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Qwen3.8 Flash on a single DGX Spark. Smooth experience!

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Mia

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17,880 görüntüleme • 3 gün önce •via X (Twitter)

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First impression of how fast the new Qwen3.8-Flash-Next runs on a single DGX Spark. 180B params, 262k context, all local.
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First impression of how fast the new Qwen3.8-Flash-Next runs on a single DGX Spark. 180B params, 262k context, all local.

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DeepSeek-V4-Flash-Spark and Spark-Mini were born today. 1 command setup to Pi / vllm-studio / docker deployment. All this is running local on a single DGX Spark.
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0xSero

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Qwen3.8-Flash-Next (176B, NVFP4, 2× DGX Spark): 40,265 thinking tokens, 21,091 answer. Qwen3.8-27B on the same prompt: 42,988 thinking, 6,040 answer. Same question, same deliberation, 3.5× the output. 55 min vs 37 min. The 176B shipped a genuine leapfrog wave equation on a 512² lattice with reflections and interference. The 27B shipped a solid ripple tank. Both run 60fps in a single HTML file Generated on DGX Sparks on my desk.
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Qwen3.8-Flash-Next (176B, NVFP4, 2× DGX Spark): 40,265 thinking tokens, 21,091 answer. Qwen3.8-27B on the same prompt: 42,988 thinking, 6,040 answer. Same question, same deliberation, 3.5× the output. 55 min vs 37 min. The 176B shipped a genuine leapfrog wave equation on a 512² lattice with reflections and interference. The 27B shipped a solid ripple tank. Both run 60fps in a single HTML file Generated on DGX Sparks on my desk.

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Qwen3.8-27B is insane at browser use. Running on a DGX Spark, sped up 3x. The Qwen bros were right....!
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Qwen3.8-27B is insane at browser use. Running on a DGX Spark, sped up 3x. The Qwen bros were right....!

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DeepSeek v4 Flash in one DGX Spark in action
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Qwen3.8 Max UD-Q1_0 4× DGX Spark + llama.cpp/MTP3 53,448 tokens · 1h54m44s · 7.76 tok/s NVIDIA AI Qwen Qwen Developers

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Watch Gemma-4-26B running 18 concurrent sessions on a single NVIDIA AI DGX Spark — delivering a cumulative 300 tokens per second. 🔥
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Watch Gemma-4-26B running 18 concurrent sessions on a single NVIDIA AI DGX Spark — delivering a cumulative 300 tokens per second. 🔥

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found an amazing deal on the DGX Spark
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DGX Spark giveaway.

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Videos of Hermes Desktop using 2 x DGX Spark with: - GLM 5.3 Flash EXL3 - Qwen 3.8 Flash Next - DeepSeek V4 0731 Flash All powered by Mia recipes and her sparkDash!
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Jensen Huang hand-delivers the new NVIDIA DGX Spark to Elon Musk at Starbase 2016: Jensen hand-delivered the first DGX-1 to Elon at OpenAI Now: Nearly a decade later, he’s delivering the next generation at Starbase • DGX-1 (2016): 3,000 Watts • DGX Spark (2025): 40 Watts
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Jensen Huang hand-delivers the new NVIDIA DGX Spark to Elon Musk at Starbase 2016: Jensen hand-delivered the first DGX-1 to Elon at OpenAI Now: Nearly a decade later, he’s delivering the next generation at Starbase • DGX-1 (2016): 3,000 Watts • DGX Spark (2025): 40 Watts

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It's been an amazing week for open models running on NVIDIA Local AI systems! 👀 Here's a few you’ll want to know about, all ready to run locally on NVIDIA RTX, DGX Spark, DGX Station, and Jetson.
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It's been an amazing week for open models running on NVIDIA Local AI systems! 👀 Here's a few you’ll want to know about, all ready to run locally on NVIDIA RTX, DGX Spark, DGX Station, and Jetson.

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This afternoon I picked up a new Nvidia DGX Spark computer with the goal of trying to run Gemma 4 31b (4bit) on it locally as a server. Just 1.5 hours later, it’s working! Using Open WebUI on my MacBook as the interface and it’s connecting to my DGX Spark running as a Gemma 4 server.
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This afternoon I picked up a new Nvidia DGX Spark computer with the goal of trying to run Gemma 4 31b (4bit) on it locally as a server. Just 1.5 hours later, it’s working! Using Open WebUI on my MacBook as the interface and it’s connecting to my DGX Spark running as a Gemma 4 server.

Dave Lee

140,419 görüntüleme • 5 ay önce

I'm really really impressed with Qwen3.8-Flash-Next😍 It is better than Qwen3.8-27B !! Below is a screen-recording from a Three.js FPS game made by Qwen3.8-Flash-Next running on my 3090. Everything here is generated at runtime: textures, sounds, music, models and the rigid-body solver. No image, audio or mesh files are downloaded. three.js is loaded from a CDN. atomic.chat Qwen3.8-Flash-Next IQ4_XS👌 DeepSeek Harness 👌 Single RTX 3090 + 64GB RAM (Total 88 GB) Stats: - ~ 10 - 11 hrs in total - 22M tokens, 94% cache - Avg decode 20t/s - Avg prefill 200t/s - TTFT avg 9.6s It is slow, but faster than Unsloth IQ3_XXS !
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I'm really really impressed with Qwen3.8-Flash-Next😍 It is better than Qwen3.8-27B !! Below is a screen-recording from a Three.js FPS game made by Qwen3.8-Flash-Next running on my 3090. Everything here is generated at runtime: textures, sounds, music, models and the rigid-body solver. No image, audio or mesh files are downloaded. three.js is loaded from a CDN. atomic.chat Qwen3.8-Flash-Next IQ4_XS👌 DeepSeek Harness 👌 Single RTX 3090 + 64GB RAM (Total 88 GB) Stats: - ~ 10 - 11 hrs in total - 22M tokens, 94% cache - Avg decode 20t/s - Avg prefill 200t/s - TTFT avg 9.6s It is slow, but faster than Unsloth IQ3_XXS !

AJ

18,608 görüntüleme • 10 gün önce

dgx spark por $5.5K dólares no país do lado
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dgx spark por $5.5K dólares no país do lado

#bolhadev

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Step-3.7-Flash Q4_K_S on DGX Spark (GB10, 128GB): > ~27 tok/s generation > 198B sparse MoE, ~11B active > 256K context, native vision > Agentic / tool-calling / reasoning > Apache 2.0 I added a mobile chat screen on the right showing what 27 tok/s actually feels like streaming on a phone.
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Step-3.7-Flash Q4_K_S on DGX Spark (GB10, 128GB): > ~27 tok/s generation > 198B sparse MoE, ~11B active > 256K context, native vision > Agentic / tool-calling / reasoning > Apache 2.0 I added a mobile chat screen on the right showing what 27 tok/s actually feels like streaming on a phone.

stevibe

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When NVIDIA CEO Jensen Huang presented the DGX Spark, then he recalled how, back in 2016, he unveiled the world’s first AI supercomputer, the DGX-1, and how Elon Musk, then at OpenAI, became its first customer. The DGX Spark is far more advanced, delivering five times the computational power of the DGX-1.
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When NVIDIA CEO Jensen Huang presented the DGX Spark, then he recalled how, back in 2016, he unveiled the world’s first AI supercomputer, the DGX-1, and how Elon Musk, then at OpenAI, became its first customer. The DGX Spark is far more advanced, delivering five times the computational power of the DGX-1.

SMX 🇺🇸

13,315,732 görüntüleme • 9 ay önce

From rockets to AI. Nine years after the original NVIDIA DGX-1 handoff, Jensen Huang delivered a brand-new DGX Spark to Elon Musk at Starbase. 🚀✨ The DGX Spark is a petaflop powerhouse built for creators, researchers, and developers — a desktop-sized supercomputer with five times the performance of the first DGX-1. Filmed at SpaceX’s rocket factory in Texas, this moment captures a conversation between the two visionariesI. ➡️ 📹 #SparkSomethingBig
1:12

From rockets to AI. Nine years after the original NVIDIA DGX-1 handoff, Jensen Huang delivered a brand-new DGX Spark to Elon Musk at Starbase. 🚀✨ The DGX Spark is a petaflop powerhouse built for creators, researchers, and developers — a desktop-sized supercomputer with five times the performance of the first DGX-1. Filmed at SpaceX’s rocket factory in Texas, this moment captures a conversation between the two visionariesI. ➡️ 📹 #SparkSomethingBig

NVIDIA

3,159,905 görüntüleme • 10 ay önce