A map of what AI tokens actually cost, and where they're wasted vs. well spent.
"I feel nervous when I have subscription left over. That just means I haven't maximized my token throughput."
Andrej Karpathy, No Priors (2026) As of 2026-07: 197 entries across five areas, 8 practices, 10 concepts, 8 claims, and 7 copy-paste setups.
Topics: Caching · Compression · Context engineering · Memory · Routing · Multi-agent systems · Gateways · Observability · Benchmarks · Cache accounting · Budgets · Pricing models · Energy
A hybrid by design: a curated awesome list at the core, plus a field-guide layer on top (practices, concepts, claims) that carries an editorial point of view.
Where to startLegendMonitorOptimizeGovernUnderstandMeasurePracticesConceptsClaimsSetups and skills
Just want the numbers: the five area sections below hold every entry. Want the method: read the practices first, then the concepts behind them. Building something: setups and skills holds runnable configurations.
Each entry ends with a kind badge: (blue, with the license when known), or a gray badge for , , , for companies, and . Plain entries are articles. GitHub-hosted tools also carry live star and last-commit badges.
ccusage- An open-source CLI that reads local agent logs to report token usage and cost across 15 coding-agent sources, with caching-aware pricing.Claude Code Usage Monitor- A live terminal dashboard for Claude Code usage, with burn-rate analytics, P90 limit detection, and session-expiry forecasts.claude-usage- A local dashboard for Claude Code token usage, costs, and session history; Pro and Max subscribers get a quota progress bar.ClaudeBar- A macOS menu-bar app that monitors AI coding quotas across 11 providers; the README declares MIT but ships no license file, so the OSS grant is unconfirmed.CodeBurn- An open-source tracker for 36 coding tools whose optimize command flags named harness-waste patterns with dollar estimates it later checks against actuals.Codex Usage Tracker- A local-first dashboard, CLI, and MCP tools indexing Codex CLI logs into SQLite to show where tokens, credits, and cost go, including cache ratios.CodexBar- A free, open-source macOS menu-bar app that shows limits and reset timers at a glance across dozens of AI providers, plus credit balances and spending when…CodeZeno Usage Monitor- A Windows-taskbar widget showing real-time Claude Code quota and usage at a glance, without opening a terminal.Datadog LLM Observability - Cost- Datadog's LLM Observability estimates per-request cost across 800+ models from token counts and public pricing; invoice reconciliation is a separate product.gh-aw (GitHub Agentic Workflows)- GitHub's agentic-workflows runtime with first-party per-run token and cost metering, plus budget caps that stop a workflow mid-run.Grafana Cloud GenAI Observability- Grafana Cloud's GenAI Observability ships a prebuilt dashboard for LLM cost, token usage, and latency, built on top of the OpenLIT SDK.OpenLIT- An open-source (Apache-2.0), OpenTelemetry-native platform with a self-hosted dashboard for LLM cost, token, and latency observability.OpenUsage- A native Swift macOS menu-bar meter for 10 AI coding subscriptions, showing session and weekly limits, credits, and estimated spend from local credentials.TokenTracker- A local-first token and cost dashboard for 27 coding tools, with a desktop pet, native widgets, and achievements as a distinct gamified take on usage metering.
AgentSight- Uses eBPF to watch an AI agent from the kernel boundary, correlating what it said it would do against what it did, at under 3% overhead.OpenTelemetry eBPF Instrumentation (OBI) - GenAI / MCP- OBI is OpenTelemetry's zero-code eBPF instrumentation (formerly Grafana Beyla) that captures GenAI and MCP traces at the kernel layer with no SDK.
Langfuse- An open-source platform for tracing, evaluating, and analyzing LLM and agent transcripts, with a prompt-management layer on top.
OpenLLMetry- An open-source set of OpenTelemetry-based SDKs and instrumentations, built by Traceloop, for LLM apps.OpenTelemetry GenAI Semantic Conventions- OpenTelemetry's GenAI Semantic Conventions define the vendor-neutral token, cost, and cache attribute names that OpenLLMetry and Phoenix both converge onto.
Arize Phoenix- A source-available (Elastic License 2.0) LLM tracing platform recording per-span token counts and USD cost via OpenTelemetry.claude-tap- A local trace viewer intercepting API traffic from 14+ coding agents, showing per-request token breakdowns: input, output, cache read, cache creation.LangSmith - Cost Tracking- LangSmith is LangChain's commercial LLM/agent observability SaaS.Opik- Comet's open-source (Apache-2.0) LLM observability platform, with per-span USD cost estimated from token usage.
GPTCache- An open-source semantic cache returning a stored LLM response for a paraphrased repeat query via vector search, skipping the paid call.khazad- A transport-layer semantic cache for LLM APIs on Redis 8 Vector Sets: it intercepts HTTP traffic with zero application code changes and replays cached responses…LMCache - KV-cache reuse layer with token-level cache-hit accounting (self-host)- LMCache is a self-hosted KV-cache layer beneath vLLM, giving token-level cache-hit observability for teams who own their GPUs, not a hosted bill.prompt-cache- A Go LLM proxy that adds a three-tier semantic cache: high similarity hits directly, low skips, and a gray zone runs a cheap verification model to guard against…Redis LangCache- Redis's fully-managed semantic cache: a REST API that returns a stored response when a new query is similar to a past one, so paraphrases skip the paid LLM…
llama.cpp- The foundational open-source (MIT) local LLM inference engine most of the local ecosystem runs on, with an OpenAI-compatible server built in.Ollama- A runtime for running open-weight models like Qwen, DeepSeek, and GLM-5.1 locally, shifting inference onto hardware you already own.
Context Mode - MCP server that sandboxes tool output out of the context window- This MCP server sandboxes tool calls and returns only the distilled result, claiming a 98% cut: 315 KB of output down to 5.4 KB.headroom - context compression for LLM and agent pipelines (quality story dissected)- An Apache-2.0 context-compression tool for LLM/agent pipelines, the category's largest repo, confirmed organic by star-forensics.LLMLingua- Microsoft's prompt-compression library that uses a small model to drop low-information tokens before a prompt reaches the target LLM.llmtrim- A local proxy that compresses a coding agent's prompt, tool schemas, and history before forwarding, and can reroute Claude calls to Grok.Minification of state-in-context agents - the clean waste-vs-capability datapoint- This ICPC 2026 study found that minifying code in a coding agent's context cuts input tokens by 42% but costs 12 percentage points of accuracy.rtk - CLI proxy that compresses dev-command output (reduction-only headline)- rtk is a single-binary Rust CLI proxy that intercepts and compresses the output of common dev commands before it reaches an LLM coding agent's context window.TOON (Token-Oriented Object Notation)- TOON is a compact, human-readable, lossless serialization of the JSON data model, designed for LLM input.
AgentDiet - trajectory reduction ("Reducing Cost of LLM Agents with Trajectory Reduction")- AgentDiet is an inference-time module that strips useless, redundant, and expired information from an agent's trajectory, without hurting performance.Anthropic vendor-native context management (context editing + memory tool + server-side compaction)- Anthropic's context editing, memory tool, and server-side compaction cut token consumption by a vendor-reported 84% in a 100-turn web-search evaluation.Claude Code compaction engine - the three-tier mechanism and its cache/correctness failure modes- Claude Code'sharness- not the API - decides how to trim a filling context window, and it does this through a three-tier compaction engine.Codex CLI compaction cost - over-eager compaction as a token-amplification loop- Upgrading Codex CLI from v0.116 to v0.118 made context compaction fire twice as often, doubling or tripling token consumption for identical tasks.Context Rot - LLM performance degrades as input length grows- This is Chroma's controlled study of how LLM output quality changes as input length grows, holding task difficulty fixed.ContextBudget - context management as a budget-constrained sequential decision- ContextBudget's BACM method has an agent decide when and how much to compress its history based on remaining context budget, not a fixed rule.Cursor vendor-native context management - dynamic context discovery + Composer self-summarization- Cursor's dynamic context discovery loads tool schemas and large outputs on demand instead of eagerly, a change the vendor reports cut context usage by 46.9%.Repomix- Packs an entire repository into a single AI-friendly file, reporting token counts and using Tree-sitter to compress code to signatures only.RULER - the "real context size" long-context benchmark- NVIDIA's RULER benchmark found that of models claiming 32K+ token context windows, only half actually maintain quality once you fill them to 32K.Self-Compacting Language Model Agents- This paper introduces SELFCOMPACT: instead of fixed-interval summarization, the model itself decides when and how to compress a growing agent trace.Serena- An open-source (MIT) MCP toolkit that gives a coding agent IDE-grade semantic code retrieval and editing: 'the IDE for your coding agent'.
Claude Code spend-governance bundle (v2.1.216-219) - caps tightened, fan-out default loosened- Claude Code's v2.1.216-219 bundle (2026-07-20 to 07-24) hardens spend controls - a concurrent-subagent cap and enforced --max-budget-usd - while simultaneously…Harness-side runaway-loop cost guardrails (Claude Code + Codex, July 2026)- In mid-July 2026 Claude Code and Codex both shipped first-party guardrails against runaway agent loops within days of each other.
Bifrost (Maxim AI)- Bifrost is a Go-based AI gateway fronting 1000+ models that measured just 11 microseconds of added latency per request at 5,000 requests per second.Cloudflare AI Gateway (Spend Limits)- Cloudflare AI Gateway is an edge-native LLM proxy that added dollar-denominated spend limits in June 2026, blocking or rerouting requests once a budget is hit.Helicone- An open-source (Apache-2.0) LLM proxy that logs every request's cost, latency, and tokens in one line of code; Mintlify acquired it in March 2026.Kong AI Gateway- The AI layer of Kong's API-gateway platform: a proxy that meters LLM/agent/MCP traffic for billing, showback, and chargeback.LiteLLM- An open-source gateway fronting 100+ LLM APIs that computes real per-request dollar cost from a live pricing map, with spend limits.OpenRouter- A unified API gateway fronting 400+ models across 70+ providers that auto-routes each request by price, with fallback on outages.Portkey AI Gateway- Routes LLM traffic across providers and enforces hard USD budget limits on virtual keys, auto-expiring a key once its cap is hit.
claude-code-memory-setup- A practitioner recipe pairing an Obsidian memory vault with a local AST code-graph tool; the author self-reports up to 71.5x fewer tokens per Claude Code…claude-mem- A coding-agent observational-memory layer that captures every session, compresses it with AI, and re-injects relevant context next time; self-reports ~10x token…Cognee- An open-source (Apache-2.0) AI-memory platform giving agents persistent memory via a self-hosted knowledge graph, via remember/recall/forget.Karpathy's LLM Wiki- Andrej Karpathy's LLM Wiki pattern has an agent build and maintain a persistent markdown wiki from your sources, instead of re-retrieving raw files.LangMem- LangChain's long-term memory library: it extracts and consolidates facts from conversations and integrates natively with LangGraph's memory store, so agents…Letta (MemGPT)- The MemGPT lineage project: a platform for stateful agents that pages an LLM's context like an OS, keeping working memory small and moving the rest to archival…Mem0- An open-source memory layer that extracts salient facts from conversations and retrieves only the relevant ones per call, not the full history.Supermemory- A memory and context engine that self-reports 95% recall on LongMemEval while adding only ~720 tokens of context, a claimed 99.4% context reduction versus full…Zep / Graphiti- A memory platform for agents built on temporal knowledge graphs; it self-reports serving benchmark answers from a few thousand tokens of retrieved context… (also:Graphiti (OSS engine)·zep repo)
Framework orchestration overhead (the manager-LLM tax)- Hierarchical frameworks like CrewAI add a manager-LLM delegation tax, an extra model that plans and validates, though its cost is unquantified in any primary.SupervisorAgent - "Stop Wasting Your Tokens" (runtime supervision)- SupervisorAgent is a lightweight, modular framework for runtime, adaptive supervision of multi-agent systems.
LOOP Skill Engine- LOOP records an agent's first run of a repetitive task with full LLM reasoning, then replays the extracted tool-call template without calling the LLM again.Orchestrator-worker model tiering (frontier plans / cheap executes)- A capable model plans while cheaper agents execute; the pattern now ships as a vendor default, hitting 89.7% of LLM quality at 4% of the cost.token-ninja- Intercepts deterministic commands like git status or npm test before they reach the model, running them locally and skipping the LLM call.
Claude Code v2.1.199 - transient-retry hardening & partial-output preservation- Claude Code v2.1.199 now auto-retries rate-limit errors with backoff and raised the default retry ceiling to 300, up from a prior cap of 15.
Antigravity CLI - per-subagent model-tier routing + /effort (v1.1.5)- Antigravity CLI v1.1.5 shipped first-party per-subagent model-tier routing (a model: flash|pro field in custom-agent frontmatter) plus an /effort control -…Claude Code via a LiteLLM gateway (cheap-tier-in-front setup)- Pointing Claude Code's ANTHROPIC_BASE_URL at a local LiteLLM proxy lets cheaper or non-Anthropic models absorb work the frontier model would otherwise bill for.Cluster, Route, Escalate - cost-aware cascaded serving- This paper proposes a two-stage cost-aware cascade for LLM serving that combines routing and escalation into one framework.Distilling agent behavior into small task-specific models- Distilling a large agent's behavior into a small 0.5-3B model lets most of its work run at a fraction of the frontier model's per-token cost.MTRouter - per-turn cost-aware routing with history-model joint embeddings- MTRouter picks a different model for each turn of a multi-turn conversation, rather than one model per query, to hit a cost budget without losing quality.Not Diamond- Not Diamond's meta-model predicts, per input, which LLM will give the best answer at the lowest cost, then routes the request there.OpenCode - open-source coding-agent CLI with explicit cost-tier routing- OpenCode is an open-source (MIT) coding-agent CLI with its own explicit cost- and model-routing configuration, set directly in config.OrcaRouter - production LinUCB bandit router (hybrid offline-online)- OrcaRouter is a production LLM router built on a LinUCB bandit, with its cost/quality tradeoff independently confirmed on the RouterArena leaderboard.RouteLLM- LMSYS's open-source router sending each query to a cheap or expensive model based on a trained cost threshold, as a drop-in server.ruflo (formerly Claude-Flow; npm- ruflo is an open-source agent meta-harness for Claude Code and Codex, providing swarm orchestration and persistent memory.claude-flow
v3.17.0) - agent meta-harness with cost-adjusted model routingvLLM Semantic Router- Sends routine queries to cheap or local models and hard ones to stronger backends, as an open-source, self-hostable router.
RLM-Cascade - response-level speculative decoding at the gateway- RLM-Cascade, from a PayPal team, has a cheap draft model answer first and an Opus 4.8 verifier accept or rewrite it, at roughly 2% of Opus's cost.SGLang- A high-performance serving framework for large language and multimodal models.vLLM- The canonical open-source LLM serving engine, using PagedAttention to manage KV-cache memory in blocks so more requests batch at lower cost.
Stop When Reasoning Converges- Reasoning models often keep generating steps after a solution has already stabilized, wasting tokens and adding latency - what this paper calls "overthink.".When more reasoning hurts - the test-time-compute ceiling- Two 2026 papers found giving a model more reasoning budget makes it perform worse and cost more; past a point, tool delegation wins outright.
Code execution with MCP (Anthropic)- Anthropic proposes agents call MCP servers by writing and executing code instead of a tool call per step, so unused tool schemas skip the context window.MCP Tool Descriptions Are Smelly!- This study found poorly-written MCP tool descriptions measurably hurt agent efficiency, using an LLM-jury scanner and an A/B protocol on MCP-Universe.Tool Attention Is All You Need- MCP re-sends every tool's full schema on every turn, whether or not the agent needs it - a protocol tax known as the MCP/Tools Tax.
CloudZero- An established commercial cloud and AI cost-intelligence / FinOps platform that brands itself 'The AI ROI Company'.JetBrains AI moves business plans from monthly licenses to 12-month credits- JetBrains is moving business AI from monthly per-seat licenses to 12-month reallocatable credits plus a governance dashboard; personal Pro/Ultimate prices are…Mavvrik (fmr. DigitalEx)- Mavvrik is an AI/hybrid-infrastructure cost governance and FinOps platform, rebranded from DigitalEx in February 2025.Pay-i- An SDK-based GenAI cost-observability platform that tracks token-level spend per call and rolls it up into cost-center allocation across orgs and apps.
Denial-of-Wallet / token-exhaustion attacks- Denial-of-wallet attacks exploit pay-per-token pricing to inflate a bill, via stolen-credential LLMjacking or agents steered into runaway token use.Governance Decay - compaction silently erasing safety/governance constraints- Compacting an agent's context can silently erase governance rules: across 7 model families, violations rose from 0% to 30%, up to 59% for some.
FinOps for AI - canonical practitioner framework for governing AI/LLM spend- FinOps for AI is the FinOps Foundation's official practitioner framework for governing AI, GPU, and token spend.Vaudit - TokenAudit (LLM invoice reconciliation / AI spend audit)- Vaudit is an AI-native, independent spend-auditing and recovery platform (San Francisco, founded late 2023).
Claude Code's 5-hour/weekly usage quotas - Anthropic has stopped publishing exact numbers- Anthropic stopped publishing exact Claude Code usage quotas, describing Max plans only as 5x/20x multipliers of Pro with no absolute numbers.TrueFoundry (AI Gateway - Budget Limiting)- TrueFoundry is an enterprise GenAI deployment/gateway company founded by ex-Meta founders.
CodeCarbon- An open-source (MIT) library for estimating a workload's energy use and CO2e emissions, and ML's widely-cited carbon baseline.EcoLogits - energy/carbon of LLM- Estimates the energy and carbon footprint of calling generative-AI APIs: the hosted counterpart to CodeCarbon, which measures your own hardware.APIcalls (the hosted-usage estimator)Epoch AI - how much energy a query uses (the per-token energy anchor)- Epoch AI built a transparent, first-principles estimate of how much energy one LLM query costs.Google - measuring the environmental impact of AI inference (provider disclosure)- Google published a first-party disclosure of the energy, carbon, and water cost of a median Gemini Apps text prompt, authored by Amin Vahdat and Jeff Dean.ML.ENERGY Leaderboard v3.0 - measured inference energy (the "reasoning ≈ 25× energy" signal)- Version 3.0 of this leaderboard measures real GPU inference energy across 46 models x 7 tasks, finding reasoning models use roughly 25x the energy of others.
ActPlane- An eBPF-based, OS-level policy-enforcement engine for AI-agent harnesses like Claude Code and Codex.AEGIS- An open-source (MIT) pre-execution firewall and cryptographic audit layer for AI agents.MCPGuard-Dynamic- An early-stage, research-grade kernel-level eBPF sandbox for MCP (64★), published under Meta's official GitHub org.
ChatGPT Enterprise - usage analytics & spend controls- OpenAI's first-party spend layer for ChatGPT Enterprise/Business: a Global Admin Console with credit caps, request workflows, and a Cost API.Claude Enterprise - admin analytics & cost controls- Anthropic's first-party spend surface for Claude Enterprise/Team admins: org-level spend caps, model defaults, and per-user cost analytics via the Admin API.PointFive (AI Efficiency OS / TokenShift)- PointFive's TokenShift governs coding-agent token spend across Claude Code, Cursor, Codex, and more, claiming a 10-20% cut across 11 partners.Revenium - runtime AI economic control / spend management- Revenium tracks AI agent spend at runtime to the cent, attributing every model call and tool cost to its workflow, with auto-shutoff on runaway budgets.Vantage- A FinOps platform ingesting native token-level cost data from Anthropic and OpenAI's own usage APIs, plus Cursor and cloud spend.Vercel AI Gateway - per-API-key budgets- Vercel AI Gateway lets you cap spend per API key in dollars (min $1) with a daily/weekly/monthly refresh, rejecting further requests once the cap is hit.
Claude "subscription arbitrage" and its (announced, then d) end- Users route agentic workloads worth far more than a subscription's price through cheap Pro/Max plans; Anthropic tried to close this, then d the fix.Coding-agent native spend controls (2026)- Within six weeks in 2026, Cursor, GitHub Copilot, and OpenAI each shipped native admin spend controls: budget caps, credit metering, usage dashboards. (also:GitHub Copilot·OpenAI)GitHub Copilot metered-billing bill-shock - the demand-side reaction ("tokenpocalypse")- GitHub's move from flat-rate Copilot plans to metered AI Credits exposed agentic workflows' true per-token cost and triggered a mass bill-shock backlash.Lanai- Lanai's AI @ Work platform discovers every sanctioned and shadow AI workflow across an org and maps its token spend to the KPIs it actually drives.State of FinOps 2026 - AI spend management is now the norm- This is the FinOps Foundation's sixth annual State of FinOps survey, the practitioner census of how organizations manage cloud and AI spend.The "$47k Claude Code bill" - the anchor bill-shock anecdote and its mechanistic debunk- A viral $47,000-in-90-days Claude Code bill story was debunked by a teardown pinning the real driver on quadratic context re-ingestion, not runaway use.Uber caps AI-coding spend at $1,500/mo per tool after burning its budget in ~4 months- Uber capped AI-coding spend at $1,500 per employee per tool after burning its entire annual budget in roughly four months of encouraged maximal use.
JetBrains independently measured two token-saving skills against their own claims- JetBrains independently A/B-tested two token-saving skills: rtk ran +7.6% more expensive at low effort (claimed 60-90% cut), Caveman saved ~8.5% (claimed 65%). (also:Caveman A/B post)Token-saving plugins are mostly a stupid idea (Tura benchmark)- A benchmark of token-saving plugins found one actively worse than none: cost up 7.2%, tokens up 13.2%, because it broke an already-cached prompt prefix.
Cisco acquires Galileo (LLM eval/observability) → folded into Splunk Observability- Cisco acquired Galileo, an LLM/agent evaluation and observability platform, folding it into Splunk Observability Cloud's AI Agent Monitoring.Tokenomics Foundation (Linux Foundation + FinOps Foundation)- The Linux Foundation is launching the Tokenomics Foundation to build open standards for AI token spend, extending FOCUS to cover token-based costs.
Aider - an OSS coding CLI that meters its own dollar cost- An open-source terminal coding agent (Apache-2.0, ~48k★) with built-in per-message dollar-cost tracking and a public polyglot leaderboard that publishes…Amp (Sourcegraph) - pay-as-you-go, no-markup pricing + mode-based routing- Amp, Sourcegraph's coding agent, passes through LLM cost with zero markup for individuals and teams, with a cost/capability mode: Deep, Smart, or Rush.Cline - an OSS coding agent on a bring-your-own-key cost model- An open-source AI coding agent (Apache-2.0, ~65k★, ~4.8M VS Code installs), built on a bring-your-own-API-key cost model with per-task token and dollar…Factory (droids) - subscription pricing + $150M Series C at $1.5B- Factory prices its Droids agents as flat subscription tiers ($20/$100/$200/mo) with usage-based rate limits, not per-token metering, after a $150M round.Gemini CLI retirement → Antigravity CLI (open-source coding agent closes, pricing restructures)- Google retired the open-source Gemini CLI on 2026-06-18, pushing users onto closed-source Antigravity CLI and $100/$200-per-month paid tiers.OpenHands - MIT OSS coding agent, free local + free cloud tier, at-cost LLM option- An MIT-licensed open-source coding-agent platform with a free local mode, a free cloud tier, and an at-cost LLM pricing option. Gartner - worldwide AI spending forecast: $2.59T in 2026 (+47% YoY)- Gartner's latest forecast puts worldwide AI spending at $2.59 trillion in 2026, up 47% year-over-year, with infrastructure over 45% of the total.Menlo Ventures - enterprise generative-AI spend $11.5B → $37B (2024→2025)- Menlo Ventures found enterprise generative-AI spend hit $37B in 2025, up 3.2x from 2024, with coding tools the largest application category at $7.3B.
"Qwen 3.6 27B is the sweet spot for local development" - Migdał / Quesma (first-party)- Piotr Migdał's #1-on-Hacker-News essay argues Qwen3.6-27B (dense) is the first local model good enough for real coding instead of a metered cloud API.Artificial Analysis - Coding Agent Index (tokens & cost per task, model × harness)- This benchmark scores full model-plus-harness stacks, spanning $0.27 to $11.80 per task: a roughly 44x range at similar quality, per Artificial Analysis.Artificial Analysis - Intelligence Index + Blended Price (intelligence-per-dollar leaderboard)- Artificial Analysis's Intelligence Index plots a 0-100 capability score against blended price per million tokens, live across 85-122 base LLMs.Claude Opus 5 - flat price vs Opus 4.8, but 1M context and thinking on by default- Claude Opus 5 launched 2026-07-24 at the same $5/$25 per MTok as Opus 4.8, but ships 1M context and thinking on by default - so the flat per-token price hides a…Gemini 3.6 Flash - a Flash tier marketed on fewer tokens per task, not just a lower unit price- Gemini 3.6 Flash (2026-07-21) is priced lower than 3.5 Flash at $1.50/$7.50 per MTok AND uses 17% fewer output tokens on the same work - a rare launch where the…Kimi K2.6/K2.7-Code and GLM-5.2 official API pricing- Kimi K2.7-Code ($0.95/$4.00 per million tokens) and GLM-5.2 ($1.40/$4.40) both undercut Claude Sonnet 5 and GPT-5.5 on raw price by 2-5x.Local / open-model economics for coding - state of the field (2026)- Open-weight coding models now score 77-81% on SWE-bench Verified, within a few points of closed frontier models, reshaping self-host-vs-API math.OckBench - measuring token efficiency / verbosity of LLM reasoning- OckBench answers a specific tokenomics question: which model burns the most tokens for the same answer?Reasoning-token billing across providers - the hidden output multiplier- Every major AI provider bills a model's hidden reasoning tokens at the most expensive output rate, without ever returning them to the caller. (also:Google·DeepSeek)Reasoning-token consumption behavior - length ≠ effort, and verbosity is a separate lever- Chain-of-thought can burn about 258 tokens on problems a direct answer solves in 15 (roughly 17x overhead), and simple agentic steps trigger it by accident.
Batch / Priority / Flex service tiers - the scheduling axis of token pricing (clustered, cross-vendor)- Every major LLM vendor sells the same lever, trading latency for price via async batch scheduling, with Anthropic, OpenAI, and Google all near 50% off. (also:OpenAI·Google)Bessemer - the AI pricing & monetization playbook (seat → usage → outcome)- Bessemer's playbook argues AI pricing is shifting from per-seat to consumption/outcome-based, citing Intercom's $0.99-per-resolved-ticket model.Cached-input discounts - the ~90%-off lever behind cache-accounting- Cache-read pricing discounts input tokens by about 90%: the biggest lever on an agentic bill, since input is roughly 85% of session cost.ChatGPT subscription tiers and Codex CLI bundling/pricing (2026)- OpenAI bundles Codex CLI into every ChatGPT tier from Free through the new $100/mo Pro plan, differing only by rate-limit multiplier.ChatGPT workspace-agent credit billing (effective July 6, 2026)- OpenAI ended the free preview for agent runs invoked inside ChatGPT Business, Enterprise, Edu, and Teachers on 2026-07-06.Cursor charges by tokens, split into first-party and third-party pools- Cursor meters by tokens per million (input/output/cache-write/cache-read), split into a first-party pool and a third-party API pool, with a $0.25/M Teams… (also:Teams pricing blog)Devin's Agent Compute Unit has no published definition of what it meters- Devin bills Enterprise usage in Agent Compute Units, but no official doc defines what an ACU measures (not tokens, seconds, or calls); the opacity itself is the…Fable 5 leaves subscription inclusion - frontier tier moves to usage-credit metering (July 7 cliff)- Fable 5's subscription saga settled 2026-07-20 (after two extensions) as a primary-confirmed two-tier split: Max & Team Premium keep it included (50% of weekly…Google AI Pro price and Gemini/Antigravity free-tier limits (2026)- Google AI Pro is confirmed at $19.99/month, beneath the $99.99 and $199.99 AI Ultra tiers giving higher rate limits on the Gemini API and Antigravity.GPT-5.6 family (Sol / Terra / Luna) - API pricing- OpenAI's GPT-5.6 family prices three tiers 2x apart: Sol at $5/$30 per million tokens, Terra at $2.50/$15, and Luna at $1/$6.LiteLLM flex/priority service-tier cost keys - the harness-level tier-routing lever- LiteLLM automatically prices requests made at a non-standard tier like flex or priority, applying the right discounted or premium rate automatically.LLM price decline + Jevons paradox - unit price crashes, total spend climbs- Per-token prices are falling roughly an order of magnitude per year, while total AI spend rises even faster.LLM token pricing dimensions - the structure of a token bill- This maps out how frontier LLM APIs meter and price tokens, read straight off the two largest providers' pricing pages, Anthropic and OpenAI.OpenAI is winding down the self-serve fine-tuning API and platform- OpenAI is winding down self-serve fine-tuning because prompting got cheaper and more capable than fine-tuning for most uses, cutting off customers by 2027.Tokenization multiplicity & overcharging - the pay-per-token integrity problem- Two academic papers show the same output can be billed a different token count depending on tokenization, and providers can be incentivized to inflate it.Windsurf became Devin Desktop and switched credits to token-based quota- Windsurf became Devin Desktop and in March 2026 swapped opaque per-model credit multipliers for token-based quota where free models cost nothing; a…
Reserved-capacity reliability economics (Azure PTU · AWS Bedrock MU)- Azure's Provisioned Throughput Units and AWS Bedrock's Model Units both let buyers reserve guaranteed capacity, billed hourly whether or not it's used.
Cloud Capital - gross margin in the age of AI (the vendor/supply side)- AI-native software runs at roughly 50-60% gross margin versus 70-80% for SaaS, since inference and compute became a large, variable cost of goods sold.Cost-of-Pass - an economic framework for evaluating language models- Cost-of-Pass defines the expected dollar cost of one correct answer as inference cost divided by success rate, pricing benchmark accuracy directly.DORA 2025 - AI as amplifier, and the delivery-stability tension- Google's DORA program found that as AI adoption becomes universal, delivery throughput rises but so does instability: AI as an amplifier, not a pure win.Faros - "The Acceleration Whiplash" (AI Engineering Report 2026)- The "velocity has a hidden bill" study: telemetry from 22,000 developers across 4,000 teams over two years.getDX - AI coding assistant pricing & ROI guide (2026)- Typical AI coding tools cost $200-600 per engineer monthly in seat plus token spend, per getDX, for a median 7.76% PR gain: below vendors' claimed 3-10x.METR - measured vs perceived AI productivity (the RCT)- METR's controlled trial found developers took 19% longer to finish issues when allowed to use AI, while still believing it had sped them up by 20%. Claw-SWE-Bench- Found that adapter/harness design alone swings an agent's Pass@1 score by about 54 percentage points on the identical model backbone.Coding Benchmarks Are Misaligned with Agentic SE (Tessl)- A position paper from Tessl (London, UK) argues that today's coding benchmarks don't measure what people think they measure.Deterministic Anchoring - how much static structure do code agents need?- This ISSTA 2026 paper found injecting static-analysis facts as plain-text comments raises a code agent's Pass@1 by 3.4pp and cuts trajectories by 1.6 rounds.GitHub Copilot agentic-harness efficiency evaluation (first-party offline ablation)- GitHub's own benchmark plots Copilot's agentic-harness resolution rate against dollar-cost-per-task across five benchmarks and four frontier models.Harness-Bench- Holds the task, model, and budget fixed while varying only the agent harness, across 5,194 trajectories spanning 6 harnesses and 8 models.LoCoMo- Snap Research's very-long-term conversational-memory benchmark; the canonical dataset that Mem0, Zep, and Supermemory all cite, kept as a background instrument…LongMemEval- The peer-reviewed (ICLR 2025) benchmark for long-term memory in chat assistants; the standard eval that mem0, Zep, and Supermemory all self-report their…MemoryBench- A pluggable harness to run memory systems (Supermemory, Mem0, Zep) head-to-head across datasets like LoCoMo; useful for standardizing comparison, but built by…Prompt Compression in the Wild - the end-to-end referee for compression- This ECIR 2026 study found LLMLingua's compression yields up to 18% speed-up only in a narrow window; outside it, the compression step cancels the gains.promptfoo- An open-source CLI/CI harness for testing LLM prompts and agents that records per-eval token usage and cost as an assertable metric.RedundancyBench - can anyone even- RedundancyBench is a benchmark for step-level redundancy detection in agent trajectories - can a model even spot the wasted step in an agent's history?detecta redundant step?RouterArena - the open benchmark + live leaderboard for LLM routers- RouterArena is an open evaluation platform and live leaderboard for LLM routers - systems that auto-select a model per query.SWE-bench - the root benchmark the cost-aware derivatives build on- The canonical accuracy-only software-engineering benchmark (2,294 real GitHub issue tasks, 12 Python repos, ICLR 2024) that every cost-aware derivative in this…SWE-Effi - cost-aware re-ranking of SWE-agents under resource budgets- SWE-Effi re-ranks popular AI issue-resolution systems on a SWE-bench subset by cost-under-resource-constraints instead of by accuracy alone.Terminal-Bench- The canonical benchmark for AI agents in real terminal/CLI environments, with 89 tasks each vetted through ~3 reviewer-hours.
Gemini context caching - the per-hour storage meter (the third-vendor axis)- Among major providers, only Gemini bills a per-hour storage meter for explicit prompt caching, making a cache a rented line item that accrues cost while it sits…OpenAI prompt-caching- This is the measurement substrate for prompt-cache savings on the OpenAI API.cached_tokens
accountingOpenAI Responses conversation state - you pay for the whole chain every turn (and the compaction levers)- This entry covers the billing semantics of stateful conversations on OpenAI's Responses API, plus the two server-side compaction levers that mitigate them.
Anthropic bill anatomy - the whole-bill line-item taxonomy- This is the canonical enumeration of every meter on a Claude API bill, read live from Anthropic's pricing page.TensorZero - cross-vendor token-count divergence ("stop comparing $/M tokens")- The same input can produce 2.65x more tokens on one tokenizer than another's: Claude Opus 4-7 runs 1.57x-2.65x more tokens than GPT-5.4 on the same content.Vision-token pricing formulas across the big three- Anthropic, OpenAI, and Google each convert an image into billed tokens with a different formula, so no single cross-vendor image-cost number exists. (also:OpenAI·Google)
Claude Code system prompts (Piebald extraction)- Piebald AI extracts Claude Code's full compiled prompt payload per release: 515 prompt strings and 27 tool descriptions at v2.1.212, each priced in tokens.Claude Code vs OpenCode token overhead (Systima study)- Systima measured harness scaffolding overhead before a prompt is even read: Claude Code carries about 32,800 tokens versus OpenCode's 6,900, a 4.7x gap.
Cross-vendor coding-agent usage trackers (AgentsView · caut)- AgentsView and caut are open-source tools that read local session logs to aggregate token usage and cost across roughly 20 coding-agent vendors.How Do AI Agents Spend Your Money?- This Stanford study is the first systematic look at token spend in agentic coding, running 8 frontier models on 500 SWE-bench Verified tasks.tokview- A local, zero-config proxy showing a coding agent's token spend by session, model, and tool call, flagging re-sent results that multiply the bill.
Early Diagnosis of Wasted Computation in Multi-Agent LLM Systems (Failure-Aware Observability)- This live waste-detection framework for multi-agent systems found that 58.1% of tokens in failed runs are spent after its first warning fires.Faros AI - "Token Intelligence" / Token Attribution Ledger- Faros AI is an enterprise engineering-intelligence SaaS (DORA/SPACE-style productivity analytics).token-optimizer (alexgreensh) - per-session $ waste-detection plugin, semi-cross-vendor- token-optimizer is a coding-agent plugin that runs eleven heuristic waste detectors per session and prices the flagged tokens in dollars.
FOCUS 1.4 - the cross-vendor billing-data normalization standard (now with invoice reconciliation)- FOCUS 1.4, the Linux Foundation's billing-data schema, added Invoice Detail and Billing Period datasets to reconcile spend against real invoices.
Tool-agnostic, evidence-grounded standards for token-efficient agentic coding. Each is one page: TL;DR, claim, evidence, links. Browse the practices.
Short reference notes explaining the ideas behind the practices: cache economics, the harness-waste taxonomy, orchestration economics. Browse the concepts.
Confidence-scored beliefs, clearly labeled as beliefs rather than facts, each with its strongest evidence linked. Read the claims.
Runnable, validated Claude Code and Codex configurations and skills for token-efficient agentic coding, each labeled with how it was validated. Browse the setups.
Text content: CC-BY 4.0 (LICENSE) · Code and configs: MIT (LICENSE-CODE). Maintained by the team at Quesma.