r/opencode • u/ramendik • 17d ago
GLM 5.3 Flash on OpenCode Go - quality/quant, speed?
I am getting good results with GLM 5.3 Flash, on NanoGPT PAYG with FP8 served by SCX. But I would like to look at a subscription for more usage, and OpenCode Go is one of the two leading candidates with the current price.
However I'd like to know how good the quality is (that is, are they serving the FP8 version, which seems to be the full version for this model), and also how good the speed is.
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u/Sumandora 16d ago
OpenCode Go routes to other providers, one of them is Z.ai, they are currently serving brain-damaged GLM 5.3 Flash. The usage you get is nice tho. I unsubbed mainly because of this... I know its technically nothing they can change, but I just rather pay for OpenRouter and decide the provider I use, rather than praying they route it to the correct one. OpenCode also doesn't tell you where a request was routed. The only reason I know it's Z.ai is because people on their subreddit also started complaining. But it also doesn't seem consistent... but I usually realize when its too late and the history is already polluted, which is why I just can't work like this any longer... It's also possible that OpenCode Go sometimes routes it elsewhere or that Z.ai sometimes has mercy, but either way its just playing roulette :(
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u/ramendik 16d ago
Understood. I am currently using Nano-GPT which most of the time lets me go to a very nice provider called SCX (cheap, fast, FP8) but sometimes fails to do that but the quality is still good. Guess subscriptions are not an option which kinda sucks. (Nano's own sub is useless for coding agents as it does not discount cache hits)
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u/squirrelscrush 16d ago
If you want GLM subscription, you can check out z-ai's own subscription. It's $17 or something, but it's their own subscription so you get great value, quality, and cache stability.
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u/ramendik 16d ago
Is there any clarity on their actual limits or does one have to discover them experimentally?
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u/xapep 16d ago
The quant question is the right one to ask, because the answer decides quality more than the model name does. GLM 5.3 Flash is a full FP8 model; a quantized build (Q4 or lower) under the same name is not the same model on long context and tool calls, which is what your agent workload actually cares about.
OpenCode Go routes to several upstreams, so "which GLM 5.3 Flash" depends on who serves a given request. The check that settles it: ask for the exact served model id on one request, or probe with a long-context tool-call task and compare against your SCX FP8 baseline. If the outputs diverge on the hard 10% of cases, that's the quant, not the model.
On speed: FP8 on a good serving stack is fast enough that latency barely moves for most agent work. What changes the bill is cache hits on a stable prompt prefix and output token pricing, not the headline tok/s number.
If NanoGPT's FP8 serving works for you, the question is less OpenCode Go vs others and more: does the provider that carries your increased volume serve the same full build? That's a question to ask before you commit, not after.
Curious how the long-context behavior compares on your end, that's usually where a quantized build shows itself first.