LLM Economics
Token math, model selection, and the true unit cost of every generation.
LLM EconomicsGPT-6.1 Terra Pricing: Cost per Task vs Sol and Luna
GPT-6.1 Terra costs $1 per 1M input tokens and $5 per 1M output tokens, half of Sol's $2 and $10. For an illustrative support bot handling 50,000 chats a month, that is about $300 on Terra versus $600 on Sol and $30 on Luna.
LLM EconomicsKimi K3.1 Pro Pricing: Cost per Task and Monthly Bill
Kimi K3.1 Pro costs $2 per million input tokens, $10 per million output tokens and $0.20 per million cached input tokens, one third below K3, but it uses about 15% more tokens per task, so the real saving is closer to a quarter.
LLM EconomicsOpenAI Decisions API Pricing: What 10M Decisions Cost
OpenAI's Decisions API is reported at $0.10 per million tokens, with cached tokens at $0.01, so 10 million small decisions a month cost roughly $130 to $400 depending on caching, before output tokens, which the coverage does not price separately.
LLM EconomicsClaude Duet Pricing: What a Proactive Agent Costs to Run
Claude Duet has no published price yet, but it runs on Opus 5.5 and wakes up on its own, so your cost is set by how often it checks your apps: roughly $18 to $216 per user per month in our illustrative model, depending on polling frequency.
LLM EconomicsReplit Anthropic Split: The LLM Cost Lesson for Founders
Replit's CEO says the company stopped working with Anthropic over cost, partnership and performance, though people familiar with the partnership dispute that account. The lesson does not depend on who is right: switch LLM providers based on cost per finished task measured on your own workload, not on per-token list prices or headlines.
LLM EconomicsLLM PDF Processing Cost: What 89,000 Documents Really Cost
LLM PDF processing cost can be extremely low: one builder reported a $0.77 total API bill for a project that read 89,000 planning decisions. But that bill hides the real costs: local hardware, a roughly 20 hour full re-read, and engineering time. Price per finished document, not per token.
LLM EconomicsJevons Paradox in AI: Why Cheaper Tokens Mean Bigger Bills
Jevons paradox in AI means that when tokens get cheaper, people use so many more that total spend rises. If price per task halves from $0.10 to $0.05, volume must double just to hold spend flat, and a tripling lifts spend 50 percent.
LLM EconomicsOpenRouter Pricing: What a Gateway Really Costs
OpenRouter pricing is the underlying model rate plus whatever platform fee the gateway adds, so the real question is net cost. Say a 5 percent fee on $10,000 of monthly tokens adds $500, and routing 15 percent of spend to cheaper models saves $1,500, a net gain of $1,000.
LLM EconomicsMoE Cost per Token: Why Active Parameters Rule
For a mixture-of-experts model, compute per token follows active parameters, while the GPUs you must rent follow total parameters. A model with 40B active out of 400B total can be cheaper per token than a dense 70B at high utilization, and more expensive when traffic is thin.
LLM EconomicsJev AI Model Cost: Is It Cheaper per Task?
Jev is a new class of AI model from a ChatGPT co-inventor that promises cheaper and faster software intelligence, but no price list is confirmed here. Judge it by cost per successful task: a model at $0.04 per task with 70 percent success beats a $0.10 incumbent only if failures escalate cheaply.
LLM EconomicsHow Many Tokens Is an Image? Vision Model Cost
An image is converted into tokens before the model reads it, and the count depends on the encoder and resolution. If an image becomes 1,000 tokens and input costs $2 per 1M, each image costs $0.002, so 100k images a month costs about $200.
LLM EconomicsGPT-6.1 Sol Pricing: Cost per Agent Task
GPT-6.1 Sol is priced at $2 per 1M input tokens, $0.10 per 1M cached input tokens and $10 per 1M output tokens. A 20-step coding agent task with 40k tokens of mostly cached context costs about $0.47, so 1,000 tasks a month runs roughly $470.
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