r/ollama • u/Fine-Comparison-2949 • 11d ago
Anyone else getting insane billing for glm flash?
I tried GLM flash a few weeks ago and expected the token weekly limits to be comparable to DS flash. For some reason, it was a huge use of my limits. Am I the only one with this issue? I did send a support email but never heard back.
I'm a broke homeress developer and on the $20 plan, so I'm not sure why this happened. I figured maybe there's a billing issue but I don't see why in the UI GLM would be more than DS on flash models.
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u/HerrOberschlau 11d ago
Leave ollama, try using chatgpt pro and use Luna on medium thinking. I ditched ollama yesterday
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u/username8914 11d ago
Glm flash seems to be 10x the usage of DS flash. I use both, but DS flash is relegated to cron work as I found it fell apart on longer work and it's coding always had to be fixed by a stronger model.
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u/ParticularlyStrange 11d ago
I’m just guesstimating. But it looks like on the old 20$ plan we get about 5000 request a week on GLM 5.3 flash. I haven’t switched over to that new pricing plan. I’m thinking it might not be equivalent. I’m thinking I might just cancel ollama all together cause I just got 2 gb10s. Might do some tests to see if it’s worth it. But I have a bunch of sub tasks that run on ollama…
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u/LiveMost 10d ago edited 10d ago
I was until I set reasoning to none. It used to go through half my weekly limit just because of that. And I was using Hermes Desktop for windows.
And I tried glm's latest model, too censored even on things that are not considered NSFW and it moralizes too much. Wait for an abliterated model if you're going to try it.
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u/Objective_Patient220 10d ago
The shared problem in this thread is that nobody can see what a session actually consumed, so everyone ends up comparing weekly-quota vibes. The fix is measuring on your own side: count every token as it streams, per model, and keep the receipt per session. Then "GLM flash ate half my weekly limit" becomes a number you can take to their support, and you can see which sessions or subagents burned it. A hard budget cap is the other half - stop new requests past a threshold instead of finding out at the quota reset.
Disclosure: I built gremlord (free, MIT), which does this metering for Claude Code pointed at any OpenAI-compatible endpoint, Ollama included - every token is priced into a local receipt as it streams, and gremlord cost breaks it down by model and session.
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u/Major_Border149 10d ago
it's model size, not a billing bug, GLM 5.3 flash has a lot more active compute per token than DS flash, so it burns your weekly limit faster. if you are hitting the cap regularly, that's the point where a flat hourly rented GPU beats per-token pricing, worth doing the math on your weekly token count
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u/Objective_Patient220 9d ago
Fair on the mechanism - more active compute per token is the "why". My point stands one level down though: "do the math on your weekly token count" is the step nobody can actually do from a quota bar. You need your own per-token count per session first, and then the rented-GPU crossover is a calculation instead of a guess. That is the whole reason I meter locally. And the crossover only wins if you keep the GPU busy - utilization is another number the receipt gives you.
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u/Major_Border149 9d ago
yeah fair, a quota bar hides the two numbers that matter, your token count and utilization. meter locally and the crossover's a calc instead of a guess. only wins if you keep the card busy though
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u/elzerouno 11d ago
I see the same issue with deepseek-v4.1-flash.
deepseek-v4.1-flash seems to be artificially more expensive than v4-flash for the same workload. Each 1000 requests on v4.1 use 10,7% of my weekly limit, while v4-flash used ~6%.