Other1 month ago
FlexInference: Drop your AI costs today
Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
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Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
Semantic caching reduces LLM token costs and latency for AI queries.
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]
Reduce unnecessary tokens in prompts to lower API costs for Claude, ChatGPT, Gemini, and Grok.
u/HourRevolutionary666 · Reddit
Solo founder, first SaaS. Honestly not sure how to get from “it works” to “people use it” Okay so here’s where I actually am right now, not the polished version. Spent months building this on my own. It’s an AI/SaaS tool called Token Optimiser that trims unnecessary tokens out of prompts before they hit the model, so you pay less per call without losing what the prompt actually needs. It’s live at https://www.tokenoptimiser.com , I ran it through a proper benchmark to make sure the numbers
Automatically route each prompt to the cheapest capable model to cut API costs.
u/ASDKING100 · Reddit
Launched an AI API router tonight, and found a bug hours in that would've taken real payments without ever upgrading the account Built LLMLite over the past few weeks — it classifies each prompt and routes it to the cheapest model that can actually handle it, instead of hitting GPT-4o for everything. Free tier, no card needed to try it. Tonight, right as I was about to launch, ran a real transaction to test the payment flow end to end. Paddle processed it, webhook fired, signature verified
An LLM gateway for OpenAI, Anthropic, Google and Azure. Every request logged, priced to the token, and audited for waste you can actually recover.
@razdagan3 · X
Route LLM calls to cost-effective models without sacrificing quality.
george_avila · Product Hunt
IQ Routing Trajectory-aware LLM routing that cuts agent cost
Use one API to access and switch between LLM providers while optimizing inference costs.
justin2025 · Product Hunt
Auriko Trading desk for LLM calls
Analytics dashboard for LLM API spending by model and environment with optimization suggestions.
ATsimbalistov · HN
Show HN: Tracking GenAI cost and endpoint fragility so app teams don't have to
API providing token-level citations for LLM output grounded in attention analysis.
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention
OpenAI-compatible API for running open-weight LLMs and video models.
bingus-bongo · HN
Use GLM-5.3 in Cursor today via tokengo API
Track AI coding costs attributed to pull requests, teams, and organizations.
haseebejaz · HN
TokenSpend, the AI ROI Solution
Get transparent app development cost estimates and visual build plans based on AI tokens.
u/Ejboustany · Reddit
Knowing your build cost from a tokens formula The bigger the feature you are building, the more tokens you spend and how you can calculate the total cost of your build. You will also spend even more tokens making that feature proper and production ready. Say you want users to sign up, log in, verify their email and reset a forgotten password. Built properly it runs around 400,000 tokens. The formula I thought of is: tokens x $1,500 / 1,000,000 = price So those 400,000 tokens come ou