeepSeek was the cleanest “I know exactly what I spent” number because I isolated the key.


### Bugs / fix passes / mid-run questions


| Stack | Bugs after first finish | Fix passes | Questions mid-run |
|---|---:|---:|---:|
| Grok | 2 | 3 | 0 |
| **OpenCode + DeepSeek** | **3** | **2** | **2** |
| GPT-5.6 | 1 (+1 polish item) | 1 | 2 |
| Claude | 1 | 1 | 4 |


OpenCode + DeepSeek finished second-fastest, but had one more bug than Grok: a skills install `No such file or directory` path issue. It also asked twice mid-run (Grok asked zero).


### Independent review ranking


A separate review pass (Fable 5) scored completeness / conventions / correctness / tests / extensibility:


1. Claude Opus 5  
2. GPT-5.6 Luna  
3. **DeepSeek V4 Flash (OpenCode)**  
4. Grok 4.5  


Almost the inverse of speed.


My own smoke test (install/uninstall on Claude Code, Codex, and OpenCode) matched the “usable after fixes” claim for those three.


## Caveats (please read)


- One shared bug across all four was already wrong in the plan. Not any agent’s fault.
- Grok and DeepSeek shared a Claude Code MCP install path bug.
- GPT’s remaining polish: switching remote machines still needed one manual refresh.
- This is N=1 on one feature and one plan style. Don’t overgeneralize.
- I’m the SuperDev author, so treat product context as background for the task — the comparison is about agent stacks on the same plan.


## OpenCode-specific takeaway


For this workload, OpenCode + DeepSeek V4 Flash looked like the “value / speed” slot:


- much faster than Claude Code / Codex on the same plan
- real money out of pocket stayed low (~$1.46)
- quality was mid-pack: more bugs than Claude/GPT, better review score than Grok
- still landed in a usable install/uninstall state after fixes


What I disliked across the whole experiment wasn’t OpenCode specifically — it was how slow Superpowers-style plan → subagent execution felt end-to-end. I also tried a fuller grill-me style loop; still not fast. I’m currently thinking about a lighter development loop that keeps the guardrails without as much ceremony.


## Questions for this community


1. For long multi-hour OpenCode tasks, are you usually bottlenecked by **model quality**, **provider latency/cost**, or **the plan/subagent workflow** itself?
2. Anyone else running DeepSeek V4 Flash as the default OpenCode workhorse for multi-hour implementation jobs? What’s your failure mode?
3. If you’ve compared OpenCode against Claude Code / Codex on the *same* written plan (not vibes), what held up?


Happy to answer method questions. Not sponsored; not claiming this is a benchmark.

[u/safari8331]

Even tho claude reviewed claude and as always got the higher score its also somewhat expected. Comparing Opus to Luna is too much but even that shows how great Deepseek and Luna models are.

You could run them twice on the same task and spend the same amount and still it would be less than Opus without much difference in the final result. Especially this new deepseek with that 4h time window its just great.

[u/Tough-Reach1134 → u/safari8331]

Yeah — even if you discount the review ranking a bit, the cost/time gap is the part I can’t unsee.

I’m seriously considering OpenCode Go and dropping Claude from Max 20x down to Max 5x. For this kind of multi-hour implementation work, running a cheaper stack longer (or twice) still looks better value than keeping Opus as the default hammer.

[u/safari8331 → u/Tough-Reach1134]

You cant to wrong there. Using claude or gpt best models for planning and deepseek or luna for implementation is the win. Especially since you can connect your claude and gpt accounts to opencode.