# groq

Published articles for groq.

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## How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin

DevFeed: [How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin](<https://devfeed.tech/articles/how-nvidia-groq-3-lpx-deterministic-execution-drives-power-efficient-high-interactivity-inference-on-nvidia-vera-rubin-26913.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/how-nvidia-groq-3-lpx-deterministic-execution-drives-power-efficient-high-interactivity-inference-on-nvidia-vera-rubin/>)

Author: Tanya Lenz

Published: 2026-09-15T16:55:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Groq 3 LPX](<https://devfeed.tech/topics/groq-3-lpx.md>), [LPX](<https://devfeed.tech/topics/lpx.md>), [NVIDIA Vera Rubin](<https://devfeed.tech/topics/nvidia-vera-rubin.md>), [Vera Rubin NVL72](<https://devfeed.tech/topics/vera-rubin-nvl72.md>), [groq](<https://devfeed.tech/topics/groq.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Low Latency](<https://devfeed.tech/topics/low-latency.md>), [long-context](<https://devfeed.tech/topics/long-context.md>)

Tags: [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [ai-platform](<https://devfeed.tech/tags/ai-platform.md>), [drive](<https://devfeed.tech/tags/drive.md>), [dsx](<https://devfeed.tech/tags/dsx.md>), [groq](<https://devfeed.tech/tags/groq.md>), [groq-3-lpx](<https://devfeed.tech/tags/groq-3-lpx.md>), [inference](<https://devfeed.tech/tags/inference.md>), [inference-performance](<https://devfeed.tech/tags/inference-performance.md>), [latency](<https://devfeed.tech/tags/latency.md>), [low-latency](<https://devfeed.tech/tags/low-latency.md>), [lpx](<https://devfeed.tech/tags/lpx.md>), [nvidia-vera-rubin](<https://devfeed.tech/tags/nvidia-vera-rubin.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [performance](<https://devfeed.tech/tags/performance.md>), [power-management](<https://devfeed.tech/tags/power-management.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

This NVIDIA developer article explains how Groq 3 LPX uses deterministic execution across 256 LPU chips to support low-latency inference on NVIDIA Vera Rubin. It describes compiler-scheduled execution and power-management techniques including Preemptive Power and Clock Period Synthesis.

### Source excerpt

Power is a defining constraint for AI factories. As AI workloads demand a full compute platform to serve them, each component of that platform must maximize...

## Nvidia's Groq acquihire is on the DOJ's radar, but it's already too late

DevFeed: [Nvidia's Groq acquihire is on the DOJ's radar, but it's already too late](<https://devfeed.tech/articles/nvidia-s-groq-acquihire-is-on-the-doj-s-radar-but-it-s-already-too-late-8851.md>)

Original publisher: [Read original article](<https://www.theregister.com/systems/2026/09/12/nvidias-groq-acquihire-is-on-the-dojs-radar-but-its-already-too-late/5295986>)

Author: Tobias Mann

Published: 2026-09-12T13:26:00Z

Content type: news

Language: en

Sources: [www.theregister.com - Articles](<https://devfeed.tech/sources/www-theregister-com-articles.md>)

Topics: [Nvidia](<https://devfeed.tech/topics/nvidia.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [alternatives](<https://devfeed.tech/tags/alternatives.md>), [datacenter](<https://devfeed.tech/tags/datacenter.md>), [department-of-justice](<https://devfeed.tech/tags/department-of-justice.md>), [groq](<https://devfeed.tech/tags/groq.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [systems](<https://devfeed.tech/tags/systems.md>)

### AI overview

The article reports that Nvidia's $20B Groq acquihire is attracting attention from the US Department of Justice, while arguing that alternatives could replace Groq even if regulators unwind the deal.

### Source excerpt

Even if regulators did somehow unwind the $20B deal, there's a growing list of alternatives ready to take Groq's place, no merger required

## With Groq 3 LPX in Full Production, NVIDIA Extends Vera Rubin Inference for Agents

DevFeed: [With Groq 3 LPX in Full Production, NVIDIA Extends Vera Rubin Inference for Agents](<https://devfeed.tech/articles/with-groq-3-lpx-in-full-production-nvidia-extends-vera-rubin-inference-for-agents-6963.md>)

Original publisher: [Read original article](<https://blogs.nvidia.com/blog/vera-rubin-lpx-spectrum-x-nvlink-fusion/>)

Author: NVIDIA Writers

Published: 2026-08-24T15:00:41Z

Content type: news

Language: en

Sources: [NVIDIA Blog](<https://devfeed.tech/sources/nvidia-blog.md>)

Topics: [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [Low-Latency Inference](<https://devfeed.tech/topics/low-latency-inference.md>), [networking](<https://devfeed.tech/topics/networking.md>), [gemma4](<https://devfeed.tech/topics/gemma4.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [bluefi](<https://devfeed.tech/tags/bluefi.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cpx](<https://devfeed.tech/tags/cpx.md>), [groq](<https://devfeed.tech/tags/groq.md>), [groq-3-lpx](<https://devfeed.tech/tags/groq-3-lpx.md>), [inference](<https://devfeed.tech/tags/inference.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [latency](<https://devfeed.tech/tags/latency.md>), [long-context](<https://devfeed.tech/tags/long-context.md>), [low-latency-inference](<https://devfeed.tech/tags/low-latency-inference.md>), [lpx](<https://devfeed.tech/tags/lpx.md>), [networking](<https://devfeed.tech/tags/networking.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-spectrum-x-ethernet](<https://devfeed.tech/tags/nvidia-spectrum-x-ethernet.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [nvidia-vera-rubin](<https://devfeed.tech/tags/nvidia-vera-rubin.md>), [nvl72](<https://devfeed.tech/tags/nvl72.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [vera-cpu](<https://devfeed.tech/tags/vera-cpu.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>)

### AI overview

NVIDIA announces Groq 3 LPX production availability alongside Vera Rubin NVL72, positioning the integrated compute, networking, and inference stack for long-context, agentic AI workloads. The article highlights a benchmark result of 3,400 output tokens per second on Gemma 4 31B and describes partner adoption of Vera Rubin, Spectrum-X Multiplane, and Groq 3 LPX.

### Source excerpt

The next era of AI inference won't be defined by a single breakthrough chip, network or system. It'll be defined by how every layer of the AI factory works together. That's why NVIDIA is extending Vera Rubin NVL72 with fast token generation for agentic systems. Announced today, the NVIDIA Vera Rubin rack-scale system NVIDIA Groq [...]

## How NVIDIA Groq 3 LPX Unlocks Ultrafast Interactivity at Long Context on NVIDIA Vera Rubin

DevFeed: [How NVIDIA Groq 3 LPX Unlocks Ultrafast Interactivity at Long Context on NVIDIA Vera Rubin](<https://devfeed.tech/articles/how-nvidia-groq-3-lpx-unlocks-ultrafast-interactivity-at-long-context-on-nvidia-vera-rubin-6843.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/how-nvidia-groq-3-lpx-unlocks-ultrafast-interactivity-at-long-context-on-nvidia-vera-rubin/>)

Author: Tanya Lenz

Published: 2026-08-24T15:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [d-matrix](<https://devfeed.tech/topics/d-matrix.md>), [Vera Rubin](<https://devfeed.tech/topics/vera-rubin.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [gemma4](<https://devfeed.tech/topics/gemma4.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Cache](<https://devfeed.tech/topics/cache.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-factory](<https://devfeed.tech/tags/ai-factory.md>), [ai-inference](<https://devfeed.tech/tags/ai-inference.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [cache](<https://devfeed.tech/tags/cache.md>), [collective](<https://devfeed.tech/tags/collective.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [developer-tools-techniques](<https://devfeed.tech/tags/developer-tools-techniques.md>), [groq](<https://devfeed.tech/tags/groq.md>), [groq-3-lpx](<https://devfeed.tech/tags/groq-3-lpx.md>), [inference-performance](<https://devfeed.tech/tags/inference-performance.md>), [long-context](<https://devfeed.tech/tags/long-context.md>), [low-latency-inference](<https://devfeed.tech/tags/low-latency-inference.md>), [lpx](<https://devfeed.tech/tags/lpx.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-vera](<https://devfeed.tech/tags/nvidia-vera.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rubin-gpu](<https://devfeed.tech/tags/rubin-gpu.md>), [speed](<https://devfeed.tech/tags/speed.md>), [systems](<https://devfeed.tech/tags/systems.md>), [tokens](<https://devfeed.tech/tags/tokens.md>), [training-ai-models](<https://devfeed.tech/tags/training-ai-models.md>), [vera-rubin](<https://devfeed.tech/tags/vera-rubin.md>), [vera-rubin-nvl72](<https://devfeed.tech/tags/vera-rubin-nvl72.md>)

### AI overview

NVIDIA Groq 3 LPX, paired with Vera Rubin NVL72, delivers high-interactivity AI inference for long-context workloads. A reported benchmark measured 3,431 output tokens per second on Gemma 4 31B with a 100K context.

### Source excerpt

NVIDIA Groq 3 LPX is the interactive AI inference accelerator for the NVIDIA Vera Rubin platform. At the core of the platform is NVIDIA Vera Rubin NVL72, the...

## Upcoming Livestream: GPUs for AI (Shaped by You)

DevFeed: [Upcoming Livestream: GPUs for AI (Shaped by You)](<https://devfeed.tech/articles/upcoming-livestream-gpus-for-ai-shaped-by-you-35026.md>)

Original publisher: [Read original article](<https://read.theaimerge.com/p/upcoming-livestream-gpus-for-ai-shaped>)

Author: Alex Razvant

Published: 2026-01-27T09:30:49Z

Content type: article

Language: en

Sources: [Neural Bits](<https://devfeed.tech/sources/neural-bits.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Hardware](<https://devfeed.tech/topics/hardware.md>), [CUDA](<https://devfeed.tech/topics/cuda.md>), [pcie](<https://devfeed.tech/topics/pcie.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [rocm](<https://devfeed.tech/topics/rocm.md>), [MLX](<https://devfeed.tech/topics/mlx.md>), [TensorRT](<https://devfeed.tech/topics/tensorrt.md>), [Google](<https://devfeed.tech/topics/google.md>), [groq](<https://devfeed.tech/topics/groq.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [google](<https://devfeed.tech/tags/google.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [groq](<https://devfeed.tech/tags/groq.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [mlx](<https://devfeed.tech/tags/mlx.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [pcie](<https://devfeed.tech/tags/pcie.md>), [rocm](<https://devfeed.tech/tags/rocm.md>), [tensorrt](<https://devfeed.tech/tags/tensorrt.md>)

### AI overview

An upcoming livestream will discuss how GPUs and other accelerators support AI workloads. The author invites audience feedback to shape coverage of GPU hardware, PCIe, CUDA, ASICs, TPUs, LPUs, model optimization, and related technologies.

### Source excerpt

You can choose the topics for a Live Session on GPUs in AI

## Groq on Hugging Face Inference Providers 🔥

DevFeed: [Groq on Hugging Face Inference Providers 🔥](<https://devfeed.tech/articles/groq-on-hugging-face-inference-providers-7281.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/inference-providers-groq>)

Author: Ben Ankiel; Hatice Ozen; Célina Hanouti; Lucain Pouget; Simon Brandeis

Published: 2025-06-16T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [groq](<https://devfeed.tech/topics/groq.md>), [inference-providers](<https://devfeed.tech/topics/inference-providers.md>), [hugging face](<https://devfeed.tech/topics/hugging-face.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [SDKs](<https://devfeed.tech/topics/sdks.md>), [API](<https://devfeed.tech/topics/api.md>)

Tags: [api](<https://devfeed.tech/tags/api.md>), [api-keys](<https://devfeed.tech/tags/api-keys.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [enterprise](<https://devfeed.tech/tags/enterprise.md>), [groq](<https://devfeed.tech/tags/groq.md>), [hub](<https://devfeed.tech/tags/hub.md>), [hugging-face](<https://devfeed.tech/tags/hugging-face.md>), [inference](<https://devfeed.tech/tags/inference.md>), [inference-providers](<https://devfeed.tech/tags/inference-providers.md>), [large-language-models-llms](<https://devfeed.tech/tags/large-language-models-llms.md>), [latency](<https://devfeed.tech/tags/latency.md>), [llms](<https://devfeed.tech/tags/llms.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [partnerships](<https://devfeed.tech/tags/partnerships.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [sdks](<https://devfeed.tech/tags/sdks.md>)

### AI overview

Groq is now available as an Inference Provider on the Hugging Face Hub, including model pages and Hugging Face client SDKs for JavaScript and Python. The article describes Groq's LPU technology, its low-latency and high-throughput inference for LLMs, support for open models such as Meta's Llama 4 and Qwen's QWQ-32B, API access, and custom-key or Hugging Face-routed usage options.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Mistral: Are LLMs Commodities Now?

DevFeed: [Mistral: Are LLMs Commodities Now?](<https://devfeed.tech/articles/mistral-are-llms-commodities-now-33433.md>)

Original publisher: [Read original article](<https://timkellogg.me/blog/2024/07/24/mistral>)

Published: 2024-07-24T09:00:00Z

Content type: opinion

Language: en

Sources: [Tim Kellogg](<https://devfeed.tech/sources/tim-kellogg.md>)

Topics: [LLMs](<https://devfeed.tech/topics/llms.md>), [AI Strategy](<https://devfeed.tech/topics/ai-strategy.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>), [anthropic](<https://devfeed.tech/topics/anthropic.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [Google](<https://devfeed.tech/topics/google.md>), [bedrock](<https://devfeed.tech/topics/bedrock.md>), [groq](<https://devfeed.tech/topics/groq.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>), [Latency](<https://devfeed.tech/topics/latency.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-strategy](<https://devfeed.tech/tags/ai-strategy.md>), [anthropic](<https://devfeed.tech/tags/anthropic.md>), [api](<https://devfeed.tech/tags/api.md>), [availability](<https://devfeed.tech/tags/availability.md>), [aws](<https://devfeed.tech/tags/aws.md>), [bedrock](<https://devfeed.tech/tags/bedrock.md>), [chatgpt](<https://devfeed.tech/tags/chatgpt.md>), [claude](<https://devfeed.tech/tags/claude.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [data](<https://devfeed.tech/tags/data.md>), [google](<https://devfeed.tech/tags/google.md>), [google-cloud](<https://devfeed.tech/tags/google-cloud.md>), [gpt](<https://devfeed.tech/tags/gpt.md>), [groq](<https://devfeed.tech/tags/groq.md>), [latency](<https://devfeed.tech/tags/latency.md>), [llama](<https://devfeed.tech/tags/llama.md>), [llms](<https://devfeed.tech/tags/llms.md>), [mistral](<https://devfeed.tech/tags/mistral.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>)

### AI overview

This opinion argues that the growing number of capable frontier language models, including Mistral 2 Large, GPT-4o, Llama 3.1, and Claude Sonnet 3.5, makes model selection increasingly resemble a commodity decision. It recommends evaluating cost, availability, and operator trustworthiness, and favors infrastructure providers that do not also train models.

### Source excerpt

Mistral 2 Large is out, and it's right up there with GPT-4o, ...and Llama 3.1, and Claude Sonnet 3.5, and...yeah, there's a lot of them. These "Frontier Models" are starting to look more like commodities. And with that shift, we need to adjust AI strategy to match. There's strong arguments to make for using an operator that doesn't also train models. Read more!