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Victor M

@victormustar • 29,892 subscribers

🤗 Head of Product @huggingface

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Fable has done AGI-level job on on the Boeing 747 benchmark... it's almost scary 👀

Fable has done AGI-level job on on the Boeing 747 benchmark... it's almost scary 👀

2,613,276 views

Finally spent 45 minutes with Grok 3 👀 Impression so far: it's the best code model I've ever used. I kept throwing random ideas at it and it grew the project to 400 lines almost error-free.

Finally spent 45 minutes with Grok 3 👀 Impression so far: it's the best code model I've ever used. I kept throwing random ideas at it and it grew the project to 400 lines almost error-free.

6,635,093 views

Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality: 🧠 LLMs → NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE, only 55B active, 1M context, MMLU 89.1. NVFP4 variant claims ~5x throughput on Blackwell. First openly-weighted 550B hybrid Mamba-Transformer, closing the gap with frontier closed models. → Google Gemma 4 12B: fully open dense any-to-any (text/image/audio/video), 256k context, encoder-free, 140+ languages, AIME 2026 at 77.5. Shipped with a 23-checkpoint QAT wave (mobile ONNX + MLX). Most deployable model of the week. → StepFun Step-3.7-Flash: 198B sparse MoE VLM, ~11B active, SWE-Bench PRO 56.3. Apache 2.0. → Liquid AI LFM2.5-8B-A1B: edge MoE, just 1.5B active, 128k ctx, MATH500 88.8, MLX-ready. Best on-device option this week. → JetBrains Mellum2-12B-A2.5B-Thinking: their first open MoE, near-Qwen3-14B coding at 2.5B active. Apache 2.0. 🎨 Image gen (the surprise of the week) → Ideogram 4: their FIRST-EVER open weights. 9.3B flow-matching DiT trained from scratch. #2 overall behind GPT Image 2, top open-weight model on Design Arena + LMArena. Strongest open checkpoint for text-rich images, full stop. It has taste. Still can't believe this is open weights. 🔊 Audio & Speech (a breakout week for open TTS, 4 labs shipped) → Boson Higgs Audio v3 4B: 102 languages, 21 emotions, singing/whispering/shouting, sub-second TTFA. → RedNote dots.tts: the only fully continuous (no codec) open TTS pipeline, Apache 2.0. → Google Magenta RealTime 2: real-time music gen, <200ms latency, text+audio+MIDI. multimodalart ported it to PyTorch within hours with live ZeroGPU demos. → NVIDIA Nemotron-3.5 ASR: 600M streaming, 17x more concurrent streams vs Parakeet RNNT 1.1B. 👁️ Vision & VLMs → PaddleOCR-VL-1.6: SOTA document parsing at 1B params, Apache 2.0. → Baidu NAVA: 6.3B joint audio-video gen, best-in-class A/V sync, Apache 2.0. 🎬 Video, 3D & World Models → NVIDIA Cosmos3-Super: 64B omnimodal world model coupling action trajectories with video+audio gen, for Physical AI. → JD JoyAI-Echo: up to 5-min multi-shot text-to-video on LTX-2.3. → ByteDance Bernini-R + VAST TripoSplat (single-image-to-3D Gaussian splats, MIT).

Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality: 🧠 LLMs → NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE, only 55B active, 1M context, MMLU 89.1. NVFP4 variant claims ~5x throughput on Blackwell. First openly-weighted 550B hybrid Mamba-Transformer, closing the gap with frontier closed models. → Google Gemma 4 12B: fully open dense any-to-any (text/image/audio/video), 256k context, encoder-free, 140+ languages, AIME 2026 at 77.5. Shipped with a 23-checkpoint QAT wave (mobile ONNX + MLX). Most deployable model of the week. → StepFun Step-3.7-Flash: 198B sparse MoE VLM, ~11B active, SWE-Bench PRO 56.3. Apache 2.0. → Liquid AI LFM2.5-8B-A1B: edge MoE, just 1.5B active, 128k ctx, MATH500 88.8, MLX-ready. Best on-device option this week. → JetBrains Mellum2-12B-A2.5B-Thinking: their first open MoE, near-Qwen3-14B coding at 2.5B active. Apache 2.0. 🎨 Image gen (the surprise of the week) → Ideogram 4: their FIRST-EVER open weights. 9.3B flow-matching DiT trained from scratch. #2 overall behind GPT Image 2, top open-weight model on Design Arena + LMArena. Strongest open checkpoint for text-rich images, full stop. It has taste. Still can't believe this is open weights. 🔊 Audio & Speech (a breakout week for open TTS, 4 labs shipped) → Boson Higgs Audio v3 4B: 102 languages, 21 emotions, singing/whispering/shouting, sub-second TTFA. → RedNote dots.tts: the only fully continuous (no codec) open TTS pipeline, Apache 2.0. → Google Magenta RealTime 2: real-time music gen, <200ms latency, text+audio+MIDI. multimodalart ported it to PyTorch within hours with live ZeroGPU demos. → NVIDIA Nemotron-3.5 ASR: 600M streaming, 17x more concurrent streams vs Parakeet RNNT 1.1B. 👁️ Vision & VLMs → PaddleOCR-VL-1.6: SOTA document parsing at 1B params, Apache 2.0. → Baidu NAVA: 6.3B joint audio-video gen, best-in-class A/V sync, Apache 2.0. 🎬 Video, 3D & World Models → NVIDIA Cosmos3-Super: 64B omnimodal world model coupling action trajectories with video+audio gen, for Physical AI. → JD JoyAI-Echo: up to 5-min multi-shot text-to-video on LTX-2.3. → ByteDance Bernini-R + VAST TripoSplat (single-image-to-3D Gaussian splats, MIT).

541,566 views

Funny how you can do the same thing with a local model without sending all your data to a remote cloud.

Funny how you can do the same thing with a local model without sending all your data to a remote cloud.

1,196,733 views

some genius invented a kebab benchmark for llms

some genius invented a kebab benchmark for llms

319,120 views

NVIDIA's Kimodo is the release of the week 🔥 Prompt the timeline whatever your want like: "a person walks forward" → "a person starts jumping", hit Generate, and watch a 3D character do it in seconds (700hrs of pro mocap training. Works on human + robot skeletons. Super fast + free to use on HF)

NVIDIA's Kimodo is the release of the week 🔥 Prompt the timeline whatever your want like: "a person walks forward" → "a person starts jumping", hit Generate, and watch a 3D character do it in seconds (700hrs of pro mocap training. Works on human + robot skeletons. Super fast + free to use on HF)

420,299 views

I just made my own Star Wars clip using AI (text-to-video)!

I just made my own Star Wars clip using AI (text-to-video)!

3,012,730 views

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B MoE refresh, Terminal-Bench 2.1 jumps 61.8→82.7 over the preview, DeepSWE 7.3→54.4. Closes in on Opus-4.8 on Agents' Last Exam (25.2 vs 25.7). MIT. → Muse-Glimmer-30B, from Meta (they are back!!): their first open agentic model. ~29.6B dense + perception encoder, 131k+ context, built to run fully local, no cloud. Apache 2.0. → Liquid AI LFM2.5-2.6B: 2.69B params, 131k context, 220 tok/s on an M5 Max in under 2.5GB RAM. Competitive with models 4x larger on agentic tasks. → inclusionAI Ling-3.0-flash: 124B total, only 5.1B active, ~12% the size of their old 1T flagship Ring-2.6, matches it on key benchmarks. MIT. → inclusionAI Ling-3.0-tiny: 7.9B total, 1.3B active, 86-90 tok/s on an M4 Pro MacBook at ~8GB peak memory. MIT. → NVIDIA Nemotron-3.5-Lightning-30B-A3B: hybrid Mamba-2+MoE+Attention, up to 1M context, runs on a single H100 or DGX Spark, SWE-bench Verified 52.8. → deepgrove maple-preview: 20B-A1B ternary-weight reasoner, 218 tok/s on a Mac mini M4, 5.3GB checkpoint. MIT. → BigBang-v1 (endless-frontier): fine-tuned from Qwen3.6-35B-A3B via a self-evolving generator/critic synthetic-data loop. Lands aggregate performance between DeepSeek V4 Flash (284B) and V4 Pro (1.6T), at 35B. Apache 2.0. 🎬 Video → MiniMax-H3: 33B dense omni model, native stereo audio, up to 2K/15s. 3.6k+ likes already. → Minimax-H3-Turbo (lightx2v): Apache-2.0 turbo distillation of H3 for fast inference. → Lightricks LTX-2.5: image-to-video update, custom Gemma-4-12B text encoder, a markedly stronger distilled model. 🔊 Voice → NVIDIA NemotronLabs VoiceChat-11B: full-duplex speech-to-speech, ~450ms turn-taking, #2 on open VoiceBench, and the first open full-duplex model with live tool-calling mid-conversation. 🛡️ Safety → Mistral Shieldstral-1.0-3B: 3B multimodal guardrail that takes your safety policy as plain text instead of fixed categories. Beats LlamaGuard-4-12B and ShieldGemma-9B on HarmBench (99.4) and ToxicChat (84.1) at a fraction of the size. Apache 2.0.

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B MoE refresh, Terminal-Bench 2.1 jumps 61.8→82.7 over the preview, DeepSWE 7.3→54.4. Closes in on Opus-4.8 on Agents' Last Exam (25.2 vs 25.7). MIT. → Muse-Glimmer-30B, from Meta (they are back!!): their first open agentic model. ~29.6B dense + perception encoder, 131k+ context, built to run fully local, no cloud. Apache 2.0. → Liquid AI LFM2.5-2.6B: 2.69B params, 131k context, 220 tok/s on an M5 Max in under 2.5GB RAM. Competitive with models 4x larger on agentic tasks. → inclusionAI Ling-3.0-flash: 124B total, only 5.1B active, ~12% the size of their old 1T flagship Ring-2.6, matches it on key benchmarks. MIT. → inclusionAI Ling-3.0-tiny: 7.9B total, 1.3B active, 86-90 tok/s on an M4 Pro MacBook at ~8GB peak memory. MIT. → NVIDIA Nemotron-3.5-Lightning-30B-A3B: hybrid Mamba-2+MoE+Attention, up to 1M context, runs on a single H100 or DGX Spark, SWE-bench Verified 52.8. → deepgrove maple-preview: 20B-A1B ternary-weight reasoner, 218 tok/s on a Mac mini M4, 5.3GB checkpoint. MIT. → BigBang-v1 (endless-frontier): fine-tuned from Qwen3.6-35B-A3B via a self-evolving generator/critic synthetic-data loop. Lands aggregate performance between DeepSeek V4 Flash (284B) and V4 Pro (1.6T), at 35B. Apache 2.0. 🎬 Video → MiniMax-H3: 33B dense omni model, native stereo audio, up to 2K/15s. 3.6k+ likes already. → Minimax-H3-Turbo (lightx2v): Apache-2.0 turbo distillation of H3 for fast inference. → Lightricks LTX-2.5: image-to-video update, custom Gemma-4-12B text encoder, a markedly stronger distilled model. 🔊 Voice → NVIDIA NemotronLabs VoiceChat-11B: full-duplex speech-to-speech, ~450ms turn-taking, #2 on open VoiceBench, and the first open full-duplex model with live tool-calling mid-conversation. 🛡️ Safety → Mistral Shieldstral-1.0-3B: 3B multimodal guardrail that takes your safety policy as plain text instead of fixed categories. Beats LlamaGuard-4-12B and ShieldGemma-9B on HarmBench (99.4) and ToxicChat (84.1) at a fraction of the size. Apache 2.0.

54,264 views

Reminder: every Hugging Face Space is an API your agents can call :) I asked mine to build a website about the flowers of France 🌸 and it used VAST AI's TripoSplat Space to turn photos it found into real 3D Gaussian splats, live on the page! All on my HF Pro daily ZeroGPU credits (40 min/day renewed daily for only $9/month)

Reminder: every Hugging Face Space is an API your agents can call :) I asked mine to build a website about the flowers of France 🌸 and it used VAST AI's TripoSplat Space to turn photos it found into real 3D Gaussian splats, live on the page! All on my HF Pro daily ZeroGPU credits (40 min/day renewed daily for only $9/month)

169,501 views

300tok/s on mobile is insane... open source must win ✊

300tok/s on mobile is insane... open source must win ✊

94,242 views

Crazy what you can do on Hugging Face in 40 seconds

Crazy what you can do on Hugging Face in 40 seconds

437,660 views

Why is a 100% open source chatbot faster than ChatGPT "Instant"? 👀

Why is a 100% open source chatbot faster than ChatGPT "Instant"? 👀

234,666 views

Microsoft TRELLIS.2 is here 🔥 • Single image → textured 3D mesh • 4B params, flow-matching transformer • Up to 1536³ resolution • Open weights, MIT licensed ⬇️ Demo available on Hugging Face

Microsoft TRELLIS.2 is here 🔥 • Single image → textured 3D mesh • 4B params, flow-matching transformer • Up to 1536³ resolution • Open weights, MIT licensed ⬇️ Demo available on Hugging Face

194,806 views

another open source win: opencode + GLM 4.6 is basically Claude Code (used it all day) but insanely cheap + better TUI. And you can use it with your Hugging Face token now 🔥

another open source win: opencode + GLM 4.6 is basically Claude Code (used it all day) but insanely cheap + better TUI. And you can use it with your Hugging Face token now 🔥

217,717 views

New Voxtral-4B-TTS is beautiful 💛 it sounds so good that it's whispering at closed models: "your time is over" - Demo available on Hugging Face ⬇️

New Voxtral-4B-TTS is beautiful 💛 it sounds so good that it's whispering at closed models: "your time is over" - Demo available on Hugging Face ⬇️

107,710 views

New Llama.cpp UI is a blessing for the local AI world 🌎 - Blazing fast, beautiful, and private (ofc) - Use 150,000+ GGUF models in a super slick UI - Drop in PDFs, images, or text documents - Branch and edit conversations anytime - Parallel chats and image processing - Math and code rendering - Constrained generation with JSON schema supported Easy setup + open-source + community-built 🔥

New Llama.cpp UI is a blessing for the local AI world 🌎 - Blazing fast, beautiful, and private (ofc) - Use 150,000+ GGUF models in a super slick UI - Drop in PDFs, images, or text documents - Branch and edit conversations anytime - Parallel chats and image processing - Math and code rendering - Constrained generation with JSON schema supported Easy setup + open-source + community-built 🔥

161,368 views

Mac owners don't miss this: MLX LM is now integrated directly within Hugging Face 🤯 ⬇️ Run 4,400+ LLMs locally on Apple Silicon at max speed, no cloud, no wait.

Mac owners don't miss this: MLX LM is now integrated directly within Hugging Face 🤯 ⬇️ Run 4,400+ LLMs locally on Apple Silicon at max speed, no cloud, no wait.

204,678 views

Making an AI Genie that checks what I'm doing, he's roasting me hard 😭😭

Making an AI Genie that checks what I'm doing, he's roasting me hard 😭😭

346,643 views

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Having so much fun with MinMax-H3. Cannot believe we now have this video quality 100% locally 🚀
0:52
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Having so much fun with MinMax-H3. Cannot believe we now have this video quality 100% locally 🚀

Victor M

248,168 views • 29 days ago

Xiaomi-Robotics-1 just dropped on Hugging Face 🔥 A robot foundation model trained on 100,000 hours of real-world manipulation. They turned it loose in a real apartment: folding laundry, loading the washer, doing the dishes, packing a suitcase. Fully autonomous.
0:28
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Xiaomi-Robotics-1 just dropped on Hugging Face 🔥 A robot foundation model trained on 100,000 hours of real-world manipulation. They turned it loose in a real apartment: folding laundry, loading the washer, doing the dishes, packing a suitcase. Fully autonomous.

Victor M

130,537 views • 1 month ago

llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s → 45 tok/s (+78%). Two flags on llama-server: --spec-type draft-mtp --spec-draft-n-max 2
0:38
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llama.cpp with MTP support makes local models fast enough to use as daily drivers 🚀 Qwen3.6-27B dense generation (on A10G): From 25 tok/s → 45 tok/s (+78%). Two flags on llama-server: --spec-type draft-mtp --spec-draft-n-max 2

Victor M

171,948 views • 3 months ago

GLM-5.1 > Claude Code (Opus 4.6)? I'm tripping or CC has become very bad but built a Three.js racing game to eval and it's extremely impressive. Thoughts: - One-shot car physics with real drift mechanics (this is hard) - My fav part: Awesome at self iterating (with no vision!) created 20+ Bun.WebView debugging tools to drive the car programmatically and read game state. Proved a winding bug with vector math without ever seeing the screen - 531-line racing AI in a single write: 4 personalities, curvature map, racing lines, tactical drifting. Built telemetry tools to compare player vs AI speed curves and data-tuned parameters - All assets from scratch: 3D models, procedural textures, sky shader, engine sounds, spatial AI audio! - Can do hard math: proved road normals pointed DOWN via vector cross products, computed track curvature normalized by arc length to tune AI cornering speed You are going to hear about this model a lot in the next months - open source let's go 🚀🚀
0:25
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GLM-5.1 > Claude Code (Opus 4.6)? I'm tripping or CC has become very bad but built a Three.js racing game to eval and it's extremely impressive. Thoughts: - One-shot car physics with real drift mechanics (this is hard) - My fav part: Awesome at self iterating (with no vision!) created 20+ Bun.WebView debugging tools to drive the car programmatically and read game state. Proved a winding bug with vector math without ever seeing the screen - 531-line racing AI in a single write: 4 personalities, curvature map, racing lines, tactical drifting. Built telemetry tools to compare player vs AI speed curves and data-tuned parameters - All assets from scratch: 3D models, procedural textures, sky shader, engine sounds, spatial AI audio! - Can do hard math: proved road normals pointed DOWN via vector cross products, computed track curvature normalized by arc length to tune AI cornering speed You are going to hear about this model a lot in the next months - open source let's go 🚀🚀

Victor M

202,410 views • 4 months ago

LTX-2 trainer is a huge deal. I tried it to add water to the podracers scene using their demo water-sim fine-tune (it's a fine-tune whose only goal is to add water :D) I think we're going to see film productions that don't use general models. They'll train their own fine-tunes, built for exactly what they need and consistent between shots for long content.
1:05
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LTX-2 trainer is a huge deal. I tried it to add water to the podracers scene using their demo water-sim fine-tune (it's a fine-tune whose only goal is to add water :D) I think we're going to see film productions that don't use general models. They'll train their own fine-tunes, built for exactly what they need and consistent between shots for long content.

Victor M

94,623 views • 2 months ago

Watch Gemma-4-E4B casually identify sea animals by classifying images in a single agentic session using its vision capabilities. (impressive for a 4B model 🚀) I'm convinced: the agents of tomorrow are local, free, fast, and run on every computer!
0:25
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Watch Gemma-4-E4B casually identify sea animals by classifying images in a single agentic session using its vision capabilities. (impressive for a 4B model 🚀) I'm convinced: the agents of tomorrow are local, free, fast, and run on every computer!

Victor M

171,614 views • 4 months ago

My last hours with Fable: I was building this movement parkour sim before it went down... Impressed by its autonomy: built its own self-verifying harness with its own rubric for how a movement should feel. When a new movement was added it could tell on its own what felt right or wrong until it felt 100% right without me in the loop (and it was very good at it) Fable was more than just another model iteration imo. For the short (but intense) time it was available, it felt like playing with clay: ideas became code with almost no friction and the line between both became blurry. More than ever: open source MUST win. I don't want a world where intelligence is centralized and you're stuck with a hand saw while others have a chainsaw.
0:27
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My last hours with Fable: I was building this movement parkour sim before it went down... Impressed by its autonomy: built its own self-verifying harness with its own rubric for how a movement should feel. When a new movement was added it could tell on its own what felt right or wrong until it felt 100% right without me in the loop (and it was very good at it) Fable was more than just another model iteration imo. For the short (but intense) time it was available, it felt like playing with clay: ideas became code with almost no friction and the line between both became blurry. More than ever: open source MUST win. I don't want a world where intelligence is centralized and you're stuck with a hand saw while others have a chainsaw.

Victor M

82,975 views • 2 months ago

finally ported my fav Claude Code feature into Pi: `/subtask` a subtask is a fork of your current conversation, it inherits everything you've discussed, works in the background, and sends only its final answer back into the conversation that spawned it. Less context pollution/bloating and you can continue the main conversation as subtasks are running. here's what's packed into the Pi extension: - a live panel under the prompt: ↑↓ to select, enter to watch a fork work in real time, x to stop or dismiss it - steer a running fork mid-task, or resume a finished one without losing its progress - the model can spawn subtasks on its own and keep working while it waits for the result - forks reuse the parent's prompt cache, so they're cheaper than briefing a subagent - every fork's transcript is a real pi session: reopen it any time with `pi --session `
0:20
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finally ported my fav Claude Code feature into Pi: `/subtask` a subtask is a fork of your current conversation, it inherits everything you've discussed, works in the background, and sends only its final answer back into the conversation that spawned it. Less context pollution/bloating and you can continue the main conversation as subtasks are running. here's what's packed into the Pi extension: - a live panel under the prompt: ↑↓ to select, enter to watch a fork work in real time, x to stop or dismiss it - steer a running fork mid-task, or resume a finished one without losing its progress - the model can spawn subtasks on its own and keep working while it waits for the result - forks reuse the parent's prompt cache, so they're cheaper than briefing a subagent - every fork's transcript is a real pi session: reopen it any time with `pi --session `

Victor M

18,314 views • 14 days ago

Why is a 100% open source chatbot faster so much faster then ChatGPT to turn an image into anime? 👀
0:30
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Why is a 100% open source chatbot faster so much faster then ChatGPT to turn an image into anime? 👀

Victor M

205,559 views • 9 months ago

Open source AI music is actually good now 🔥 Made a free demo for ACE-Step 1.5: describe any song, get it back in seconds ⤵️
1:04
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Open source AI music is actually good now 🔥 Made a free demo for ACE-Step 1.5: describe any song, get it back in seconds ⤵️

Victor M

99,588 views • 4 months ago

This is wild 🤯 We finally have an open-source music generation model that rocks 🚀
0:56
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This is wild 🤯 We finally have an open-source music generation model that rocks 🚀

Victor M

248,949 views • 1 year ago

Asked Kimi K3 for "The Odyssey in ASCII" (didn't expect the arrow scenes 👌)
1:30
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Asked Kimi K3 for "The Odyssey in ASCII" (didn't expect the arrow scenes 👌)

Victor M

24,459 views • 1 month ago

Why isn't everyone using FLUX.2-dev-Turbo? Top quality, great at editing, 1.5s/image speed, 120 images for $1. My go-to for AI image gen/editing now 🔥
0:26
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Why isn't everyone using FLUX.2-dev-Turbo? Top quality, great at editing, 1.5s/image speed, 120 images for $1. My go-to for AI image gen/editing now 🔥

Victor M

78,040 views • 8 months ago

New TTS bomb dropped on Hugging Face. It has multispeaker support and the output quality looks amazing 🤯
0:23
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New TTS bomb dropped on Hugging Face. It has multispeaker support and the output quality looks amazing 🤯

Victor M

112,653 views • 1 year ago

🤯 Mind blown by the realism of podcasts generated by NotebookLM...
6:45
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🤯 Mind blown by the realism of podcasts generated by NotebookLM...

Victor M

165,968 views • 1 year ago

it's open source time, with a real leap for world models 🎉 NVIDIA's SANA-WM: a camera-conditioned world model that fits on one GPU. 60s of 720p in 34s on a single 5090 - 2.6B params and Apache 2.0!
0:20
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it's open source time, with a real leap for world models 🎉 NVIDIA's SANA-WM: a camera-conditioned world model that fits on one GPU. 60s of 720p in 34s on a single 5090 - 2.6B params and Apache 2.0!

Victor M

34,386 views • 3 months ago

DeepSite V2 just dropped (insane for Vibe Coding) 🤯 🔹Amazingly good at UI Design 🔹DeepSeek-R1 model now available 🔹Targeted Edits on any element 🔹Redesign any existing website 🔹100% open source (UI + models)
0:36
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DeepSite V2 just dropped (insane for Vibe Coding) 🤯 🔹Amazingly good at UI Design 🔹DeepSeek-R1 model now available 🔹Targeted Edits on any element 🔹Redesign any existing website 🔹100% open source (UI + models)

Victor M

105,886 views • 1 year ago

Introducing: HuggingChat Omni 💫 Select the best model for every prompt automatically 🚀 - Automatic model selection for your queries - 115 models available across 15 providers Available now all Hugging Face users. 100% open source.
0:31
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Introducing: HuggingChat Omni 💫 Select the best model for every prompt automatically 🚀 - Automatic model selection for your queries - 115 models available across 15 providers Available now all Hugging Face users. 100% open source.

Victor M

72,428 views • 10 months ago

Hugging Face Spaces, the world's largest AI app directory, is now MCP-compatible 🤯 Here turning an entire website into Ghibli in one shot with Claude Code to demonstrate what's now possible: instantly access any A I tool right in your LLM client!
0:21
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Hugging Face Spaces, the world's largest AI app directory, is now MCP-compatible 🤯 Here turning an entire website into Ghibli in one shot with Claude Code to demonstrate what's now possible: instantly access any A I tool right in your LLM client!

Victor M

82,196 views • 1 year ago

who made this 🇫🇷 banger lol (identify yourself)
2:00
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who made this 🇫🇷 banger lol (identify yourself)

Victor M

28,235 views • 4 months ago