Hackernews posts about FP16

1. Show HN: Train 300M/32-Layer Model in 1.5GB RAM on Base M1 Mac
   3 points by vlad_kalinkin 21 days ago | discuss
2. Show HN: Cactus Needle 3: 8-29MB automation models can match DeepSeek V4 Flash (cactuscompute.com)
   230 points by HenryNdubuaku 3 days ago | 91 comments
3. Anthropic withheld latest AI model from UK testing agency (www.ft.com)
   5 points by JumpCrisscross 12 days ago | discuss
4. Historic Business Machines Collection (cdm16471.contentdm.oclc.org)
   2 points by Group_B 7 days ago | discuss
5. ONNX Runtime and CoreML May Silently Convert Your Model to FP16 (ym2132.github.io)
   98 points by Two_hands 9 months ago | 17 comments
6. Insights from 84,000 comments on "Ask HN: Who Is Hiring" using Llama3.1-70B-FP16 (exxa.notion.site)
   8 points by Blue_Cosma almost 2 years ago | 1 comments
7. TurboOCR: 270–1200 img/s OCR with Paddle and TensorRT (C++/CUDA, FP16) (github.com)
   7 points by pfdomizer 5 months ago | 4 comments
8. Running the Deepseek-R1 671B Model at FP16 Fidelity on AMD EPYC CPUs (www.servethehome.com)
   5 points by tanelpoder over 1 year ago | 2 comments
9. 90T/s on my iPhone llama3.2-1B-fp16 (www.reddit.com)
   5 points by darkolorin over 1 year ago | 1 comments
10. Show HN: TurboOCR up to 1200 pages/s with Paddle and TensorRT (C++/CUDA, FP16) (github.com)
    3 points by pfdomizer 5 months ago | discuss
11. Native vLLM and ROCm 7.15 for RX 6000 (RDNA2) on Windows 11 – 26 Tflops FP16 (github.com)
    2 points by esseba-dev about 1 month ago | discuss
12. Number to GPU Float Converter: FP32, FP16, BF16, FP8, and FP4 Explained (www.bestgpusforai.com)
    2 points by javaeeeee 2 months ago | discuss
13. TTS engines: WebSocket vs. sync is 5.5x, INT8 slower than fp16 on M4 (ai.gopubby.com)
    2 points by KirMoisha 5 months ago | discuss
14. Defeating the Training-Inference Mismatch via FP16 (arxiv.org)
    2 points by matt_d 11 months ago | discuss
15. PyTorch 2.6 Delivers FP16 Support for x86 CPUs, Better Intel GPU Experience (www.phoronix.com)
    2 points by rbanffy over 1 year ago | discuss
16. Defeating the Training-Inference Mismatch via FP16 (arxiv.org)
    1 points by billyzs 11 months ago | discuss
17. PyTorch 2.6 Delivers FP16 Support for x86 CPUs, Better Intel GPU Experience (www.phoronix.com)
    1 points by mikece over 1 year ago | discuss
18. Show HN: Kitten TTS – 25MB CPU-Only, Open-Source TTS Model (github.com)
    1003 points by divamgupta about 1 year ago | 361 comments
19. Show HN: Three new Kitten TTS models – smallest less than 25MB (github.com)
    561 points by rohan_joshi 6 months ago | 181 comments
20. Show HN: Appear as anyone in video calls like zoom or Google meets (www.phazr.ai)
    110 points by michaelphi over 1 year ago | 51 comments
21. Show HN: ZSE – Open-source LLM inference engine with 3.9s cold starts (github.com)
    58 points by zyoralabs 7 months ago | 9 comments
22. Show HN: GPULlama3.java Llama Compilied to PTX/OpenCL Now Integrated in Quarkus
    24 points by mikepapadim 9 months ago | 6 comments
23. Show HN: Run 500B+ Parameter LLMs Locally on a Mac Mini (github.com)
    17 points by fatihturker 7 months ago | 10 comments
24. Show HN: OpenGraviton – Run 500B+ parameter models on a consumer Mac Mini (opengraviton.github.io)
    13 points by fatihturker 7 months ago | 5 comments
25. Show HN: Lightweight Llama3 Inference Engine – CUDA C (github.com)
    12 points by abhisheknair10 over 1 year ago | discuss
26. Show HN: OS Megakernel that match M5 Max Tok/w at 2x the Throughput on RTX 3090 (github.com)
    6 points by GreenGames 6 months ago | 1 comments
27. Show HN: Slash your LLM Inference Costs with Overnight Processing
    5 points by Blue_Cosma almost 2 years ago | 1 comments
28. Transformers 2.0: What Ilya and Sam Might Have Missed
    5 points by metehan777 almost 2 years ago | 1 comments
29. Show HN: 1B Embeddings
    4 points by INVARIAN 6 months ago | 2 comments
30. Tq-KV – Rust implementation of TurboQuant that works on GGUF models
    3 points by onurgokyildiz 6 months ago | discuss
31. Show HN: HyperAI GPU Leaderboard – A benchmark comparison site for AI workloads (hyper.ai)
    2 points by Ada_trying 8 months ago | 2 comments
32. Show HN: Efficient LLM Architectures for 32GB RAM (Ternary and Sparse Inference) (github.com)
    2 points by fatihturker 7 months ago | 1 comments
33. Show HN: Loft CLI – Fine-tune and run LLMs (1–3B) on 8 GB MacBook Air, no GPUs
    2 points by dips2umar about 1 year ago | 1 comments
34. Show HN: I made Qwen3.5-4B 13% smarter by compressing it to 4-bit (huggingface.co)
    2 points by singularity_max 7 months ago | discuss