Models & Pricing | DeepSeek API Docs

The prices listed below are in units of per 1M tokens. A token, the smallest unit of text that the model recognizes, can be a word, a number, or even a punctuation mark. We will bill based on the total number of input and output tokens by the model.

tokens are getting more expensive

"language models will get cheaper by 10x" will not save ai subscriptions from the short squeeze

Claude Fable 5.1 and Mythos 5.1: The System Card

At the time of its release Claude Fable 5.1 was, by a healthy margin, the most capable publicly available AI model in the world.

Jacky Kwok on Twitter / X

Scaling self-verification with DeepSeek V4 Flash beats Claude Fable 5 on Terminal-Bench 2.1, while being 11x cheaper 💰As open-source models become more capable, they can now generate large numbers of high-quality candidate solutions and verify their own outputs at very low… https://t.co/as2HtyHzzW pic.twitter.com/XzVBgr5JPz— Jacky Kwok (@jackyk02) August 17, 2026

Groq On-demand Pricing for Tokens-as-a-Service

Groq powers leading openly-available AI models. View the pricing of our core models including GPT-OSS, Kimi K2, Qwen3 32B, and more.

A broken pricing paradigm

A token is not a fixed unit of cost Variance in usage creates an interconnected pricing and scaling issue Anjali Shrivastava anjali.shrivastava99@gmail.com | @anjali_shriva THIS ESSAY IS NOW LIVE! A token is not a fixed unit of cost PART I: High variance in AI demand breaks unit economics and re...

Simple Pricing | Machine Learning Infrastructure | Deep Infra

We provide only pay-what-you-use pricing with no long-term contracts or upfront costs for our machine learning models and infrastructure. Learn more!

Jev introduces a new shape of LLM—System One, aka Decision Models

Last week TypeSafe AI unveiled Jev, their first example of a new category of model that they are calling “System One models” (I’m with Maggie Appleton, I think “decision models” …

AI is Cheap Building It Isn't

Cheaper Tokens Meet an Expensive Reality

AI Inference Pricing, EU Hosted, Per Token | TensorX

Transparent, pay-as-you-go pricing for private AI inference on TensorX. No lock-in, EU-hosted, with zero data retention and an OpenAI-compatible API.

The control layer for AI

The industry spent two years teaching LLMs to speak JSON. That work mattered: free-form text was unusable in production. Today, every serious inference provider uses some implementation (often open-source) of structured output. Structured output has become essential infrastructure that the team at .txt is proud to have spearheaded. Even as the ecosystem evolves, and open-source alternatives emerged, our engine remains the state of the art.

The control layer for AI

The industry spent two years teaching LLMs to speak JSON. That work mattered: free-form text was unusable in production. Today, every serious inference provider uses some implementation (often open-source) of structured output. Structured output has become essential infrastructure that the team at .txt is proud to have spearheaded. Even as the ecosystem evolves, and open-source alternatives emerged, our engine remains the state of the art.

Ways to think about token pricing — Benedict Evans

AI is in a supply crunch today, but what happens when we come out of it? How and where will supply, demand, price, capacity and capex get back into equilibrium? Today, model labs can name their price, but why won’t they end up as low-margin commodity infrastructure?

rektide/opencode-quota-plus

opencode-quota-plus — maintained, enhanced fork of slkiser/opencode-quota: pro-rata burn-rate indicator (default on), subagent-aware session-token tree, composable bar themes, upstream-tracking maintenance