Blogsby GlyphOct 20
EAGLE-4 Technical Deepdive
In collaboration with Fireworks and fal, we are releasing a technical analysis of EAGLE-4 alongside a public dataset for benchmarking speculative decoding on creative tasks. Why Speculative Decoding?
fal.ai Blog the company blog of fal: latest posts and feed
fal · Company blog · 1 a month · 16 posts since Feb 23, 2026
Sep 17
H3 Max: Built with fal Inference and Training
H3 Max generates a 5-second video in under 3 seconds. In our human preference evaluations against twelve leading video models, it ranks first on quality, prompt understanding, and aesthetics.
Aug 27
Introducing H3 Max by fal
Announcing H3 Max, a post-trained version of MiniMax H3 developed by fal Research and optimized for maximum speed by fal's inference team.
Jul 13
From clay 3d render to a real action short: a 3D-to-AI pipeline with total control
We built a short action film, a 1930s pickup racing a steam freight train through a desert town, and jumping over it, where everything is exactly what was designed upstream: the action, the animation, the camera placement, the timing, the...
Jul 10
FASHN AI: reimagining fashion and photography
fal Editorial Deep dives with the companies taking AI seriously in the industries that matter. One company, one hard problem, and what it actually takes to solve it at scale.
Jul 9
Serving sub-second Ideogram v4 without quality loss
At @fal we serve Ideogram V4 at high speed. At 1K resolution, a generation that used to take 2.75 s now renders in 0.44 s, a 6x speedup with no visible quality loss. We got there by pushing the cost of a generated image down on every axis
Jul 8
How We Achieved ~1000 tok/s and 16x Throughput with DSpark for Ideogram V4 Prompt Expander
At @fal, we've achieved 16 times higher throughput on Qwen3.6 for a use-case that required high interactivity per user using DSpark on SGLang. But why did we need it? And how did we achieve it?
Jun 29
The operational reality of marketing inside an AI company
By Tina Sang, Marketing & Growth Lead at fal I spent last week at Cannes Lions International Festival of Creativity, where nearly every conversation eventually landed on AI. Usually the same questions came up: Will AI replace creatives?
May 19
fal and AWS: Building for the Next Phase of Generative Media
By Emir Lise, Technical Partnerships Manager, AI Infrastructure @fal Today fal announced a strategic partnership with Amazon Web Services (AWS). I interned at AWS in college, working on compute pricing.
May 15
Building long-term trust in a world where creation moves at the speed of thought
By Sean Bonawitz, Head of Trust & Safety at fal My first job was in the US Navy as an EOD platoon commander, where my job was to protect the people around us and make sure they could keep moving forward.
Apr 10
Introducing PATINA
AI image models have become extremely good at producing something that looks like stone, ceramic, brushed metal, leather, or concrete, but these images are not readily usable in a traditional CGI workflow - they have baked-in specular...
Mar 24
Inworld TTS-1.5 Max Now Available on fal
We’re excited to add Inworld TTS-1.5 Max to fal, expanding our set of cutting-edge real-time voice models on the platform.
Mar 19
Connect your AI to 1,000+ models with the fal MCP Server
Today we're launching the fal MCP Server, a hosted endpoint that lets any AI assistant search, run, and chain 1,000+ generative AI models directly from a conversation. One command. No SDK. No docs to read. What is it?
Mar 2
HeyGen models are now available on fal
Starting today, HeyGen's models are available on fal. Whether you need talking avatars, automated video generation, or multilingual lip sync, HeyGen brings a focused set of capabilities that complement what's already on the platform.
Feb 25
Seedream 5.0 Lite Prompting Guide
Seedream 5.0 Lite dropped in February 2026 and it's a different beast from what we've been used to. Every single image on this page was generated with the exact prompt shown. This is an independent guide based on our own testing.
Feb 23
Ulysses Unbound: Experiments in Communication–Computation Overlap
As video diffusion models scale, sequence lengths get uncomfortably large. A practical answer is context parallelism, and within that family, Ulysses is the canonical approach. The core idea is simple: full sequence, sharded heads.
About this blog
fal's own blog on fal.ai, found by the daily check.
Posts per week, last 26 weeks
1 a month over the last six months (or since the feed's oldest post)
Posts by month
Writes about
Product and company (4), Reliability and performance (2), AI and agents (1) in the last six months.
History
Listed on Blogs Sep 28, 2026. No changes to its feed, status or cadence since.