Phi-4 hits 91.2% on GSM8K, top of the 3-4B class on math.
An NPU runs Phi-4 at 30-35 t/s on 3-5W vs 15-20W on CPU.
https://botmonster.com/ai/why-small-language-models-are-better-for-edge-devices/?utm_source=bluesky&utm_medium=social #LocalLLM
An NPU runs Phi-4 at 30-35 t/s on 3-5W vs 15-20W on CPU.
https://botmonster.com/ai/why-small-language-models-are-better-for-edge-devices/?utm_source=bluesky&utm_medium=social #LocalLLM
November 3, 2026 at 12:20 AM
Phi-4 hits 91.2% on GSM8K, top of the 3-4B class on math.
An NPU runs Phi-4 at 30-35 t/s on 3-5W vs 15-20W on CPU.
https://botmonster.com/ai/why-small-language-models-are-better-for-edge-devices/?utm_source=bluesky&utm_medium=social #LocalLLM
An NPU runs Phi-4 at 30-35 t/s on 3-5W vs 15-20W on CPU.
https://botmonster.com/ai/why-small-language-models-are-better-for-edge-devices/?utm_source=bluesky&utm_medium=social #LocalLLM
Redditで出てた
Gamma5 could be interesting with Japanese translation : r/LocalLLM: https://www.reddit.com/r/LocalLLM/comments/1xjfo6c/gamma5_could_be_interesting_with_japanese/
Gamma5 could be interesting with Japanese translation : r/LocalLLM: https://www.reddit.com/r/LocalLLM/comments/1xjfo6c/gamma5_could_be_interesting_with_japanese/
November 2, 2026 at 11:55 PM
Redditで出てた
Gamma5 could be interesting with Japanese translation : r/LocalLLM: https://www.reddit.com/r/LocalLLM/comments/1xjfo6c/gamma5_could_be_interesting_with_japanese/
Gamma5 could be interesting with Japanese translation : r/LocalLLM: https://www.reddit.com/r/LocalLLM/comments/1xjfo6c/gamma5_could_be_interesting_with_japanese/
Are you tired of relying on cloud-based services to run your own voice assistants and agents?
▶️ https://plastikelectrik.xyz/go/x9AZT8Q
📘 Create Your Own AI Agents With OLLAMA & MCP: https://plastikelectrik.xyz/go/3yNz9HM
#Ollama #LocalLLM
▶️ https://plastikelectrik.xyz/go/x9AZT8Q
📘 Create Your Own AI Agents With OLLAMA & MCP: https://plastikelectrik.xyz/go/3yNz9HM
#Ollama #LocalLLM
November 2, 2026 at 11:47 PM
Are you tired of relying on cloud-based services to run your own voice assistants and agents?
▶️ https://plastikelectrik.xyz/go/x9AZT8Q
📘 Create Your Own AI Agents With OLLAMA & MCP: https://plastikelectrik.xyz/go/3yNz9HM
#Ollama #LocalLLM
▶️ https://plastikelectrik.xyz/go/x9AZT8Q
📘 Create Your Own AI Agents With OLLAMA & MCP: https://plastikelectrik.xyz/go/3yNz9HM
#Ollama #LocalLLM
Extract entities, translate text, analyze sentiment, or search the web—all using simple AI formulas inside (Un)Perplexed Spready! 🛠️🌍 🔗 matasoft.hr/qtrendcontro...
#NLP #TextAnalysis #Software #GenAI #FutureTech #AISpreadsheet #AIFunctions #SpreadsheetSoftware #DataEnrichment #WebScraping #LocalLLM
#NLP #TextAnalysis #Software #GenAI #FutureTech #AISpreadsheet #AIFunctions #SpreadsheetSoftware #DataEnrichment #WebScraping #LocalLLM
Download (Un)Perplexed Spready or Try Online
(Un)Perplexed Spready is a spreadsheet software that thinks! It combines familiar spreadsheet power with revolutionary AI models for effortless data analysis and smart insights. Use AI-powered formulas to unlock insights beyond the reach of Excel. Unleash Artificial Intelligence in your spreadsheets! Drink you coffee, while the AI is doing hard job for you! You can now try it online for free!
matasoft.hr
November 2, 2026 at 10:22 PM
Extract entities, translate text, analyze sentiment, or search the web—all using simple AI formulas inside (Un)Perplexed Spready! 🛠️🌍 🔗 matasoft.hr/qtrendcontro...
#NLP #TextAnalysis #Software #GenAI #FutureTech #AISpreadsheet #AIFunctions #SpreadsheetSoftware #DataEnrichment #WebScraping #LocalLLM
#NLP #TextAnalysis #Software #GenAI #FutureTech #AISpreadsheet #AIFunctions #SpreadsheetSoftware #DataEnrichment #WebScraping #LocalLLM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 7:36 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 7:21 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
All six boxes share one GB10 chip and one 273 GB/s memory pool, so speed barely separates them. Price, stock, storage and cooling do: Dell.com listed its 128 GB model at $7,967 on Nov. 2, against $6,593 on Oct. 30. #LocalLLM
GB10 Boxes Compared: Similar gpt-oss-120b Speed, Prices $4,759 to $7,967
StorageReview's separate vLLM reviews put six NVIDIA GB10 boxes close together on gpt-oss-120b. Listed US prices run $4,759 to $7,967 across configurations and dates.
voltgridnews.com
November 2, 2026 at 7:14 PM
All six boxes share one GB10 chip and one 273 GB/s memory pool, so speed barely separates them. Price, stock, storage and cooling do: Dell.com listed its 128 GB model at $7,967 on Nov. 2, against $6,593 on Oct. 30. #LocalLLM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 7:05 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:55 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:48 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:44 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:40 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:36 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:33 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:30 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:27 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:23 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:20 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:17 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:14 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Making Local LLMs Usable on 8GB GPUs
hackernoon.com
November 2, 2026 at 6:11 PM
Learn how to optimize local LLM inference on 8GB GPUs using KV-cache quantization, Flash Attention, batching, and practical latency benchmarks. #localllm
Both boxes use NVIDIA's GB10 with 128 GB of memory, and StorageReview measured 649.62 tokens per second on gpt-oss-120b at batch 64. At CDW's Nov. 2 price, Gigabyte's version now costs more than the DGX Spark. #LocalLLM
Gigabyte AI TOP ATOM Review: $7,312 at CDW, Up From $3,999.99 at Launch
CDW advertises Gigabyte's 4TB GB10 box at $7,312, 83% above launch and above NVIDIA's DGX Spark. StorageReview's vLLM runs and ServeTheHome's power data show what that buys.
voltgridnews.com
November 2, 2026 at 5:26 PM
Both boxes use NVIDIA's GB10 with 128 GB of memory, and StorageReview measured 649.62 tokens per second on gpt-oss-120b at batch 64. At CDW's Nov. 2 price, Gigabyte's version now costs more than the DGX Spark. #LocalLLM
Sam Altman says it's ""quite terrible"" that ordinary people keep DRAM in their own computers, ""being used 5% of the time."" He'd rather it all sat in the cloud he sells.
He's wrong on all accounts. Just a ""quite terrible"" and ""wasteful"" human being.
#ai #localllm #hardware
He's wrong on all accounts. Just a ""quite terrible"" and ""wasteful"" human being.
#ai #localllm #hardware
November 2, 2026 at 5:12 PM
The change is memory capacity, not speed. GMKtec says up to 160 GB of the EVO-X5 Pro's pool can go to the GPU, against a 96 GB limit on the Ryzen AI Max+ 395. Bandwidth rises about 6.6%, Voltgrid's arithmetic. #LocalLLM
GMKtec EVO-X5 Pro: 192GB at $6,799, or $35.41 per GB with 2TB
GMKtec's EVO-X5 Pro, built on AMD's Ryzen AI Max+ PRO 495, lists 192 GB at $6,799 with 2 TB: 50% more memory than a DGX Spark at the same 273 GB/s, and a 94% price premium over the 128 GB, 1 TB EVO-X2.
voltgridnews.com
November 2, 2026 at 4:46 PM
The change is memory capacity, not speed. GMKtec says up to 160 GB of the EVO-X5 Pro's pool can go to the GPU, against a 96 GB limit on the Ryzen AI Max+ 395. Bandwidth rises about 6.6%, Voltgrid's arithmetic. #LocalLLM