AI budget guides
Understand token costs, subscription credits and workload assumptions with practical, source-checked guides.
Choose the question you need to answer. Each guide explains its assumptions and links to the provider documentation. Pricing is a dated snapshot, not a live quote.
Ollama Pro vs Max: start with the bill, not the allowance
Compare Ollama Pro, Max, PAYG and Team by monthly cash, included usage, break-even points and workload limits. Source-checked September 5, 2026.
Read guide →AI credits are not your monthly cash bill
Understand included usage, subscription fees, overage and remaining credits. Worked Ollama examples separate consumption value from actual cash outlay.
Read guide →Cache and peak pricing without double-counting tokens
Avoid double-counted input tokens. Learn cached-input semantics, token-weighted peak rates and a complete synthetic Ollama GLM 5.3 cost example.
Read guide →AI token cost calculator
Calculate input, cached-read and output token costs with your own API rates. See per-request and total consumption without uploading prompts.
Read guide →LM Studio vs Ollama: choose a workflow before a price tag
Compare LM Studio and Ollama by local workflow, API integration, privacy boundaries and total cost. A practical evaluation checklist, not invented benchmarks.
Read guide →Ollama cloud limits: identify the constraint before changing plans
Understand current Ollama cloud limits, legacy quotas, concurrent requests and 429 errors. Diagnose the actual constraint before changing plans or retry settings.
Read guide →Anthropic prompt caching: budget the write before celebrating the hit
Plan Anthropic prompt caching with separate write, read and ordinary input costs. Worked TTL examples and a measurement checklist explain when reuse pays off.
Read guide →OpenAI prompt caching: check the model generation before the discount
Understand OpenAI prompt caching by model generation, including current write charges, usage fields and stable-prefix tests. Avoid outdated universal discount claims.
Read guide →Ollama API usage: turn response metrics into a cost estimate
Read Ollama API token and timing fields, reconcile streaming responses, avoid double-counting cache, and distinguish cloud consumption from local running costs.
Read guide →Ollama with Claude Code: connect the tool, identify the bill
Connect Claude Code through Ollama, distinguish local and cloud execution, verify the active endpoint, and budget a coding task without confusing subscriptions.
Read guide →Ollama in Docker: budget resources and keep the endpoint private
Plan an Ollama Docker deployment with loopback networking, persistent model storage, measured resource limits, and an honest local-versus-cloud cost comparison.
Read guide →What is a context window in an LLM, and what does it cost?
Understand context-window capacity versus token consumption, reserve room for output, and compare repeated requests without treating the advertised limit as a bill.
Read guide →Context window exceeded: a practical diagnostic checklist
Diagnose context_window_exceeded errors, distinguish oversized input from output stopping and rate limits, and recover with a smaller, testable request.
Read guide →Claude Code context limits: compaction, custom models, and task budgets
Understand what happens at Claude Code context limits, inspect compaction settings, and use CLAUDE_CODE_MAX_CONTEXT_TOKENS without confusing client and server capacity.
Read guide →Ollama API key: identify the destination before adding a secret
Find out when Ollama needs an API key, distinguish local and cloud requests, troubleshoot authentication, and keep credentials out of client code.
Read guide →Ollama WebUI: connect the interface, then verify the model path
Understand the Open WebUI–Ollama connection, Docker localhost errors, model context overrides, authentication boundaries and a practical cost test.
Read guide →OpenCode with Ollama: verify one coding task before scaling up
Connect OpenCode to Ollama using the documented launch workflow, verify local versus cloud models, protect your repository and measure completed-task cost.
Read guide →Ollama update: change one layer and verify the workload
Update Ollama with a platform-aware checklist, distinguish runtime and model changes, preserve configuration and verify a representative task afterward.
Read guide →Ollama with Codex CLI: change the model, keep the acceptance bar
Use the documented Ollama–Codex CLI integration, distinguish the coding client from its model, check web access and compare cost per verified task.
Read guide →OpenClaw with Ollama: plan the gateway, tools and recurring cost
Understand the Ollama–OpenClaw launch workflow, its gateway side effects, native API connection, local versus cloud routing and recurring agent cost.
Read guide →Is Ollama free? The local software and the complete workload differ
Separate free local Ollama software from cloud usage, hardware, electricity and maintenance, with an original break-even worksheet and cost examples.
Read guide →Ollama on Windows: install one runtime and verify one useful task
Plan a native Windows Ollama installation, separate storage from memory requirements, verify a first local model and diagnose common setup problems.
Read guide →Tokens in AI: the unit behind context and usage, not a word count
Understand AI tokens without confusing them with words, requests or credits. Work through input, output, cache, context and per-million pricing examples.
Read guide →Start with your workload
For Ollama Cloud monthly plans, use the cash calculator. Compare the same consumption across plans before deciding. Included allowance is not cash you can withdraw, and model consumption is not always the amount you pay.