Can you explain the differences between managing LLM token budgets in OpenAI versus Anthropic when running small business automation tools as a retiree consulting part time
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Can you explain the differences between managing LLM token budgets in OpenAI versus Anthropic when running small business automation tools as a retiree consulting part time
5 real searches · 1 real-search pass
OpenAI API pricing input output cached tokens context window official documentation 2026Google ↗
OBSERVEDOther / navigational
Anthropic API pricing input output cache read write tokens context window official documentation 2026Google ↗
OBSERVEDOther / navigational
OpenAI API conversation state compaction prompt caching documentationGoogle ↗
OBSERVEDReason
OpenAI API documentation token usage input output cached input tokens context window max output tokens officialGoogle ↗
OBSERVEDOther / navigational
Anthropic API documentation token counting input output cache creation cache read tokens context window max output officialGoogle ↗
OBSERVEDInstruction
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (5)
Classes come from the query-classifier (a local Laya model). 5 of 5 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT5 real searches · gpt-6
OpenAI API pricing input output cached tokens context window official documentation 2026 Google ↗
Anthropic API pricing input output cache read write tokens context window official documentation 2026 Google ↗
OpenAI API conversation state compaction prompt caching documentation Google ↗
OpenAI API documentation token usage input output cached input tokens context window max output tokens official Google ↗
Anthropic API documentation token counting input output cache creation cache read tokens context window max output official Google ↗
- Counting tokens · developers.openai.com
- Understanding and counting tokens · help.openai.com
- Token counting · platform.claude.com
- Reasoning models · developers.openai.com
- Prompt caching · developers.openai.com
- Prompt caching · developers.openai.com
- Prompt caching · platform.claude.com
- Anthropic prompt caching · platform.claude.com
Queries
5 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
OpenAI API pricing input output cached tokens context window official documentation 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Anthropic API pricing input output cache read write tokens context window official documentation 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
OpenAI API conversation state compaction prompt caching documentation OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
OpenAI API documentation token usage input output cached input tokens context window max output tokens official OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Anthropic API documentation token counting input output cache creation cache read tokens context window max output official OBSERVED | Google ↗ AI Mode ↗ | — | Instruction | — | — | 1x of 1 |