How to reduce LLM API costs without making your product worse
Five ways to cut your OpenAI/LLM API bill: right-size models per task, cache, trim context, measure per feature, and re-shop as prices move.
Fresh AI news, model performance deep-dives, and the real cost of AI model APIs.
Five ways to cut your OpenAI/LLM API bill: right-size models per task, cache, trim context, measure per feature, and re-shop as prices move.
Nobody searches "LiteLLM alternatives" because LiteLLM is bad — it's the category standard. They search it because self-hosting a proxy is ops they didn't sign up for, or the March 2026 supply-chain scare spooked them, or they're tired of maintaining model IDs. Here's the honest 2026 field — hosted gateways, observability platforms, the new edge entrants, TierUp — mapped to each trigger, sources and our own bias disclosed.
Gateway, proxy, and router get used interchangeably in LLM infra threads, and it makes tool comparisons a mess. They aren't synonyms — they describe three different axes. Here's the plain-English distinction, why one product is usually all three at once, and how to tell which one you actually need.
People don't search "OpenRouter alternatives" at random — there's a trigger. The 5.5% credit fee, provider quality variance, wanting self-hosting, or wanting to stop managing model IDs. Here's the honest 2026 field — LiteLLM, Requesty, Portkey, Helicone, TierUp — mapped to each reason, sources and our own bias disclosed.
Every "best LLM router" roundup is written by a vendor, including this one. Here's the 2026 field — OpenRouter, LiteLLM, Portkey, Helicone, Requesty, NotDiamond, TierUp — sorted by the question that actually splits them, with sources and our own bias disclosed.
The cheapest AI API on paper is not the cheapest in your invoice. Here's the July 2026 price floor, a worked example with real per-token math, and the three discounts most teams never claim.

Three charts of the July 2026 LLM price sheet — the 400x input spread on a log scale, the 4–6x output tax, and what a month actually costs at your request volume.

The gap between the cheapest and most expensive LLM APIs is now roughly 400x on input and 600x on output — here's the July 2026 landscape and how to think about it.

What SWE-bench Pro, Terminal-Bench 2.1, and GPQA Diamond actually measure, where they break down, and why single-number rankings mislead.

GPT-5.6 launched to a small government-coordinated preview group, and Anthropic's newest Claude models spent 19 days suspended under a US directive — day-one access to frontier models is no longer a given.

Anthropic's mid-tier Sonnet 5 outscores the flagship Opus 4.8 on Terminal-Bench 2.1 — what it means when the cheaper default beats the expensive one.

Reports of large orgs canceling token-billed AI coding tools show what happens when per-seat budgets meet per-token reality — and what finance teams are doing about it.

Per-token prices have collapsed, yet enterprise AI spend keeps climbing — agents, RAG, and always-on workloads are multiplying volume faster than prices drop. Here's the math and a mitigation checklist.

The 2026 evidence is in — routing work across price tiers beats hardcoding any single model, whether your fixation is the cheapest token or the best benchmark score.

Google's Deep Think mode posts an 82.4% GPQA Diamond — what the reasoning-benchmark race tells you, and what it conveniently leaves out.

OpenAI's GPT-5.6 preview splits the flagship into three named tiers — here's what Sol, Terra, and Luna mean for how you pick models.

OpenAI and Broadcom unveiled the Jalapeño inference chip on June 24 — here's the custom-silicon race in context, and whether any of it will show up as cheaper API prices.

The Transformer co-author is leaving Google for OpenAI — what the frontier talent market signals, and why architecture work is the quiet driver of API price/performance.

Zhipu AI's MIT-licensed GLM-5.2 posts frontier-adjacent coding scores at a fraction of frontier prices — here's what's verified, what's vendor-reported, and what it means for your API bill.

Claude Opus 4.7 kept its per-token price and still made many workloads 12-27% more expensive — a case study in the hidden multipliers that move your bill more than the rate card does.

Alphabet raised $84.75 billion in equity for AI infrastructure — here's what capital raises at this scale signal about compute costs and where API pricing goes next.

What we'll be writing about — fresh AI news, model performance deep-dives, and the real cost of AI model APIs.