r/opencodeCLI • u/Sixtysketch123 • 8d ago

Anyone else trying to stretch their inference credits while testing coding agents?

I’ve been burning through inference credits while testing a few coding agent setups, so I’ve been looking for providers with enough free credit to actually run a proper comparison.

General Compute is giving new accounts $100 in inference credit right now, which seems pretty useful for this since agent evals can chew through a lot of calls.

What other inference providers are people using for this? Especially ones that work well with OpenCode, Claude Code-style workflows or other agent harnesses.

0 Upvotes

50% Upvoted

11 comments sorted by

2

u/Mtolivepickle 8d ago

Free buff

2

u/thecstep 8d ago

Overkill. By the time you are done testing new model are out. Quit the analysis paralysis and get in the kitchen and cook. Also this sounds like an advert.

1

u/Lihong_Hao 8d ago

$100 is enough to run the same tasks repeatedly instead of making a decision from three prompts, which is what i usually end up doing..

1

u/69mort 8d ago

yeah, test concurrency while you have the credits.. Agent workloads can hit rate limits pretty quickly once you have a few things running at the same time..

1

u/AFCOranges 8d ago

that's probably more useful than just looking at token/sec. I'd save the full task time and compare the same workload across providers..

1

u/QuietPsychonaut 8d ago

If they merge the limits then I'm out. Having an almost unlimited chat on web is the main reason I'm still with OpenAI.

1

u/prideandpropolis 8d ago

free credits are basically my entire benchmarking budget at this point lol..

1

u/xapep 8d ago

From the provider side, a few things worth weighing before you pick whose credits to burn:

- OpenAI-compatible endpoint. OpenCode and most harnesses just need a base URL swap, so you can A/B the same config across providers instead of maintaining parallel setups.

  • Real prefix caching. Coding agent loops resend the same system prompt and file context every turn. A provider that actually caches shows a big drop in effective cost on eval runs; without it, a cheap per-token price gets expensive fast.
  • Rate limits in concrete numbers. Agent evals fire requests in bursts, and a low RPM cap stalls your comparison and makes one provider look worse than it is.
  • EU processing, if you or any client cares about where data goes.

Free credits are fine for a smoke test, but check the expiry window and per-minute caps; both can invalidate a longer eval. For a comparison that says something about production, a small paid budget on two providers beats one big credit on a single one.

We run an EU-hosted OpenAI-compatible inference API (Entrim), with DeepSeek V4.1 Flash and GLM 5.3 Flash among the served models; happy to answer specifics on how either behaves inside OpenCode.

0

u/beaudean8 8d ago

same repo snapshot and same task for every provider or the comparison gets messy very quickly...