Fireworks - Blog

Enabling Function Calling in DeepSeek v3: Bridging the Gap Between Text and Action

Large language models (LLMs) generate impressive text but cannot access or update real-world information. Function calling addresses this by allowing LLMs to use external functions or APIs, extending their capabilities. Fireworks AI API now supports function calling with DeepSeek V3.

Featured Blogs

Enabling Function Calling in DeepSeek v3: Bridging the Gap Between Text and Action

DeepSeek v3 and R1 Model Architecture: Why it's powerful and economical

DeepSeek R1 Just Got Eyes with Fireworks AI Document Inlining

From text to task: Constrained generation for structured extraction in R1

Distillation with Reasoning: Can DeepSeek R1 Teach Better Than Humans?

Mistral Small 3 Now Available on Fireworks: Faster, Lighter, and More Efficient

Beyond Supervised Fine Tuning: How Reinforcement Learning Empowers AI with Minimal Labels

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DeepSeek V3 just got vision capabilities!

20x faster Whisper than OpenAI - Fireworks audio transcribes 1 hour in 4 seconds

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Fireworks f1: A breakthrough in complex reasoning with Compound AI

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FLUX.1 on Fireworks: Fast, frugal, and flexible

FireAttention V3: Enabling AMD as a viable alternative for GPU inference

Three projects, one platform: A developer's winning streak with Fireworks AI

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How Enterprises are using Multimodal Models in production with Fireworks

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FireAttention V2: 12x faster to make Long Contexts practical for Online Inference

Firefunction-v2: Function calling capability on par with GPT4o at 2.5x the speed and 10% of the cost

Announcing custom models and on-demand H100s with 50%+ lower costs and latency than vLLM

GPUs on-demand: Not serverless, not reserved, but some third thing

Code Generation with Large Language Models - Fireworks AI Take

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Fireworks launches fine-tuning service - Rapidly iterate on quality and scale to production through Fireworks inference

Fireworks Platform Spring 2024 Updates

FireFunction V1 - Fireworks’ GPT-4-level function calling model - 4x faster than GPT-4 and open weights

Why do all LLMs need structured output modes?

FireLLaVA: the first commercially permissive OSS LLaVA model

FireAttention — Serving Open Source Models 4x faster than vLLM by quantizing with ~no tradeoffs

Fireworks Raises the Quality Bar with Function Calling Model and API Release

Mixtral 8x7B on Fireworks: faster, cheaper, even before the official release

LLM Inference Performance Benchmarking (Part 1)

New in Fireworks: Image-to-Image and ControlNet support for SSD-1B and SDXL!

Fireworks.ai Achieves SOC 2 Type II and HIPAA Compliance

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Multi-Query Attention is All You Need