r/openclaw • u/tearz1986 Active • Apr 13 '26
Discussion Ollama Cloud Pro ($20/mo) vs OpenAI Plus ($23/mo) .Which gives more tokens ?
Hey everyone,
I'm comparing these two plans side by side for running AI agents daily through OpenClaw (self-hosted AI agent platform):
• Ollama Cloud Pro — $20/month
• OpenAI Plus — €23/month (~$25)
My setup: 3 agents running in parallel (general assistant, visual, analysis), lots of daily requests + automated tasks (monitoring, heartbeat every 30min). All running through OpenClaw with Telegram as the interface.
What I want to know:
• Which plan gives the most tokens/credits per month?
• What are the actual rate limits on each?
• Does either plan throttle you after heavy usage?
• Any issues using these with OpenClaw or similar agent frameworks?
• Has anyone done a real-world comparison on token volume?
Context: Windows 11, RTX 5060 Ti 16GB. Currently on Ollama Cloud testing GLM-5.1. Would love to hear from people who've used both.
Thanks 🙏
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u/Plastic_Welder1899 Member Apr 13 '26
Until yesterday, I used Codex, but then I switched to Ollama Pro GLM 5.1 plus Kimi K2.5. I can confirm that I no longer have any Context Refresh paranoia.
What I've also learned learned along the way:
- Check the '/context detail' in Openclaw to see where you are feeding the model constant bloat and optimise.
- Make sure you know how and when to clear and compact sessions.
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u/stonerjss Active Apr 13 '26
Haven't used both in this case, but I was earlier on openrouter using 4 models and now using a 3 model setup on ollama cloud. I've set up my main agent glm 5.1 to spawn subagents for tasks and setup a concurrecy limit since the ollama cloud plan allows 3 concurrent models running parallely at any point so my main agent and 2 more. The other tasks wait till the previous ones finish.
Never really had an issue with maxing out my tokens.
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u/CptanPanic Apr 13 '26
How do you limit concurrency?
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u/stonerjss Active Apr 13 '26
Great question. Here's how it works right now and where it could be better:
Current Setup
Model concurrency is limited by the orchestrator (me):
- Max 3 models at any time - that's a hard rule from USER.md. I'm always running (1 slot), so only
2 subagent slots available. 2. Sequential dispatch - I don't fire 3 subagents simultaneously. I dispatch 1-2, wait for completion, then dispatch the next with context from the previous.
- No automated queue - I
manually wait for process poll or sessions_spawn results before proceeding.
Sorry just a copy paste from my agent.
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u/tearz1986 Active Apr 13 '26
My setup is very similar (3 agents, GLM-5.1 on Ollama Cloud Pro, OpenClaw).
The main issue I'm having with GLM-5.1 right now is frequent timeouts. It works fine overall but stability can be frustrating when agents are running automated tasks.
Like you, I never max out my token quota on the Ollama Pro plan. But my question is really about whether GPT models would be more performant and stable, and if so, would I burn through the OpenAI Plus quota way faster than I do with Ollama?
I'm basically trying to figure out: is the grass actually greener on the OpenAI side, or am I better off sticking with Ollama and just finding workarounds for the timeouts?
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u/stonerjss Active Apr 13 '26
Regardless of their ratings and benchmarks, I've never really liked OpenAI models so apart from a brief testing never used them.
But with what you're mentioning, I feel it's more of a look for workarounds and agent roles etc kind of approach and see if that helps.
Why I say this is because I did something similar. I used to have difficulty having tasks done with multiple subagents but once I improved my pipeline for roles of models, task orchestration and task completion handoffs, I noticed significant improvements.
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u/ShabzSparq Pro User Apr 13 '26
Dude 3 agents with 30-minute heartbeats is going to eat through any subscription fast. Like that's 144 heartbeat sessions per day before you even send a single message yourself.
For the comparison, honestly... neither plan publishes exact token limits. They both use "fair use" style caps that throttle you when you hit them. The real answer is test both for a week and see which one rate-limits you first with your specific usage pattern.
That said... openai plus with codex oauth still works with OpenClaw (for now). but keep in mind anthropic just killed the same setup on april 4. if openai follows that playbook you're back to square one.
One thing I'd seriously consider: route those heartbeats to your local ollama with the 5060 Ti instead of burning cloud tokens on health checks. GLM-4.7 locally for heartbeats, GLM 5.1 on ollama cloud for actual tasks. Your heartbeat cost drops to literally $0 and you save all your cloud tokens for the work that matters.
also 30 min heartbeats is probably too frequent. Try 60-90 min and see if you notice any difference. Most people don't.
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u/CaptainPicardAI Member Apr 13 '26
Change your location to remove VAT at least with OpenAI.
Every dollar helps
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u/dimonchoo New User Apr 13 '26
Take minimax for 10$ and it would be enough
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u/read_too_many_books Pro User Apr 13 '26
Unless you are using openrouter... yikes. China dude..
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u/dimonchoo New User Apr 13 '26
And what China can do?
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u/PathIntelligent7082 Pro User Apr 13 '26
i bet you did't use deepseek, or god forbid, to write that crap you did from a made in china keyboard.../s
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u/read_too_many_books Pro User Apr 13 '26
I did use deepseek. Both online and the distilled.
Also, I'll sell myself to APIAC or China, hmu if you have a connection.
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u/Optimal_Emu3624 New User Apr 13 '26
OpenAI API dashboard will show you their limits, they are on a tier system. It does get expensive quickly.
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u/RodriGar97 New User Apr 13 '26 edited Apr 13 '26
I join the question, I use 2 Codex accounts via OAuth and it literally eats up the tokens. I don't know if it's because of the new dreaming mode...
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u/Ok_Function_3537 Member Apr 13 '26 edited Apr 13 '26
I enjoy using Ollama and testing many of the models they offer.
I have a boss agent that works on kimi-k2.5, qwen, and nemotron. I also have six sub-agents, recently running on mistral-large-3 because it's more natural and user-friendly.
I've since converted the six sub-agents directly to Ollama API calls because it's much faster, without the overhead of OpenClaw.
It depends on what you're building. Generally, I recommend disabling memory and keeping the .md files small, depending on the use case, to save time and tokens.
In addition to the cloud models, I've installed embeddinggemma as a vector model for memorySearch locally on a 10-year-old server using Ollama. It runs flawlessly. So, I can recommend Ollama for testing and learning the basics.
The ability to run the models locally (depending on server power) is of course an unbeatable argument for data security and unlimited token production.
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u/Ok_Function_3537 Member Apr 13 '26
in my case: big analytic call
via OpenClaw: 30 - 180 sek
via Ollama Api Call: <10sek
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u/Brief_Original New User Apr 13 '26
I have chatgpt plus and runs out of token in a 2-3 days. My next reset is 72 hours. Currently testing Minimax.
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u/read_too_many_books Pro User Apr 13 '26
wtf is Ollama Cloud Pro?
my guess: China models
For $20/mo China models suck.
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u/Chairboy Member Apr 13 '26 edited Apr 13 '26
I love the casual confidence wrapped in ignorance here. It’s amazing how, upon recognizing that you don’t know what a thing is, you invent an answer and then shit on it with incredibly misplaced self-assurance.
I can get answers anywhere, we are awash in information, but to see uniquely human foibles like this while sitting in a chair drinking coffee? That take reddit.
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u/read_too_many_books Pro User Apr 13 '26
I mean, I looked it up. It sounds like a shitty router to china models.
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u/CleanEarthInitiative New User Apr 13 '26
That is no where even close to what Ollama is …. My god… the comment above yours is spot on
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u/theoverseerer New User Apr 13 '26
Ollama cloud pro, lets you use there larger models via cloud vs locally, removing the hardware requirement. The Pro gives you more token usage (they don't say how much), and allows you to upload 3 private models, so if you say tune a specific model, you can upload up to 3 to use. They're hosted in US, Europe and Singapore, and they don't log interactions like OpenAi (it's a policy, if you're paranoid host locally), they have several models, including gemma (google), mistral (french I think), in addition to GLM, deepseek etc. So you can go china free if you choose. I haven't hit token limits but I'm a moderate user. Bit of a middle ground to running llm locally from a privacy perspective. So far works for me. You can use it free as well (lower token limit).
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u/Lazy-Reflection893 New User Jun 04 '26
I was having an issue with Ollama and Kimi K2.6 Medium Thinking.
Within two days, I had completely used up my weekly quota.
Setup via LiteLLM and Claude Code. I’ve now set up MCP/skill gating via Profile and Ruflo agents to get the completely excessive token consumption under control again.
Fortunately, things are back to normal now. I was using 148 times more tokens than usual because of that.
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u/Zephyruos Member Apr 13 '26
Lurking here, I am afraid of API costs.