Alternatives
Products that do what Tokenmaxx does
Wholesale AI tokens. You pay bulk rates, not retail.
- 1PP
The LLM providers are constantly adding new models and updating their API prices. Anyone building AI applications knows that these prices are very important to their bottom line. The only place I am aware of is going to these provider's individual website pages to check the price per token. To solve this inconvenience I spent a few hours making pricepertoken.com which has the latest model's up-to-date prices all in one place. Thinking about adding image models too especially since you have multiple options (fal, replicate) to use the same model and the prices are not always the same.
2025 · pricepertoken.com
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- 4TP
Hey HN! Tokencost is a utility library for estimating LLM costs. There are hundreds of different models now, and they all have their own pricing schemes. It’s difficult to keep up with the pricing changes, and it’s even more difficult to estimate how much your prompts and completions will cost until you see the bill. Tokencost works by counting the number of tokens in prompt and completion messages and multiplying that number by the corresponding model cost. Under the hood, it’s really just a simple cost dictionary and some utility functions for getting the prices right. It also accounts for…
2024 · github.com
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- 6AU
Hi HN, I was once given the advice: Don't waste expensive frontier model credits (GPT/Claude/etc.) on bulk work. Send the boring, repetitive, high-volume jobs to a smaller model, and save the expensive prompts for when you actually need frontier-level reasoning. I complained and told my manager that I shouldnt have to think about using certain models for certain coding tasks, and that one model should handle everything. Well, here we are anyway. If anyone needs a place to absolutely abuse an LLM with high-volume tasks, come beat ours up at https://yolo-auto.com. Here are…
Jul 2026 · yolo-auto.com
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I use Claude Code, Codex and Cursor (and sometimes Antigravity) basically every day, and could never tell how much I was actually consuming across all of them. So I built TokenMaxxer. A small CLI reads the files these tools already write locally and puts it all in one dashboard, broken out by tool, model, provider and day. It covers 18 tools now, and you get a profile page with your daily activity, cost estimates, and your top models and tools. There's also a global leaderboard if you want to compete against other TokenMaxxers! I'd love to see if anyone can beat the first place (currently…
Aug 2026 · tokenmaxxer.xyz
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I'm a solo dev in Taiwan. I built 4 AI agents that handle content, sales leads, security scanning, and ops for my tech agency — all on Gemini 2.5 Flash free tier (1,500 req/day). I use ~105. Monthly LLM cost: $0. Architecture: 4 agents on OpenClaw (open source), running on WSL2 at home with 25 systemd timers. What they do every day: - Generate 8 social posts across platforms (quality-gated: generate → self-review → rewrite if score < 7/10) - Engage with community posts and auto-reply to comments (context-aware, max 2 rounds) - Research via RSS + HN API + Jina Reader → feed…
Mar 2026
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- 16CS
Hi HN! Token cost has started to become a high topic of concern to all of us. I tried a few (awesome) tools such as rtk, caveman, and the recent (hillarious but effective) ponytail. What they usually do, is in-line token reduction, e.g. try to compress requests / responses as much as possible. But then it hit me (and I’m sure others had similar ideas) - just like we have routers that pick the right model, why not have something that will also narrow down the amount of available tools, skills and mcps based on repo/context? People usually accumulate skills, agents, MCP servers,…
Jun 2026 · github.com
- 17TE
Hi HN, I'm Paul from Tensordyne. We build AI inference systems and chips on logarithmic math. We've put together an interactive Token Economics Calculator to help make apples-to-apples comparisons of inference hardware across vendors: We're interested in how closely it lines up with the community's view of the market. Why we built this Investors and customers kept asking how our system compares to others (NVIDIA and a growing list of startups). Plenty of publicly available data exists, but it's scattered and inconsistent. News articles, provider sites, Artificial Analysis, MLCommons, and now…
Nov 2025 · tensordyne.ai
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I built this after hitting the same wall repeatedly — no good way to enforce token budgets in application code. Provider caps are account-level and tell you what happened, not what is happening. Two ways to add it: # Direct client wrapper client = tokencap.wrap(anthropic.Anthropic(), limit=50_000) # LangChain, CrewAI, AutoGen, etc. tokencap.patch(limit=50_000) Four actions at configurable thresholds: WARN, DEGRADE (transparent model swap), BLOCK, and WEBHOOK. SQLite out of the box, Redis for multi-agent setups. One design decision worth mentioning: tokencap tracks tokens, not dollars. Token…
Apr 2026 · github.com
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