Other4 days ago
AI Model Rightsizing for OpenAI and Anthropic | SpendLens AI
Rightsize OpenAI and Anthropic models. See what drives your AI bill, then validate cost-efficient model changes without rewriting your application.
@SpendLensAI · X
The full gallery
Tech stack
22 projects
Rightsize OpenAI and Anthropic models. See what drives your AI bill, then validate cost-efficient model changes without rewriting your application.
@SpendLensAI · X
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
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]
Access 207+ AI models from different providers through a single unified API.
TaylorM492 · HN
InferAll – One API for OpenAI, Anthropic, Google, Nvidia Nim
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
Scores AI-generated ad creative and returns verdicts (run/fix/kill) via MCP and REST API.
ds246 · HN
Spendict – a performance marketer's verdict for AI agents, over MCP
Combine multiple AI models in one place. Run multi-AI chat and AI meetings where ChatGPT, Claude, Gemini and more collaborate, compare, and debate. Start free.
@PayCall_ · X
The AI subscription developers must have. 40+ open-source models — DeepSeek, Qwen, Mistral, Kimi K2.5, MiniMax, GLM-5 and more — in any editor. One plan, one subscription. From $9/
@openadapter · X
Public token leaderboard ranked by bid weight. Highest score wins. Score decays over time.
@Ranktokenlol · X
Built a live board where rank is a dollar amount that melts ~2.5% an hour.
API platform providing access to Pingu models with pre-paid credits and team management.
@ozgurozkan123 · X
You not only need abliterated model for offensive cybersecurity simulations you also need a good harness: made for this. Get your abliterated model API from configure below export CLAUDE_CONFIG_DIR="$HOME/.audncode-platform" export OPENCLAUDE_SKIP_AUTH=1 export CLAUDE_CODE_USE_OPENAI=1 export OPENAI_BASE_URL=" export OPENAI_API_KEY="<GET_API_KEY_FROM_platform_audn_ai>" export OPENAI_MODEL="necromicon" export OPENCLAUDE_AUTOCONTINUE=0 export OPENCLAUDE_AUTOCONTINUE_DECIDER=0 voila, you run on export const CYBER_RISK_INSTRUCTION = IMPORTANT: Assist with security testing, defensive security, CTF challenges, and educational contexts, requests for destructive techniques, DoS attacks, mass targeting, supply chain compromise, or detection evasion for malicious purposes. Dual-use security tools (C2 frameworks, credential testing, exploit development), pentesting engagements, CTF competitions, security research, or defens