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DeepSeek V4.1 Flash made DOOM in Atomic Chat 🐳 DeepSeek dropped a new architecture for the flash model so we tested it by making Doom in an html file and it built a real raycasting shooter with gun mechanics and enemy waves Run AI models locally ->

atomic.chat

15,513 subscribers

21,103 次观看 • 1 天前 •via X (Twitter)

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2 条评论

AshutoshShrivastava 的头像

AshutoshShrivastava1 天前

@deepseek_ai Crazy for local model and it is so cheap too . mogging opus and sol

Nedim Dino 的头像

Nedim Dino1 天前

@deepseek_ai Incredible

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deepseek v4.1 flash ran all four three.js scenes for $0.15. gemini 3.8 flash needed $1.25 we put the two models on one job: a self-contained html page that renders an animated 3d scene with three.js – a storm at sea, a spiral galaxy, a tornado over farmland, a tesla coil on a dark table. same prompt - calls until all four scenes were usable #1 deepseek v4.1 flash – 6 #2 gemini 3.8 flash – 12 - time #1 deepseek v4.1 flash – 13m 57s #2 gemini 3.8 flash – 32m 02s - cost #1 deepseek v4.1 flash – $0.15 #2 gemini 3.8 flash – $1.25 observations: • gemini blew out the exposure on 4 of 5 first attempts – a white blob where the tesla coil should be. the prompt had a paragraph on exposure. it did not help. • both models overcorrect in the fix loop: "too bright" becomes "almost black". round two is where it lands. same four scenes, 6 calls and $0.15 against 12 calls and $1.25!

deepseek v4.1 flash ran all four three.js scenes for $0.15. gemini 3.8 flash needed $1.25 we put the two models on one job: a self-contained html page that renders an animated 3d scene with three.js – a storm at sea, a spiral galaxy, a tornado over farmland, a tesla coil on a dark table. same prompt - calls until all four scenes were usable #1 deepseek v4.1 flash – 6 #2 gemini 3.8 flash – 12 - time #1 deepseek v4.1 flash – 13m 57s #2 gemini 3.8 flash – 32m 02s - cost #1 deepseek v4.1 flash – $0.15 #2 gemini 3.8 flash – $1.25 observations: • gemini blew out the exposure on 4 of 5 first attempts – a white blob where the tesla coil should be. the prompt had a paragraph on exposure. it did not help. • both models overcorrect in the fix loop: "too bright" becomes "almost black". round two is where it lands. same four scenes, 6 calls and $0.15 against 12 calls and $1.25!

thehype.

58,442 次观看 • 1 天前

deepseek-v4.1-flash I'm really curious to understand the architecture behind the scenes. 🤔 Model is really fast as you can see in the video! I've got an average decoding speed of around 350 t/s. BTW it is clearly experimental and: - currently, the model is under heavy load and failing quite often. - it thinks like there is not tomorrow - it keeps failing editing file - after 4M tokens my frogger game is still in progress - it can't see images out of the box on DeepSeek Harness, you have to add these config lines - id: deepseek-v4.1-flash-expires-on-0910 name: deepseek-v4.1-flash-expires-on-0910 contextWindow: 1000000 inputModalities: - text - image imagePixelBudget: 640000 imageMaxBytes: 1048576 So play with it, but be aware of the very early stage.

deepseek-v4.1-flash I'm really curious to understand the architecture behind the scenes. 🤔 Model is really fast as you can see in the video! I've got an average decoding speed of around 350 t/s. BTW it is clearly experimental and: - currently, the model is under heavy load and failing quite often. - it thinks like there is not tomorrow - it keeps failing editing file - after 4M tokens my frogger game is still in progress - it can't see images out of the box on DeepSeek Harness, you have to add these config lines - id: deepseek-v4.1-flash-expires-on-0910 name: deepseek-v4.1-flash-expires-on-0910 contextWindow: 1000000 inputModalities: - text - image imagePixelBudget: 640000 imageMaxBytes: 1048576 So play with it, but be aware of the very early stage.

Ivan Fioravanti ᯅ

26,971 次观看 • 3 天前

deepseek v4.1 flash vs secret model tested both with the same prompt at the highest reasoning available > v4.1 flash took 2 hours to finish both tests and cost $2.60 > secret model finished both in 30 minutes, can’t reveal cost yet v4.1 flash spent a lot of time overthinking and running random tests, which slowed it down thanks AIHubmix for providing api access so i could test v4.1 flash hoping that team will cut down the overthinking before the full release, but for now here are the results which model did better here?

deepseek v4.1 flash vs secret model tested both with the same prompt at the highest reasoning available > v4.1 flash took 2 hours to finish both tests and cost $2.60 > secret model finished both in 30 minutes, can’t reveal cost yet v4.1 flash spent a lot of time overthinking and running random tests, which slowed it down thanks AIHubmix for providing api access so i could test v4.1 flash hoping that team will cut down the overthinking before the full release, but for now here are the results which model did better here?

J A Z I I

28,586 次观看 • 3 天前

I've asked Astra to read the DeepSeek v4.1 Flash paper and compare it to the original Transformer architecture in 3D - you can zoom in an inspect each element side by side. Things have changed quite a bit. Try yourself:

I've asked Astra to read the DeepSeek v4.1 Flash paper and compare it to the original Transformer architecture in 3D - you can zoom in an inspect each element side by side. Things have changed quite a bit. Try yourself:

Peter Gostev

135,337 次观看 • 22 小时前

Turn any AI Model into Reasoning Model with Deepseek r1 <thinking> Architecture. Models like GPT4o and Sonnet 3.5 are Implementation Models But a new breakthrough with Deepseek can make them a Reasoning model. Here's a step-by-step Explanation: 🧵

Turn any AI Model into Reasoning Model with Deepseek r1 <thinking> Architecture. Models like GPT4o and Sonnet 3.5 are Implementation Models But a new breakthrough with Deepseek can make them a Reasoning model. Here's a step-by-step Explanation: 🧵

CJ Zafir

192,667 次观看 • 1 年前

DeepSeek V4.1 Flash vs Kimi K3 This is not one-shot from DeepSeek btw. The first result was boxy and not realistic, so I iterated with a $6 cap. Kimi did this in one shot, costing $6.95. Not as good as Kimi K3, but it did better than the other Flash models I’ve tried.

DeepSeek V4.1 Flash vs Kimi K3 This is not one-shot from DeepSeek btw. The first result was boxy and not realistic, so I iterated with a $6 cap. Kimi did this in one shot, costing $6.95. Not as good as Kimi K3, but it did better than the other Flash models I’ve tried.

Bhavy☄️

33,428 次观看 • 1 天前

Deepseek running locally and privately for autocompletion in VSCode! 🙌 In less than a minute, I'll show you how to download Deepseek-coder and set it as the autocompletion model in VSCode. You’ll need to use ollama to download the model and CodeGPT to select it as the autocompletion model. Enjoy the best models running locally with :)

Deepseek running locally and privately for autocompletion in VSCode! 🙌 In less than a minute, I'll show you how to download Deepseek-coder and set it as the autocompletion model in VSCode. You’ll need to use ollama to download the model and CodeGPT to select it as the autocompletion model. Enjoy the best models running locally with :)

Daniel San

992,753 次观看 • 1 年前

Introducing DeepSeek R1:1.5b Running Locally in Cursor! In less than 4 minutes, I set up the DeepSeek R1:1.5b model, download it, and run it locally to seamlessly work with code in Cursor The video is shown in real-time, with the model impressively running on an Intel Core i5 😱 using Ollama and the CodeGPT extension 👇

Introducing DeepSeek R1:1.5b Running Locally in Cursor! In less than 4 minutes, I set up the DeepSeek R1:1.5b model, download it, and run it locally to seamlessly work with code in Cursor The video is shown in real-time, with the model impressively running on an Intel Core i5 😱 using Ollama and the CodeGPT extension 👇

Daniel San

584,100 次观看 • 1 年前

MiMo-X-Pro-Preview vs DeepSeek V4.1 Flash the difference in quality is honestly insane, MiMo X Pro Preview, especially when paired with MiMo-Flash-Preview, feels noticeably ahead You can already tell the kind of benchmark scores MiMo must be hitting right now. DeepSeek V4.1 Flash is good and fast, but MiMo feels like it’s playing in a completely different league, It’s still only in beta for now, but I really hope Xiaomi releases this model soon! , And huge congratulations to the DeepSeek as well for building such a fast and genuinely good model

MiMo-X-Pro-Preview vs DeepSeek V4.1 Flash the difference in quality is honestly insane, MiMo X Pro Preview, especially when paired with MiMo-Flash-Preview, feels noticeably ahead You can already tell the kind of benchmark scores MiMo must be hitting right now. DeepSeek V4.1 Flash is good and fast, but MiMo feels like it’s playing in a completely different league, It’s still only in beta for now, but I really hope Xiaomi releases this model soon! , And huge congratulations to the DeepSeek as well for building such a fast and genuinely good model

Iam_

18,359 次观看 • 1 天前

For anyone wandering what does it mean to run ds4-agent locally on an M5 Max using DeepSeek V4 Flash q2-imatrix gguf model. Here's a video of ds4 updating itself, adding a way to leverage HF_HOME for gguf models. Future of Local AI is bright!

For anyone wandering what does it mean to run ds4-agent locally on an M5 Max using DeepSeek V4 Flash q2-imatrix gguf model. Here's a video of ds4 updating itself, adding a way to leverage HF_HOME for gguf models. Future of Local AI is bright!

Ivan Fioravanti ᯅ

30,452 次观看 • 3 个月前

Timelapse #177 (14 hrs) - Picked up an RTX Pro 6000 Blackwell and wired in another 1000W PSU - running two of them now - DeepSeek v4 Flash running locally on both GPUs - Distilling DeepSeek v4 Flash down into Nanbeige (still cooking) - Kernel bench runs for DeepSeek v4 Flash and Qwen 3.8 Max - Got it into chat but couldn't reliably get it into the OMP harness yet - Private contract work - days like this are stuff I actually want to build. and when it's the high-intensity grind, i still have to show up and get it done

Timelapse #177 (14 hrs) - Picked up an RTX Pro 6000 Blackwell and wired in another 1000W PSU - running two of them now - DeepSeek v4 Flash running locally on both GPUs - Distilling DeepSeek v4 Flash down into Nanbeige (still cooking) - Kernel bench runs for DeepSeek v4 Flash and Qwen 3.8 Max - Got it into chat but couldn't reliably get it into the OMP harness yet - Private contract work - days like this are stuff I actually want to build. and when it's the high-intensity grind, i still have to show up and get it done

Elliot Arledge

17,401 次观看 • 1 个月前

We gave DeepSeek Harness its own browser. DeepSeek Paired with ego lite, it can navigate the web using your existing browser sessions. For its first run, it opened X, watched the Gemini 3.7 Flash launch video from Google, and broke down what made it effective.

We gave DeepSeek Harness its own browser. DeepSeek Paired with ego lite, it can navigate the web using your existing browser sessions. For its first run, it opened X, watched the Gemini 3.7 Flash launch video from Google, and broke down what made it effective.

ego

28,515 次观看 • 28 天前

🚀 New update for the Grafilab AI ecosystem! We’ve just updated new frontier models in our Playground and Unified API, including the highly anticipated models by DeepSeek and Qwen families! 🧠⚡ But that’s not all… you can now run Side-by-Side Model Comparisons directly in the Grafilab Playground! 🥊 Compare outputs from Gemini, DeepSeek, Qwen, and more in real-time, on the exact same prompt, with zero code. Find the perfect model for your workload instantly. Try it out now:

🚀 New update for the Grafilab AI ecosystem! We’ve just updated new frontier models in our Playground and Unified API, including the highly anticipated models by DeepSeek and Qwen families! 🧠⚡ But that’s not all… you can now run Side-by-Side Model Comparisons directly in the Grafilab Playground! 🥊 Compare outputs from Gemini, DeepSeek, Qwen, and more in real-time, on the exact same prompt, with zero code. Find the perfect model for your workload instantly. Try it out now:

Grafilab - Unleash AI

805,542 次观看 • 2 个月前

DeepSeek V4.1 Flash is a very interesting model. I just tested it on the BridgeBench lava lamp test and it took LONGER to complete than Fable 5.1 and GPT 6 Astra. It ran at 344 toks/sec, spent 23.5M tokens with a cache hit rate of 99.7%, and cost $0.33. Even though it runs so fast it ends up completing tasks very slowly. The lava lamp that it produced was better than Muse Spark 1.3 and Gemini 3.8 Flash.

DeepSeek V4.1 Flash is a very interesting model. I just tested it on the BridgeBench lava lamp test and it took LONGER to complete than Fable 5.1 and GPT 6 Astra. It ran at 344 toks/sec, spent 23.5M tokens with a cache hit rate of 99.7%, and cost $0.33. Even though it runs so fast it ends up completing tasks very slowly. The lava lamp that it produced was better than Muse Spark 1.3 and Gemini 3.8 Flash.

BridgeMind

123,641 次观看 • 2 天前

The new DeepSeek V4.1 Flash model is mindblowing - back on top of the open-source model leaderboard and extremely cheap. It has a lot of very smart ways to be efficient and highly capable so I made a video of the forward pass to give you a view of what going on inside the model during inference. Read more at And find the weights at

The new DeepSeek V4.1 Flash model is mindblowing - back on top of the open-source model leaderboard and extremely cheap. It has a lot of very smart ways to be efficient and highly capable so I made a video of the forward pass to give you a view of what going on inside the model during inference. Read more at And find the weights at

Thomas Wolf

56,387 次观看 • 1 天前

ox alpha vs deepseek v4 flash vision vs grok 4.6 vs gemini 3.7 flash vs – on photo-to-3d four vision models got one photograph each and had to rebuild the place inside it as a Three.js scene. twelve scenes, twelve first-try runs, zero console errors the setup: one reference photo per scene, sent as an image on OpenRouter. the prompt never says what is in the picture – no "motel", no "bar", no "gas station". the model has to read the photo and rebuild it: layout, materials, hour of the day, and whatever is around the corner that the frame does not show tasks – three photographs of early-2000s america: 1. a motel at night, neon pylon lit, snow on the ground 2. an old new york tavern interior, tin ceiling, tiled floor 3. an abandoned service station in the california desert, midday sun each scene ships as one self-contained html file, procedural geometry and canvas textures only, no downloads. three timed camera shots, and shot 1 has to reproduce the framing of the reference photo models: xAI grok 4.6, Google DeepMind gemini 3.7 flash, DeepSeek deepseek v4 flash vision exp, and ox alpha – a stealth model on openrouter, free, no lab attached to it yet results: - wall clock, three scenes #1 gemini 3.7 flash – 11m 12s #2 deepseek v4 flash – 15m 20s #3 grok 4.6 – 28m 11s #4 ox alpha – 38m 54s - output tokens #1 gemini 3.7 flash – 77,396 #2 ox alpha – 87,613 #3 grok 4.6 – 105,687 #4 deepseek v4 flash – 127,884 - lines of code shipped #1 ox alpha – 2,090 #2 deepseek v4 flash – 2,291 #3 grok 4.6 – 3,529 #4 gemini 3.7 flash – 3,989 - total price #1 ox alpha – $0.000 #2 deepseek v4 flash – $0.091 #3 gemini 3.7 flash – $0.136 #4 grok 4.6 – $0.697 observations: • grok is 7.7x the price of deepseek. it is the only model that read the light – low sun, real shadows on the station, a cold night on the motel • gemini is the fastest and the least deliberate. 17,158 reasoning tokens against deepseek's 99,172, and it still shipped the most code – 3,989 lines • deepseek thought hardest and rendered plainest. 99,172 reasoning tokens, 5.8x gemini's, spent on layout rather than on light. its motel is the second best in the set for $0.030 • ox alpha is free and reads a photo as well as anything here – it lifted "family units / kitchenettes" off the pylon and redrew it in canvas conclusion: twelve scenes, four models, zero fixes, and the whole run cost $0.924! follow thehype. for 24/7 ai news, analysis and breakdowns

ox alpha vs deepseek v4 flash vision vs grok 4.6 vs gemini 3.7 flash vs – on photo-to-3d four vision models got one photograph each and had to rebuild the place inside it as a Three.js scene. twelve scenes, twelve first-try runs, zero console errors the setup: one reference photo per scene, sent as an image on OpenRouter. the prompt never says what is in the picture – no "motel", no "bar", no "gas station". the model has to read the photo and rebuild it: layout, materials, hour of the day, and whatever is around the corner that the frame does not show tasks – three photographs of early-2000s america: 1. a motel at night, neon pylon lit, snow on the ground 2. an old new york tavern interior, tin ceiling, tiled floor 3. an abandoned service station in the california desert, midday sun each scene ships as one self-contained html file, procedural geometry and canvas textures only, no downloads. three timed camera shots, and shot 1 has to reproduce the framing of the reference photo models: xAI grok 4.6, Google DeepMind gemini 3.7 flash, DeepSeek deepseek v4 flash vision exp, and ox alpha – a stealth model on openrouter, free, no lab attached to it yet results: - wall clock, three scenes #1 gemini 3.7 flash – 11m 12s #2 deepseek v4 flash – 15m 20s #3 grok 4.6 – 28m 11s #4 ox alpha – 38m 54s - output tokens #1 gemini 3.7 flash – 77,396 #2 ox alpha – 87,613 #3 grok 4.6 – 105,687 #4 deepseek v4 flash – 127,884 - lines of code shipped #1 ox alpha – 2,090 #2 deepseek v4 flash – 2,291 #3 grok 4.6 – 3,529 #4 gemini 3.7 flash – 3,989 - total price #1 ox alpha – $0.000 #2 deepseek v4 flash – $0.091 #3 gemini 3.7 flash – $0.136 #4 grok 4.6 – $0.697 observations: • grok is 7.7x the price of deepseek. it is the only model that read the light – low sun, real shadows on the station, a cold night on the motel • gemini is the fastest and the least deliberate. 17,158 reasoning tokens against deepseek's 99,172, and it still shipped the most code – 3,989 lines • deepseek thought hardest and rendered plainest. 99,172 reasoning tokens, 5.8x gemini's, spent on layout rather than on light. its motel is the second best in the set for $0.030 • ox alpha is free and reads a photo as well as anything here – it lifted "family units / kitchenettes" off the pylon and redrew it in canvas conclusion: twelve scenes, four models, zero fixes, and the whole run cost $0.924! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

24,202 次观看 • 17 天前

here’s how you can use DeepSeek V4.1 Flash completely FREE inside OpenCode. the setup takes less than 5 minutes. 1️⃣ first, download and install OpenCode from if you don’t already have it. 2️⃣ once it’s set up, head over to Token Harbor and sign in with your Gmail or GitHub account. 3️⃣ create a new API key and save it somewhere safe. 4️⃣ then go back to OpenCode and head to: Settings → Providers → Custom Model 5️⃣ fill in the details with: - Base URL: - API Key: paste the key you created earlier. add the model, save the setup, and you can start using DeepSeek V4.1 Flash directly inside OpenCode. the only catch: this free access is available for a limited time, so take advantage of it while it lasts.

here’s how you can use DeepSeek V4.1 Flash completely FREE inside OpenCode. the setup takes less than 5 minutes. 1️⃣ first, download and install OpenCode from if you don’t already have it. 2️⃣ once it’s set up, head over to Token Harbor and sign in with your Gmail or GitHub account. 3️⃣ create a new API key and save it somewhere safe. 4️⃣ then go back to OpenCode and head to: Settings → Providers → Custom Model 5️⃣ fill in the details with: - Base URL: - API Key: paste the key you created earlier. add the model, save the setup, and you can start using DeepSeek V4.1 Flash directly inside OpenCode. the only catch: this free access is available for a limited time, so take advantage of it while it lasts.

m0h

36,619 次观看 • 1 天前