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Real 2026 prices with worked per-call math: GPT-5 flagship is $1.25/$10 per 1M — half GPT-4o's input at the same output, with 3× the context. GPT-5 mini and nano compared, and where the money actually goes.

We priced Cerebras, E2B, Browserbase and LiveKit against one realistic 10-minute agent call. LLM tokens came to 0.89% of the bill; proxy bandwidth came to 74%. Two config habits separate $485 per 1,000 calls from $3,026.

We calculated the cost of 13 AI models across 20 production workloads: customer support, RAG chatbots, content moderation, code review, legal extraction, and more. Gemini Flash-8B wins all 20 on price — 4× cheaper than GPT-4o mini, 145× cheaper than Claude Opus 4.8 for content moderation at 1M calls/month.

Advertised: ~$3,100. Real year-1 bill: $6,170. We modelled a 500-user SaaS and added every hidden fee — Stripe Radar, Billing add-on, Twilio A2P 10DLC registration, Pinecone storage at scale. The combined stack costs 2× what the pricing pages suggest.

Caching changes the ranking. Claude charges a write fee but gives 90% off reads. GPT-4o caches automatically with 50% off. Gemini's context cache costs per hour stored. For a 10k-token system prompt at 500 req/day, Claude Sonnet becomes cheapest after caching.

Stripe went from 2.9% to 3.1%. Google Maps doubled some routes. AWS started charging for public IPv4 that used to be free. A running log of provider price increases with old vs new numbers and bill impact.

Real token math for 100k AI support chats/month. Gemini Flash: $432. GPT-4o: $10,125. The 23× difference, how conversation history grows your bill, and three levers to cut costs without changing models.

We ran the cost for 20 production workloads — email classification, code review, RAG, legal extraction and more — at 1,000 req/day. The cheapest model is 97% less than frontier for identical classification tasks. Full tables.

We tracked every major LLM price event since GPT-4's $30 launch: frontier-class input is down 97% in three years, both discontinuous shocks came from DeepSeek, and output prices quietly deflate slower than input. What the ~10×/year curve does to annual contracts, unit economics and build-vs-wait calls.

Every API call re-sends the full conversation history as input. By turn 30, you're paying to process 11,300 tokens instead of 1,150. A 30-turn conversation totals over $1 — 4× what it would cost stateless. The math behind the accumulation and four ways to manage it.

The per-call rate you compare between vendors is usually under a fifth of the real cost. We added up developer build time, monthly maintenance and usage for a typical integration — and the "cheaper" API on paper is often the pricier one in your ledger. Where volume flips the story, and how to actually compare two APIs.

A free tier isn't a plan, it's a runway. At 20% monthly growth, jumping from 40% to 80% utilisation doesn't halve your runway — it cuts it four-fold. We ran the logarithmic math on real 2026 free tiers (Gemini, Resend, Supabase, Cloudflare) and the reset-vs-hard-stop trap that breaks apps in production.

Same workload, every major model: $450 on Grok 4.1 Fast versus $17,500 on Claude Opus 4.6 — a 39× spread. xAI took the cheap end of the frontier in 2026, OpenAI and Google split into budget and premium tiers, and Claude stayed top of the ladder. The real per-million numbers.

Your tier allows 500 requests a minute, so why the 429s at eight? The tokens-per-minute limit binds first — at 4,500 tokens a request, OpenAI's entry tier caps you under 7 RPM, about three concurrent users. The real math on every tier, and the four levers that fix it.

We size a real RAG workload — 500k vectors, 1536 dimensions, 1M queries/month — and the bill lands in single-to-low-double-digit dollars on every provider. The storage layer is the cheap part of RAG; here's the math and which model to pick.

Plivo wins on platform rate, but the US carrier pass-through fee adds ~$300 the same for everyone — and emoji-laden templates quietly bill as 2–3 segments. The all-in math on 100k messages, and when to skip SMS entirely.

Reusing the same system prompt or RAG context? You're paying full price to re-read it. Caching cuts input cost 50–90% — with the 2026 discounts for OpenAI, Anthropic and Gemini, plus the write-premium gotcha that can make your bill go up.

Free tiers compared on calls/min and data freshness, where paid plans start, and the per-asset-class billing quirk that turns Polygon's $29 into $58. Which to pick for dashboards, live quotes or tick data.

A worked breakdown on $10,000/month: why the spread is $3,000/yr, why small orders pay nearly double, and when a Merchant of Record's higher fee is actually the cheaper choice.

The headline price is rarely what you pay. SMS carrier fees, email IPs, maps SKUs, payout charges and AI output tokens — the line items that add 30–50% after launch, with real numbers.

Same workload — 1M requests, 1,000 in / 500 out tokens — priced on every major model. The gap between cheapest and priciest is 35×.

A numbers-first comparison of OpenAI, Anthropic and Google API pricing — and the 175× spread between cheapest and priciest for the same workload.

Genuinely useful free API tiers across AI, email, maps, crypto data and search — and how far each really gets you.

Payment API fees compared — and when a merchant-of-record like Paddle is worth the higher cut.

Why the carrier fee, not the platform, often decides your SMS bill.

SendGrid vs Resend vs Amazon SES vs Postmark — pricing, free tiers and which is cheapest at your volume.

Pricing, models, strengths — and which to pick for your use case.