... Claude Code twice: explain 4 source files and how they relate. Once with a single agent reading all four, once with a lead agent that launched one subagent per file and combined the answers. 3 runs each, same model, token counts from the CLI's JSON usage output (input + output + cache read + cache creation, subagents included). Single agent: about 106k tokens

... Here s gpt-realtime-2.1 on its published schedule. Text input is $4 per million tokens. Audio input is $32. Same model, same request, and the audio side costs eight times more. My engine used to price audio tokens

... excited to share a major milestone for GLMall, our blockchain powered global commerce ecosystem. We're preparing for the launch of GLX, alongside a proposed $2.265 million token fundraising round to support the next phase of GLMall's development. What is GLMall? GLMall brings six marketplaces together within one connected ecosystem: Products and online stores Professional and personal services Jobs and recruitment Real estate GLHelp - community support and donations GLNFT - digital assets and NFTs Our goal is to make global ... ... commerce more connected, accessible and transparent while giving users greater control over their data. What makes the technology different? GLMall is built around GloBra's Chain Code Technology and Parallel Token

... AgentDock 1.4 is out. The short version: it now works on a Mac without cmux, tells you what your agents tokens would cost at API prices, lets you leave a message for a busy agent, answers questions from other agents over MCP, and reads seven more agents. Works without cmux If you run Claude Code or Codex in any terminal, or in the Claude or Codex app, AgentDock now shows them on a Mac that doesn t have cmux. Before ... ... strip and the menu showed only the cmux error. cmux is optional. Costs at API prices The hover card, the Tokens

... users. They came from running my own test suite. So before I market anything, I did the math. Everything below is my estimate, not measured on production. The numbers: Groq lists this model at about $0.15 per million input tokens and $0.60 per million output tokens

... Last time I wrote about the small itch: one OpenAI bill , no idea which feature spent it, so I built a tiny logger. One line after every LLM call, sending model and token counts to my endpoint. That line still exists. So the question I kept asking myself: if the integration is one line, what s an SDK for? (an "SDK" sounded very cool in my head at that time, someone who -before making this product- had no clue what ... ... where everything works. Then I started reading other people s usage objects, and the old routine kicked back in: open a docs page, hit a word I didn t know, open another tab to look it up, repeat. Cached tokens

... tempting to send more context on every call. For anything personal, that is the wrong place to spend the savings. OpenAI announced GPT-6.1 Sol at DevDay on 2 October. Its API page lists $2.00 per million input tokens, $0.10 for cached input and $10.00 for output, with a 1,050,000-token

... gives your agent a list. The other gives your agent a decision. 2. The Linux Kernel Benchmark (74,619 files) We cloned torvalds/linux locally and ran cold index extraction and queries on both engines: Filesystem Discovery: Synapse 2.0s vs Graphify 1m 15s (37.5 faster) Peak RAM Consumption: Synapse 877 MB vs

... pricing. A real question I could not answer until I went looking. The intuition is that a better model needs fewer attempts, so a job should get cheaper. My bill kept going the other way, and the price per token had gone down, not up. The answer turned out to be in the docs. Reasoning models produce a block of internal work before they answer, and OpenAI's guide says it plainly: those tokens

... product. But when the time actually comes, a ton of questions appear... For us, pricing plans are also connected to the architecture of the product. We built a dashboard where we can include or exclude features, storage, and AI tokens for each plan. But deciding what should actually be included in each plan became the subject of many team meetings. Especially in our case, where we have a complex product with many different modules and capabilities - where users share large ... ... around that moment, and the plan structure follows more naturally. A few things that helped us move forward: AI usage was the trickiest lever. It's a real cost, so you can't just make it unlimited. But hard token

... post will lead with: on Terminal-Bench-Science , a benchmark for autonomous scientific computing, Fable 5.1 scores 52.6% more than double Fable 5 s 24.7%, and comfortably ahead of Opus 5 s 29.0%. It ships with a 1-million-token context window , up to 128K tokens

... push back on hardest, because it's the answer I hear whenever this comes up: costs are collapsing, so just wait. The unit price genuinely is collapsing. GPT-4-class inference ran somewhere around $20 30 per million tokens in late 2022; equivalent performance is roughly $0.40 0.80 today. I'd treat the multipliers people quote with suspicion I've seen 50x, 300x and 1,000x for the same three-year window, and which one you get depends entirely ... ... which two models someone picked to compare. The direction is real. The round number is marketing. But per-token

... most auth setups issue a JWT and move on. the token is valid, the user is in, done. but here's the scenario nobody wants to think about: the token

... Models shipped million-token windows this year. Then the research showed they quietly get worse the more you feed them and that flips how you build. There's a move almost every maker makes the first time they build something on top of an AI model, and I made it too. The window is huge now, so you fill it. All the docs. The whole conversation history. Every tool you might conceivably need. The reasoning goes: the model is smart ... ... well they held up as the input got longer. The finding is uncomfortable if you've been dumping everything into the prompt: accuracy degrades well before the window is anywhere near full. A model advertised at a million tokens

... probably saw the comparison: one coding agent harness sends ~33k tokens before your prompt, another sends ~7k. Big thread, lots of outrage about waste. I finally read the whole study instead of the headline, and the actually useful findings are different from what got shared. First, in their realistic-config lane (instruction file + several MCP servers), the "light" harness came out HEAVIER: ~90.8k vs

... Analyzed a day of token logs across an autonomous coding agent setup running on internal codebases. The raw count: 769M input tokens

... tools, and a few things genuinely surprised me. The efficiency numbers aren't close, and not in the direction I expected. One widely cited test had Claude Code completing an identical multi-file feature task using around 33,000 tokens with zero errors , while Cursor Agent burned roughly 188,000 tokens

... SWIFT just built its answer to stablecoins, and almost everyone misread it. Seventeen banks, six continents, live this month on a tokenized-deposit ledger. The story got told as "banks embrace blockchain." It's really banks defending their deposits. When a customer buys a stablecoin, the money leaves the bank for an issuer's reserve. Roughly $315B has already made that trip. Tokenized

... careless Netfox can expose a read-only metrics endpoint, so your own monitoring can scrape your network. Handy and, it turns out, far too easy to leave wide open. Switch on "allow access from other devices" without setting a token and that endpoint was reachable from anywhere on your network with no authentication at all . What it serves is your entire device inventory: every IP, every MAC address, every hostname, every open port. That's fixed ... ... kind of fix I'd rather tell you about than quietly bury in a changelog. It fails closed. No token

... Over the past year, I've noticed that discussions around asset tokenization have shifted away from "Will this technology work? " to "How do we build something that's production-ready?" The technical side of tokenization

... Anthropic and Google charge heavy text token rates when you feed them huge context windows, logs, or codebases. But if you render that exact same text into a dense PNG, vision OCR pricing kicks in cutting overall token

... using Claude for content creation, but my tokens get used up pretty quickly. Does anyone have tips for reducing token

... install copium-ai copium wrap claude That is it. Two commands. Now every Claude Code request routes through a local compression proxy before hitting the API. My prompts get 40-80% smaller. Same answers come back. Where My Tokens Were Going I ran copium stats --period month after the first week and saw the breakdown: Category Tokens/Day (Before) Tokens/Day (After) Savings File reads (duplicates) 180K 12K 93% Tool outputs (JSON) 320K 64K 80% Build logs 95K 14K 85% Search results ... ... 150K 30K 80% Conversation history 200K 140K 30% Tool schemas 45K 8K 82% Total 990K 268K 73% Almost a million tokens

... tools hide limits until you hit a wall. We tried to make Oasis usage visible up front. Insight for other users:  The  daily token usage bar  shows how much of your  plan allowance  you have used, compared to your  Kahana subscription limit . It is tied to  plan limits from subscription and usage services , not a raw model quota alone. That way you see  remaining headroom for your billing period , not a mystery ... ... composer or in the header  for the bar and label. After a long chat or a voice session, give it a few seconds to refresh. If numbers look stale, reopen the assistant (offline time can delay sync). Bonus tokens

... businesses across India, the Middle East, and Southeast Asia. Every month, we're making thousands of API calls across multiple providers and for the longest time, our AI cost estimates were embarrassingly wrong. Not because we weren't tracking tokens. We were. We didn't know what we didn't know. The problem that made us build this Six months into production, our bills were consistently 3 4 our estimates. We started digging. Turns out the token