Developer Tools1 week ago
LLM Status — AI model deprecation tracker & CLI checker
Track AI models used in your apps and receive warnings before they're deprecated.
taylorgt · HN
Find every AI model your code calls and warn before it's retired
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Track AI models used in your apps and receive warnings before they're deprecated.
taylorgt · HN
Find every AI model your code calls and warn before it's retired
View LLM model rankings across 10 benchmark questions.
fristovic · HN
She watched me look at model rankings and asked what do the numbers mean... I literally had no good way of explaining it to her so I just came up with something that is approximately in the same ballpark as some of the benchmarks out there lol
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
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
Compare LLM API pricing across 450+ routes and calculate real monthly costs with caching and batch pricing factors.
u/Greywolff06 · Reddit
I built LLMPrice — a free calculator for comparing LLM API costs across 450+ pricing routes I kept running into the same problem when comparing LLM APIs: the headline token price doesn't always tell you what your actual workload will cost. Caching, batch pricing, reasoning tokens, retries, different endpoints, and OpenRouter routes can change the result quite a bit. So I built LLMPrice.com. You enter your workload once — requests, input/output tokens, caching, retries, etc. — and it com
Route LLM calls to cost-effective models without sacrificing quality.
george_avila · Product Hunt
IQ Routing Trajectory-aware LLM routing that cuts agent cost
Compress prompts before LLM API calls to reduce token usage and costs.
@asgujjuasitgets · X
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]
API providing token-level citations for LLM output grounded in attention analysis.
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention
Tests LLM endpoints with adversarial cases and provides OWASP-mapped security audit reports.
@aryaan_sheth · X
- LLM security for small teams
Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
Generate MCP endpoints and llms.txt files from any website for AI agents.
AshHackerNews · HN
AgentReady – MCP server that makes any docs site queryable by AI agents