Top all-time · #8168
FuriosaAI Blogs
Company blog · furiosa.ai/bloghardwareai
FuriosaAI Blogs is the company blog at furiosa.ai, writing about hardware and ai. Since 2022, 10 different Hacker News readers have linked it 11 times, most often “Compiler optimizations for 5.8ms GPT-OSS-120B inference (not on GPUs)”. It is still writing: the last post was on 2026-10-28, and you can follow it by feed.
Too few sampled comments (7) to say how often HN recommends it.?
Why HN links it
HN readers link FuriosaAI's blog and product pages for its RNGD AI inference chip, including efficiency comparisons with H100s, LLM serving results and MLPerf benchmarks.
Summarised by Claude from a sample of 7 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
FuriosaAI designs high-performance, power-efficient AI accelerators (NPUs) used in data centers for computer vision, GenAI, LLMs, and demanding workloads.
Most-linked posts?
- /3 people · 3 mentions · first linked 2022-08-26
- Compiler optimizations for 5.8ms GPT-OSS-120B inference (not on GPUs)2 people · 2 mentions · first linked 2025-10-17
What Hacker News says?
In case anyone's interested in these niche startups like taalas, here are a few more: 1. https://matx.com/ 2. https://www.d-matrix.ai/ 3. https://www.etched.com/ 4. https://www.positron.ai/ 5. https://hyperaccel.ai/ 6. https://axelera.ai/ 7. https://www.enchargeai.com/ 8. https://furiosa.ai/
Comment linking /
on “OpenAI Jalapeño: Better than Nvidia Blackwell”Submitted Compiler optimizations for 5.8ms GPT-OSS-120B inference (not on GPUs) as a story · 9 points
HN discussionAdding: https://www.esperanto.ai/ - RISC-V based Tensor computes chip, Founded by Intel Hybrid Parallel Computing Vice President Dave Ditzel. https://www.furiosa.ai/ - AI accelerator company which show good results in MLPerf benchmark.
Comment linking /
on “Ask HN: Chip startups?”Submitted Furiosa: 3.5x efficiency over H100s as a story · 5 points
HN discussionI believe Furiosa hardware is a variant of TPU, and that's pretty much why they can beat Nvidia on LLM inference. GPUs are more general purpose, which means Furiosa can cut some of the overhead with designs dedicated for matrix multiplication only. https://furiosa.ai/blog/tensor-contraction-processor-ai-chip...
Comment linking /blog/tensor-contraction-processor-ai-chip-architecture
on “Furiosa: 3.5x efficiency over H100s”Submitted How DRA and CDI are shaping Kubernetes for AI workload as a story · 2 points
HN discussionI think it's actually really cool to focus on efficiency over just raw performance! The page for the cards themselves goes into more detail and has a pretty nice graph: https://furiosa.ai/rngd You can see them admit that RNGD will be slower than a setup with H100 SXM cards, but at the same time the tokens per second per watt is way better! Actually, I wonder how different that is from Cerebras chips, since they're v…
Comment linking /rngd
on “Furiosa: 3.5x efficiency over H100s”Submitted FuriosaAI unveils RNGD at Hot Chips 2024 as a story · 2 points
HN discussionLooking at their blog, they in fact ran gpt-oss-120b: https://furiosa.ai/blog/serving-gpt-oss-120b-at-5-8-ms-tpot-... I think Llama 3 focus mostly reflects demand. It may be hard to believe, but many people aren't even aware gpt-oss exists.
Comment linking /blog/serving-gpt-oss-120b-at-5-8-ms-tpot-with-two-rngd-cards-compiler-optimizations-in-practice
on “Furiosa: 3.5x efficiency over H100s”From the last thread on this ( https://news.ycombinator.com/item?id=32610780 ): - https://sambanova.ai/ (Enterprise AI and dataflow-as-a-service for established models) - https://www.cerebras.net/ (AI accelerator, trying to compete with Nvidia) - https://www.graphcore.ai/ (Another AI accelerator company, UK based) - https://femtosense.ai/ (Sparse NNs on very low power chips, cool hardware and software challenges) -…
Comment linking /
on “OpenAI is exploring making its own AI chips and evaluates acquisition targets”I also know the founder of an AI chip company (ex-AMD), they taped out in 2022, got working chips on the first try. Miraculously, they hired a good software team, some even with previous compiler experience. In their brochure they write things like: > In 2022, FuriosaAI remained the only startup to submit results in MLPerf Inference... This time, through purely enhancements in the compiler, our team was able to doub…
Comment linking /
on “The tiny corp raised $5.1M”
