Can LLMs recognize ASCII art?. Our tests show accelerated Elastic Models analyze line-by-line features and combine them using statistical patterns. Try it yourself with DeepSeek-Qwen-14B – 120 tok/s on H100, 40 tok/s on L40s, up to 3× faster. Free API token!.

Replace static scale estimation with dynamic activation quantization. Accuracy jumps to 66.5% – almost original performance. This progress is only possible thanks to open source. Special thanks to SmoothQuant authors (@Guangxuan_Xiao, @jilin_14, @songhan_mit), their method is

After static quantization, MMLU accuracy dropped from 67% to 25%. Use SmoothQuant to shift error into weights – quality recovers to 60%.

Calibrate on your dataset. Run MMLU eval to record baseline accuracy.

Import QLIP + pre-tuned NVIDIA config. Set quantization for all linear layers.

We made this to demonstrate quantization in our QLIP framework. Let’s start – load LLaMA-8B model ready for quantization.

Our research team took @AIatMeta LLaMA-8B, quantized it with QLIP using post-training int8, applied SmoothQuant, and used pre-defined compiler-compatible NVIDIA configs. Why do this? Up to 2× fewer weights and 3.6× faster on one GPU. Try it with our simple Jupyter Notebook.

Our @TheStageAI team was happy to gain early access to the @nvidia B200 from @nebiusai and establish benchmarking for our optimized diffusion models. We now fully support inference of optimized models on B200 across various AI applications - LLMs, VLMs, Text-to-Image,.

RT @TheStageAI: AI engineers and researchers can now use our Quantization API to run accelerated LLMs, VLMs, and diffusion on NVIDIA and ed….

Been cooking up some audio tools. Made a quick playground on Hugging Face Spaces for easy testing. It’s Elastic MusicGen, our fork of Meta’s MusicGen Large by @TheStageAI. Drop prompts, get tracks —.in seconds, right in your browser. 🚀 11× faster than.

Meet Elastic MusicGen Large — our optimized fork of @metaai's MusicGen, powered by ANNA (@TheStageAI’s Automated Neural Network Accelerator):. Ye @kanyewest used AI for vocals on "Bully," calling it the "next Auto-Tune." He switched up later, but tracks.

⌁ EUROPE SIGNAL: ACTIVE ⌁. ↳ Want to accelerate your model’s inference?.↳ These guys sure do. ✦ Berlin: mapped next steps with our investors Christophe Maire and Lukas Erbguth of Atlantic Labs. ✦ Paris: @NVIDIAGTC showed us what’s possible. ✦ Germany: more investor talks

▚▞▚▞ DATA LOG: AI EUROPE ▚▞▚▞. For years, AI talk was all Silicon Valley. After @NVIDIA #GTCParis, one thing became clear: Europe’s AI ecosystem has already kicked into high gear. 🇫🇷 @MistralAI’s dropping open weights that actually run. 🇩🇪 @Aleph__Alpha building native

RT @TheStageAI: Bonjour, Paris 🇫🇷. Just wrapped 2 amazing days at @NVIDIA #GTCParis at @VivaTech — AI infra, agentic systems, and robots wa….

RT @TheStageAI: 🥐 Bon appétit, developers. New @MistralAI models for self-hosting accelerated by TheStage AI:. - New LLM: Mistral Small 24B….

RT @TheStageAI: Wrong model = slow app. We help you pick the right one for your GPU. You can now explore a new Models section on our platf….

RT @TheStageAI: 💻Hey devs - real-time speech transcription inference, zero cost to run! Starting from MacOS 14, M1-M4. Check the crash test….

Hello! We are releasing the fastest LLMs every week! Its has simple HuggingFace libraries interface! Please check!. - All models are coming in 4 tiers: S, M, L, XL. - For instance Llama 8B runs ~200 tok/s. - Models coming with quality, speed benchmarks.

Yes! We already supporting @NVIDIAAI B200! And it's giving us the fastest performance in the world!.