Routing

LiteLLM for tokenmaxxing

The most direct tokenmaxxing fit: route calls, track spend, enforce budgets, and stop pretending every prompt deserves the priciest model.

47.8K starsBerriAI/litellm
8.2K forksGitHub metadata checked 2026-05-21
Source-availableDirect tokenmaxxing fit

What it does

An OpenAI-compatible gateway and SDK for calling many model providers with budgets, logging, load balancing, guardrails, and cost tracking.

Why it belongs here

The most direct tokenmaxxing fit: route calls, track spend, enforce budgets, and stop pretending every prompt deserves the priciest model.

Best use case

Teams that want one gateway for provider abstraction, model routing, usage logging, budgets, fallbacks, and cost-aware defaults.

How to use it

Put it between the app and model providers, tag requests by workflow, set spend limits, and route low-risk tasks to cheaper models after evals pass.

Limits

A gateway will not fix vague prompts or poor review loops by itself. Budget rules need ownership and ongoing tuning.

Tags

gatewaycost-trackingrouting
Related feed

Source notes connected to this use case

Startup Fortune source artwork
newsSF
news

Hermes Agent leads OpenRouter as agent usage becomes a market signal – Startup Fortune

OpenRouter's public app/agent leaderboard briefly put Hermes Agent at #1, illustrating how token-based usage dashboards can steer attention in the agent boom.

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Read note
TrueFoundry tokenmaxxing article image
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long-form

Tokenmaxxing as the new lines-of-code metric

Fresh AI infra angle on why token volume becomes dangerous when teams optimize for consumption instead of attributable outcomes.

cost-governancemodel-routingllm-infra
Read note
Generated Tokenmaxxing editorial thumbnail for Anthropic raises Claude Code limits with new compute
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agentmedium review

Anthropic raises Claude Code limits with new compute

Anthropic ties higher Claude Code and API limits to new compute capacity, making capacity itself part of the agent-product story.

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Read note
Augment Code source artwork
newsAC
news

Introducing Augment Prism: model routing to reduce cost and maintain quality

Augment Code introduces Prism, a cache-aware model router for coding-agent sessions that chooses an underlying model per user turn to reduce token spend without materially degrading output quality (per Augment’s benchmarks).

tokenmaxxingcost-governancemodel-routing
Read note
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