#Choosing the right model

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spring whale
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I'm trying to choose the right model for my use case. Basically I'm looking for a personal assistant to help me plan out my day based on short term and long term goals. And I need it to be free, or cheap enough to basically free. I'll be texting it maybe 20 times a day, i need it to give me summaries and updates 4-5 times a day, and maybe update me based on certain random variables anywhere from 0 to 30 times a day. It will be text heavy. No local llms. i have a minimal server i run it on and chat with via a discord bot. is openclaw even the right tool for me? if yes, what model do you suggest. if no, what am i looking for?

dense pondBOT
paper gulchBOT
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dense pondBOT
silver prawnBOT
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Yeah, probably, with one caveat: truly free is unlikely if you want an always-on hosted assistant and no local model. Cheap is very doable.

OpenClaw is a good fit if you want:

  • Discord as the chat surface
  • scheduled summaries
  • periodic check-ins
  • event-triggered updates

That maps well to your use case. Your minimal server is fine too, since the model runs remotely.

What I’d recommend:

  • Use OpenClaw if you want an assistant platform that can grow with you.
    • Heartbeat for regular check-ins
    • Cron for exact scheduled summaries
    • Hooks/webhooks for random-variable triggers
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  • Use something simpler if all you want is “Discord bot + planner”.
    • Then you’re really looking for a lightweight Discord bot + cron/webhooks + hosted LLM API

For the model strategy, I would not use an expensive flagship as the default.
Best pattern is:

  1. Cheap small hosted text model for normal chat, reminders, summaries
  2. Stronger fallback only for deeper planning / weekly reviews

That keeps cost low without making the assistant feel dumb all day.

For exact current model picks, ask in #models. Those change fast, and community recs there will be fresher than anything static.

Docs:

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If you want, I can sketch the cheapest practical setup for this in OpenClaw, like default model tier + summary schedule + trigger pattern.

spring whale
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i was looking into gemini and wondering if its free resources are enough for me

silver prawnBOT
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For testing the workflow, probably yes.

For depending on it every day, I wouldn’t bet your whole assistant on the Gemini free tier alone.

A few reasons:

  • Google’s free tier is limited to certain models
  • limits are enforced on RPM / TPM / RPD, so bursty updates can hurt more than the raw daily count
  • quotas are per project, not per API key
  • the docs explicitly say free-tier capacity can vary, and you should check AI Studio for your live limits
  • on the free tier, content may be used to improve Google’s products

For your workload, the risky part is not the 20 chats/day by itself. It’s the combo of:

  • 20 chats
  • 4 to 5 summaries
  • 0 to 30 event-triggered nudges
  • possible bursts in a short window
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That can still be fine if prompts stay short, but it’s not the kind of thing I’d call reliably free.

My honest take:

  • Gemini free tier is good for prototyping
  • cheap paid tier is better for a real daily assistant
  • OpenClaw still makes sense here, because it gives you the Discord + scheduling + automation layer either way

Official docs:

If you want, I can help you estimate whether your exact message volume would stay comfortably under a cheap paid setup, or help you design it so the free tier has the best shot.

spring whale
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what if i switch to PAYG but limit myself to free resources? is that a thing?

silver prawnBOT
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Not really.

With Gemini, the docs treat Free and Paid as different billing tiers. Once you link a billing account and move that project to paid, you’re not really doing “PAYG but only free resources”.

The practical version of what you want is:

  • move to paid
  • use a small prepaid balance
  • disable auto-reload
  • stick to the cheapest text models
  • monitor usage in AI Studio

That gives you a pretty hard ceiling. From the docs, paid setup usually starts with a minimum $10 prepay, and if your prepaid balance hits $0, requests stop.

So the answer is basically:

  • Free-tier-only while on PAYG: no, not in the way you mean
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  • Paid tier with a tiny capped budget: yes, that’s the sane version

If I were doing your setup, I’d probably use:

  • OpenClaw for the Discord/scheduling/automation side
  • a cheap paid model tier
  • prepaid credits as the safety rail

Docs:

If you want, I can help you think through whether $10/month, $20/month, etc. is realistic for your message volume.

spring whale
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how much do you think is a good budget for my use case

silver prawnBOT
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I’d start with $10/month, and treat $20/month as the “comfortable, don’t-think-about-it much” ceiling.

My rough take:

  • $0 to $5/mo: possible, but only if prompts stay short and you’re okay with some fragility
  • $10/mo: probably the best starting budget for your use case
  • $20/mo: plenty of headroom for a cheap text model, summaries, and bursty updates
  • $50+/mo: only if you accidentally run an expensive model as the default or let context get huge

For your workload, the real cost driver is usually context size, not message count.

So if you:

  • keep replies concise
  • keep summaries compact
  • avoid resending giant history every turn
  • use a cheap default model
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...then this should stay pretty reasonable.

If it were me, I’d do:

  1. Prepay $10
  2. No auto-reload
  3. Run it for a week
  4. Check actual usage
  5. Only raise budget if needed

That gives you a hard safety rail and real numbers fast.

If you want current hands-on model picks for that budget, I’d also ask in #models since those change constantly.

spring whale
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what if i create two projects, one with PAYG and the other with free resources? i'll use the free resources initially and fallback to PAYG if it runs out. is there an easy way to monitor how much of the limit has been used up and feed that data to the ai itself?

silver prawnBOT
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Yeah, that strategy can work, and honestly it’s probably the cleanest version of “mostly free, but not fragile”.

The important nuance is: I would do it as failover, not as “constantly measure remaining free quota and route perfectly”.

Why:

  • Gemini’s docs clearly expose rate limits and usage in AI Studio
  • but I haven’t seen a nice simple “remaining free quota” API that OpenClaw can just read and hand to the model every turn
  • so easy monitoring + automatic quota-aware routing is the hard part

What is a good fit with OpenClaw:

  • set free project/key first
  • set paid project/key second
  • let rate-limit / resource-exhausted errors trigger fallback

OpenClaw already has auth profile failover inside a provider, which is the right building block here:

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One caveat: OpenClaw also does session stickiness for auth profiles, so it won’t behave like a super-fine-grained “check quota before every message” router. It’s more like:

  1. use preferred profile
  2. if it starts failing, rotate
  3. stay there for a while

So my recommendation would be:

  • Yes to two projects
  • Yes to free-first, paid-second
  • No to expecting a super clean built-in “remaining free quota -> feed to AI -> switch preemptively” loop

If you want that last part, you’d probably need a custom wrapper/script around Gemini usage data, not just stock OpenClaw config.

Useful refs:

spring whale
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go ahead

silver prawnBOT
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Here’s the practical setup I’d use.

1. Keep OpenClaw

It’s a good fit for this because you want:

  • Discord chat
  • scheduled summaries
  • event-driven updates
  • a self-hosted control layer

2. Use two Gemini auth profiles

  • Profile A: free-tier project/key
  • Profile B: paid project/key

Set them up so free is preferred first, and paid is fallback.

OpenClaw already supports auth-profile failover:

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3. Use a cheap Gemini text model as the default

Not a premium one.
For your workload, cheap + fast matters more than “best possible reasoning” on every turn.

For exact current picks, check:

4. Let failover happen on quota/rate-limit errors

Do not try to build perfect quota-aware routing on day 1.

Just let the system do:

  1. try free
  2. if it hits quota / resource exhausted
  3. fall back to paid

That’s way simpler than trying to feed “remaining free quota” into the AI every turn.

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5. Structure the assistant like this

  • Normal chat: Discord thread / DM
  • Scheduled summaries: cron, 4 to 5 times/day
  • Random variable updates: webhook or hook from your own script/service
  • Optional heartbeat: only if you want ambient periodic check-ins

Docs:

6. Keep costs down with prompt design

This matters a lot more than people think.

Do:

  • keep summaries short
  • keep a rolling “today so far” summary
  • store long-term goals separately
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  • avoid replaying giant history every turn

Don’t:

  • send the whole life story back on every message
  • ask for long essay replies unless needed

7. Budget

I’d start with:

  • free project first
  • $10 prepaid on the paid project
  • no auto-reload initially

That gives you a safe fallback without surprise bills.

8. Monitoring

At first, keep it simple:

  • check AI Studio Usage
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  • check whether fallback is happening too often
  • if paid gets hit constantly, either tighten prompts or just accept that free tier is only for overflow testing

One important nuance

OpenClaw auth is session-sticky, so once a session falls over to paid, it may stay there for a while instead of bouncing back to free immediately. That’s normal.

So the architecture is basically:

Discord + OpenClaw + cheap Gemini model + free auth first + paid auth fallback + cron/webhooks + compact prompts

If you want, next I can sketch the actual config shape I’d use for that.

spring whale
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ah. but it won't be private if i do the free resources thing initially.
can't have that.

silver prawnBOT
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Yep, then that settles it.

If privacy is non-negotiable, I would skip Gemini free tier entirely.

Google’s docs say:

  • free tier: content may be used to improve products
  • paid tier: that changes, and paid is the privacy-safe path

So the sane setup becomes:

  • OpenClaw
  • paid-only Gemini project
  • cheap text model
  • prepaid budget cap
  • no auto-reload at first

That gives you:

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  • privacy
  • predictable cost
  • no weird free-to-paid routing logic

Honestly, this is simpler and better anyway.

If it were me, I’d do:

  • start with $10 prepaid
  • watch usage for a week
  • bump to $20 only if needed

So, short version:

  • OpenClaw: yes
  • Gemini free tier: no, if privacy matters
  • Gemini paid tier with a hard budget: yes, that’s probably your best fit
spring whale
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if i'm paying anyway, what do you think is the best model for my usecase? things will be very context heavy and will burn through tokens probably

silver prawnBOT
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If you’re paying and expect heavy context, I would optimize for cheap input tokens, not “smartest model possible”.

That usually means:

  • use a fast / flash-tier paid model as the default
  • use a stronger model only occasionally for deeper planning, weekly reviews, or hard reasoning

For your use case, that’s almost always the best tradeoff.

Why:

  • your workload sounds input-heavy
  • so the expensive part is likely the context you keep sending in
  • a premium model as the default will burn money fast without giving you much extra value on routine check-ins

So my honest recommendation is:

Best pattern

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  • Default: cheapest reliable long-context paid text model
  • Occasional override: stronger model for “think hard about my goals / priorities” moments

What I would not do

  • run the premium model on every chat
  • keep dumping giant history into every turn
  • confuse “large context window” with “good cost profile”

The bigger win is usually architecture:

  • keep a rolling today summary
  • keep long-term goals separately
  • inject only the relevant bits each turn

If you’re leaning Gemini specifically, I’d look at the paid Flash side, not the Pro side, for your everyday default.

For the exact current model name, I’d still ask in #models, because that changes fast:

spring whale
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is gemini the right provider? or do you think there is a clear better alternative i should use

silver prawnBOT
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For your priorities, I think Gemini is a very reasonable place to start.

You want:

  • cheap
  • private
  • text-heavy
  • likely lots of context
  • minimal server
  • Discord/OpenClaw on top

For that combo, I don’t see a clear universal better alternative.

My honest take:

  • Gemini is a good default if you care most about cost + context
  • other providers may beat it on some things, like tool reliability or “feel”
  • but they often lose on price, which seems to matter a lot for you
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So I’d frame it like this:

Start with Gemini if:

  • budget matters a lot
  • you expect long context
  • you can tolerate “good enough” over “best possible” on every reply

Consider switching later if:

  • tool use feels flaky
  • it starts misunderstanding your planning style
  • you decide quality matters more than cost

So no, I don’t think there’s an obvious “Gemini is wrong, use X instead” answer here.

I’d probably start with:

  • Gemini paid
  • cheap default tier
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  • OpenClaw for the orchestration
  • then reevaluate after a week of real usage

For fresh community opinions, still worth checking:

If you want, I can give you a decision rule for when to stay on Gemini vs when to switch providers.

spring whale
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any private free models i can experiment with first?

silver prawnBOT
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Honestly, not really, at least not in a clean, durable way.

If your requirements are:

  • private
  • hosted
  • not local
  • free

...that combo usually falls apart.

The usual tradeoff is:

  • free tiers often are not private enough
  • private hosted APIs usually mean paid
  • free + private usually means local, which you already ruled out

So for experimenting, your best bets are usually:

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  1. provider trial credits / signup credits, if available
  2. a paid tier with a tiny prepaid cap
  3. very short testing sessions before you commit to a real setup

If privacy matters, I would not waste much time hunting for “free but private” hosted options. That space is mostly marketing traps, limited promos, or terms you won’t like.

So my blunt answer is:

  • private + free + hosted: basically no
  • private + cheap + hosted: yes, absolutely

If you want, I can help you design the cheapest possible private trial run so you can validate the workflow without spending much.

spring whale
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the server is oracle cloud infrastructure's Ampere A1 4 ARM-based OCPUs and 24 GB of RAM. other processes may use 3-4 GB of RAM. are local llms out of the question?

silver prawnBOT
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Not completely out of the question, but I wouldn’t recommend local as your main plan on that box.

Why:

  • RAM: actually okay for small quantized models
  • CPU: this is the problem
  • No GPU: big problem for responsiveness
  • Context-heavy chats: especially painful on CPU-only local inference

So on that server, local is more like:

  • good for experimenting
  • not great for a real always-on personal assistant

You could probably run a small local model and see something work, but I’d expect:

  • slower replies
  • weaker planning quality
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  • worse long-context behavior
  • less reliable tool use / agent behavior

So my honest answer is:

  • Local for testing? sure, maybe
  • Local for your actual use case? probably not worth the pain

Given your goals, I still think cheap paid cloud is the better move, even if the server technically can host something small.

If you want, I can help you decide whether it’s worth doing one local test run just to satisfy curiosity, versus skipping straight to a paid private setup.

spring whale
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am i supposed to get a budget capped PAYG or is there a plan i can use that's more cost effective

silver prawnBOT
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For your setup, I’d go with budget-capped PAYG / prepay.

I don’t think there’s some magic “plan” that’s clearly more cost-effective once you want:

  • OpenClaw
  • your own server
  • Discord bot access
  • automation / summaries / triggers
  • private API use

Consumer subscriptions are usually better for using the provider’s own app, not for powering your own assistant stack.

So the cost-effective move is usually:

  1. API PAYG / prepay
  2. cheap default model
  3. hard budget cap
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  1. no auto-reload at first
  2. reduce token burn with compact prompts/summaries

That’s boring, but it’s the right boring.

So my recommendation is:

  • Yes: budget-capped PAYG / prepay
  • No: I wouldn’t expect a cheaper “plan” to beat that for your use case

If you want, I can help you choose between:

  • Gemini paid/prepay
  • another provider’s API
  • or “ditch OpenClaw and use the provider app directly” if minimizing cost matters more than customization
spring whale
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estimate my costs

silver prawnBOT
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Ballpark, assuming a cheap paid Gemini text tier, not a premium model.

Your traffic looks roughly like this:

  • light day: ~25 interactions
  • normal day: ~35 interactions
  • busy day: ~55 interactions

That’s about:

  • 750/month on the low end
  • 1,050/month normal
  • 1,650/month busy

Rough monthly cost

If you keep context compact

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(around 2k input / 300 output per interaction)

  • low: about $1/mo
  • normal: about $1.5 to $2/mo
  • busy: about $2 to $3/mo

If it’s moderately context-heavy
(around 8k input / 1.5k output per interaction)

  • low: about $4.5 to $5/mo
  • normal: about $6.5/mo
  • busy: about $10/mo

If you get really loose with context
(around 20k input / 2k output per interaction)

  • low: about $8/mo