LLM Economics
Token math, model selection, and the true unit cost of every generation.
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LLM EconomicsLatency Now Has a Price Tag: What Faster Inference Is Actually Worth
Anthropic charges exactly double for Fast Mode, which gives you a market price for latency and therefore a ceiling on what any speed optimization is worth to your business.
LLM EconomicsOpen Model Adoption vs Attention: What the Download Data Means for Your Cost Model
Hugging Face's summer 2026 data shows the models the field talks about and the models it actually runs are almost entirely different sets, and your cost model should follow the second one.
LLM EconomicsClaude Opus 5 Pricing: Why the Same $5/$25 Rate Can Still Raise Your Bill
Opus 5 kept Opus 4.8's per-token price, but thinking now runs by default, which raises the output share of a typical request and pushes your real blended rate above the sticker math.
LLM EconomicsWhy Harness Optimization Beats Model Switching for Cutting LLM Costs
Changing the scaffolding around your model cut inference cost by an average of 40% in Writer's own research, which was often a more reliable lever than changing the model itself.
LLM EconomicsWhat 14X Faster Inference Does to Your AI Cost Model
Speed is now a purchasable tier rather than a property of your model, which means latency becomes a line item you choose per endpoint instead of a constraint you inherit.
LLM EconomicsAgent Memory Token Cost: Why Delivery, Not Storage, Decides Your AI Bill
Two agent-memory systems with the same lessons and the same accuracy can differ by nearly 7x in tokens per task, because the cost is set by how much context you send at inference, not by how much you keep.
LLM EconomicsDistillation Just Got 15x Cheaper. Here Is What That Does to Your AI Cost Model
A new memory-efficient training method cut peak VRAM in knowledge distillation from 85.2 GiB to 5.45 GiB at 32K context, which moves the volume at which running your own small model beats paying per token.
LLM EconomicsDeepSeek's API Price Hike: Why Cheap Tokens Were Never a Strategy
DeepSeek announced on August 6, 2026 that it will raise API prices by a relatively large margin, and the smartest response for AI builders is to model their exposure now, before the number lands.
LLM EconomicsLLM API Pricing Comparison 2026: GPT, Claude, Gemini and DeepSeek by Blended Cost Per Million Tokens
The cheapest LLM API in August 2026 is DeepSeek V4-Flash at $0.14/M input and $0.28/M output, but the number that decides your gross margin is the blended rate for your own input:output mix, not any provider's headline input price.
LLM EconomicsOpen-Weight vs Frontier LLMs: How to Model the Real Cost Difference
Open-weight models are close enough to frontier quality that the switch is now a pricing decision, but the per-token sticker price hides the serving, safety and compliance work the API price was quietly covering.
LLM EconomicsInference Engineering Is a Gross Margin Lever, Not an Infra Detail
Inference engineering is the discipline of turning model weights into a fast, affordable production API, and the throughput gains it produces land in someone's gross margin: yours if you serve the model, your provider's if you buy tokens.
Open-Weight Models and Your LLM Cost Per Token: What DeepSeek V4 Flash Actually Changes
An open-weight model landing within a few points of the frontier does not automatically cut your AI bill: your real cost per token is set by how many tokens you consume, how fast you can serve them, and whether you own the hardware at all.
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