Other1 week ago
OpenLLM — All your LLM needs in 1 place
Format-agnostic LLM hub. Bring your own provider keys and route across Anthropic, OpenAI, ChatGPT/Codex, Kimi, Alibaba DashScope, and AWS Bedrock — with unified observability and c
@0xxmemo · X
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Format-agnostic LLM hub. Bring your own provider keys and route across Anthropic, OpenAI, ChatGPT/Codex, Kimi, Alibaba DashScope, and AWS Bedrock — with unified observability and c
@0xxmemo · X
Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
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
Route LLM calls to cost-effective models without sacrificing quality.
george_avila · Product Hunt
IQ Routing Trajectory-aware LLM routing that cuts agent cost
Send your question to a panel of LLMs that peer-review each other and return one synthesized answer.
u/Puzzleheaded-Log-27 · Reddit
Building a multi-model AI deliberation tool taught me something about trust LLM Counsel isn't another wrapper around one model - it sends your question to a panel of frontier LLMs, has them peer-review each other anonymously, and an impartial "chairman" model returns one synthesized answer. Free to start, pay-as-you-go after, credits don't expire. What I've learned so far: people trust a synthesized answer a lot more once they can see that the models actually disagreed and how that disagree
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
Grades AI agents' real conversations with an LLM judge, providing A–F scorecards and FinOps analysis.
@tech_maju · X
Compress prompts before LLM API calls to reduce token usage and costs.
@asgujjuasitgets · X
Estimate GPU memory, latency, TTFT, TPOT, and throughput for LLM inference.
popopanda · HN
LLM Inference Calculator – Estimate VRAM, Latency, and Throughput
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 latency and throughput performance across LLM API providers.
@QAInsights · X
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