Arch-Function: 3B parameter LLM that beats GPT-4o on function calling

Hacker News

Hi HN! My name is Salman Paracha. I aam the the Founder/CEO of Katanemo - the organization behind the open source Arch GW (an intelligent gateway for prompts - https://github.com/katanemo/arch ). Today, we are making the (SOTA) LLMs engineered in Arch GW for function calling scenarios available under an OSS license that borrows from Llama's community license. What is function calling? Function calling helps developers personalize apps by calling application-specific operations via user prompts. This involves any predefined functions or APIs you want to expose to perform tasks, gather information, or manipulate data - via prompts. With function calling, you get to support agentic workflows tailored to domain-specific use cases - from updating insurance claims to creating ad campaigns. Arch-Function analyzes prompts, extracts critical information from prompts, engages in lightweight conversations with the user to gather any missing parameters and makes API calls so that you can focus on writing business logic. Arch-Function is an auto-regressive model that if run on the NVIDIA A100 GPUs using vLLM offers throughput of ~1900/output tokens per second, and a output token price of $0.10/M token. This is ~12x faster and 44x cheaper than GPT-4o.

Visit product View on Hacker NewsOct 16, 2024

Share card

Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, agentic · Missing: mac, agents, macos

90%90% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersIH features products with proven revenue · Strong signals: para, ios · Missing: supports, reddit linkedin, podcasting

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, video

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, llama, io · Missing: https docs, excited, just released

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Serverless GPT Function Calling50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Serverless GPT Function Calling

Hacker News2

TensorFlowithInception as an OpenFaaS function34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TensorFlowithInception as an OpenFaaS function

Hacker News4

TensorFlow ImageNet/Inception as an OpenFaaS function48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TensorFlow ImageNet/Inception as an OpenFaaS function

Hacker News4

Added Supporting Function by Patreon to Pixela63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Added Supporting Function by Patreon to Pixela

Hacker News1

Weighted Scoring Function for CodersBracket32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Weighted Scoring Function for CodersBracket

Hacker News1

typerassistant – turn any Typer app in to a function-calling assistant45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

typerassistant – turn any Typer app in to a function-calling assistant

Hacker News1

Open-Source Function Calling (Anthropic, or Any LLM)57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Open-Source Function Calling (Anthropic, or Any LLM)

Hacker News2

Function calling on Claude 2 and Cohere with good DX powered by Cursive39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Function calling on Claude 2 and Cohere with good DX powered by Cursive

Hacker News1

Tiger – Function Hub for LLM Agents33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tiger – Function Hub for LLM Agents

Hacker News28

Relaunch of function-plot – a powerful function plotter54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Relaunch of function-plot – a powerful function plotter

Hacker News4

Browse all products Analyze your launch