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Deepseek-V4-Flash helping me setup Nvidia's Dynamo for disaggregated inference. I have really gotten this model to be a daily driver now. It's really strong at agentic workflows and a decent programmer. For all my side stuff, it's local deepseek now Claude sub cancelled wdyt

0xSero

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24,469 просмотров • 3 месяцев назад •via X (Twitter)

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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.

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.

0xSero

20,019 просмотров • 3 месяцев назад

I LOVE Deepseek-v4-flash, incredibly reliable and capable, logical. It's lacking in frontend but I have MiMo for that. I would recommend any company spending 100k+ a year on AI to purchase 8-10~ 6000s and have a few of the works to have them blind test these models for work.

I LOVE Deepseek-v4-flash, incredibly reliable and capable, logical. It's lacking in frontend but I have MiMo for that. I would recommend any company spending 100k+ a year on AI to purchase 8-10~ 6000s and have a few of the works to have them blind test these models for work.

0xSero

51,035 просмотров • 3 месяцев назад

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 просмотров • 24 дней назад

I just saw AGI, what the heck. Deepseek-v4-flash-0731 invented vision for itself, this is so incredible. Result in the next post:

I just saw AGI, what the heck. Deepseek-v4-flash-0731 invented vision for itself, this is so incredible. Result in the next post:

0xSero

173,214 просмотров • 16 дней назад

FREE DeepSeek V4 Pro and V4 Flash API. Runtime by Bad Theory Labs just dropped it. Same platform, new free model, same 2-minute setup. > Runtime already gave you free Claude Opus 4.8 and GPT 5.5 access. Now they added DeepSeek V4 Pro and V4 Flash to the free tier. Absolutely FREE, YES. Same exact flow as before: → Go to runtime(.)badtheorylabs(.)com → Sign up with Google → Fill in your details during onboarding → Free balance lands automatically(But you don't need it to use DeepSeek - it's completely free right now) → Grab your API key from the dashboard → Plug into OpenCode, OpenClaw, or Hermes - done DeepSeek V4 Pro is one of the strongest coding and reasoning models available right now. Free tier also includes btl-2 - auto-routes between GLM, OpenAI, Anthropic, and Gemma. 10 million tokens per month at zero cost. 344 models total. One OpenAI-compatible endpoint. No code rebuild, no card, no limits hunting. >> Just start using the API, and when choosing a provider, select DeepSeek I tested it myself - fully working. Bookmark this before the free tier fills up.

FREE DeepSeek V4 Pro and V4 Flash API. Runtime by Bad Theory Labs just dropped it. Same platform, new free model, same 2-minute setup. > Runtime already gave you free Claude Opus 4.8 and GPT 5.5 access. Now they added DeepSeek V4 Pro and V4 Flash to the free tier. Absolutely FREE, YES. Same exact flow as before: → Go to runtime(.)badtheorylabs(.)com → Sign up with Google → Fill in your details during onboarding → Free balance lands automatically(But you don't need it to use DeepSeek - it's completely free right now) → Grab your API key from the dashboard → Plug into OpenCode, OpenClaw, or Hermes - done DeepSeek V4 Pro is one of the strongest coding and reasoning models available right now. Free tier also includes btl-2 - auto-routes between GLM, OpenAI, Anthropic, and Gemma. 10 million tokens per month at zero cost. 344 models total. One OpenAI-compatible endpoint. No code rebuild, no card, no limits hunting. >> Just start using the API, and when choosing a provider, select DeepSeek I tested it myself - fully working. Bookmark this before the free tier fills up.

Atenov int.

26,920 просмотров • 2 месяцев назад

A 3B model just cleared a puzzle that a 1.6 TRILLION param model couldn't. You've seen this benchmark before: my sliding-puzzle test. Same Kimi & DeepSeek runs as last time. The only new thing: I dropped VibeThinker-3B in for a side-by-side. > VibeThinker → 3B > DeepSeek V4 Flash → 284B > Kimi K2.6 → 1T > DeepSeek V4 Pro → 1.6T Shuffle depths 5, 10, 12, 15, 18, 22. One wrong move scrambles the whole board, so it's pure long-chain reasoning. ✅ VibeThinker-3B: solved all six. Never lost the thread. ⚠️ The giants started cracking at depth 15: Flash, Pro, and even Kimi each blew a run, scrambling the board past the move cap. As VibeThinker was not trained for tool calling, I had it emit X and ran the move. Bigger generalist ≠ smarter.

A 3B model just cleared a puzzle that a 1.6 TRILLION param model couldn't. You've seen this benchmark before: my sliding-puzzle test. Same Kimi & DeepSeek runs as last time. The only new thing: I dropped VibeThinker-3B in for a side-by-side. > VibeThinker → 3B > DeepSeek V4 Flash → 284B > Kimi K2.6 → 1T > DeepSeek V4 Pro → 1.6T Shuffle depths 5, 10, 12, 15, 18, 22. One wrong move scrambles the whole board, so it's pure long-chain reasoning. ✅ VibeThinker-3B: solved all six. Never lost the thread. ⚠️ The giants started cracking at depth 15: Flash, Pro, and even Kimi each blew a run, scrambling the board past the move cap. As VibeThinker was not trained for tool calling, I had it emit X and ran the move. Bigger generalist ≠ smarter.

stevibe

32,638 просмотров • 2 месяцев назад

holy sh*t this is f**king insane I cancelled my $200/mo Claude for this I replaced opus 5 with deepseek v4-flash and someone figured out to how to use them as subagents on codex [it takes 3 mins to set up here is how] 1. install this repo called 'model-router' 2. toggle subagent models > 'all selected models' 3. that's it

holy sh*t this is f**king insane I cancelled my $200/mo Claude for this I replaced opus 5 with deepseek v4-flash and someone figured out to how to use them as subagents on codex [it takes 3 mins to set up here is how] 1. install this repo called 'model-router' 2. toggle subagent models > 'all selected models' 3. that's it

Avid

416,979 просмотров • 21 дней назад

Loading DeepSeek v4 Flash just reminded me how good and fast this model is and how well it runs on DGX Sparks. GLM-5.2 is really awesome, but if you want fast and concurrent inference, DS4F is still a top choice IMO. Created by DS4F in single shot The coffee guy

Loading DeepSeek v4 Flash just reminded me how good and fast this model is and how well it runs on DGX Sparks. GLM-5.2 is really awesome, but if you want fast and concurrent inference, DS4F is still a top choice IMO. Created by DS4F in single shot The coffee guy

Mia

39,686 просмотров • 1 месяц назад

Jumpkit rigged! This was quite fun, even though it's quite a simple setup. Still really pleased with my model and textures😍 Although... now I have to tackle the hips and legs. #rigging #blender #3d

Jumpkit rigged! This was quite fun, even though it's quite a simple setup. Still really pleased with my model and textures😍 Although... now I have to tackle the hips and legs. #rigging #blender #3d

RyanLykos

295,274 просмотров • 1 месяц назад

I have been testing DeepSeek-V4-Pro with the Pi coding agent. I am mindblown by how well it works out of the box. A few notes: I spent a few hours building an LLM wiki with an agent powered entirely by DeepSeek-V4-Pro on Fireworks inference. This is the first time I feel like there is an open-weight model that can reason at the level of Claude and Codex. And it does this in a cost-effective way with support for 1M context length. To be clear, I am using DeepSeek-V4-Pro inside of Pi without any special configuration. It works out of the box. It's exciting that there is a model that can just be plugged into a basic harness like Pi, and it just works. I've never seen that before. Most models require lots of configuration and setup. DeepSeek's DeepSeek-V4-Pro is clearly good at agentic coding (probably the best from the open-weight models), but the model is also great on knowledge-intensive tasks where reasoning matters. The agent pulled agentic engineering best practices from different company docs (Anthropic, OpenAI, Google, Stripe, Meta, Modal, DeepSeek, Mistral, Cohere), searched and digested Reddit and HN threads, summarized arxiv papers, and surfaced trending GitHub repos. Then it distilled everything into actionable tips across categories. I love the Wiki it built. The quality is really good. Here is a snapshot of what the wiki looks like: DeepSeek-V4-Pro handled the task without breaking stride. Multi-step research queries, code generation for scaffolding, context-heavy reasoning across disparate sources. For coding specifically, this is the first open-weight model that genuinely feels like a Codex or Claude Code experience. It compares in capability and actual multi-turn agentic work. What made the loop feel so responsive was Fireworks' inference speed (the fastest in the market) and the fact that they actually validate models at the systems level before shipping. No corrupted reasoning traces. Just fast, reliable iteration. The hybrid CSA and HCA attention design cuts KV cache to just 10% and inference FLOPs by nearly 4x at 1M-token context. This is what makes the agent loop actually fast and cheap enough to run in practice. For devs who've been watching open-weight models close the gap but haven't found one that actually delivers in practice, this is the closest I've seen. Try it here:

I have been testing DeepSeek-V4-Pro with the Pi coding agent. I am mindblown by how well it works out of the box. A few notes: I spent a few hours building an LLM wiki with an agent powered entirely by DeepSeek-V4-Pro on Fireworks inference. This is the first time I feel like there is an open-weight model that can reason at the level of Claude and Codex. And it does this in a cost-effective way with support for 1M context length. To be clear, I am using DeepSeek-V4-Pro inside of Pi without any special configuration. It works out of the box. It's exciting that there is a model that can just be plugged into a basic harness like Pi, and it just works. I've never seen that before. Most models require lots of configuration and setup. DeepSeek's DeepSeek-V4-Pro is clearly good at agentic coding (probably the best from the open-weight models), but the model is also great on knowledge-intensive tasks where reasoning matters. The agent pulled agentic engineering best practices from different company docs (Anthropic, OpenAI, Google, Stripe, Meta, Modal, DeepSeek, Mistral, Cohere), searched and digested Reddit and HN threads, summarized arxiv papers, and surfaced trending GitHub repos. Then it distilled everything into actionable tips across categories. I love the Wiki it built. The quality is really good. Here is a snapshot of what the wiki looks like: DeepSeek-V4-Pro handled the task without breaking stride. Multi-step research queries, code generation for scaffolding, context-heavy reasoning across disparate sources. For coding specifically, this is the first open-weight model that genuinely feels like a Codex or Claude Code experience. It compares in capability and actual multi-turn agentic work. What made the loop feel so responsive was Fireworks' inference speed (the fastest in the market) and the fact that they actually validate models at the systems level before shipping. No corrupted reasoning traces. Just fast, reliable iteration. The hybrid CSA and HCA attention design cuts KV cache to just 10% and inference FLOPs by nearly 4x at 1M-token context. This is what makes the agent loop actually fast and cheap enough to run in practice. For devs who've been watching open-weight models close the gap but haven't found one that actually delivers in practice, this is the closest I've seen. Try it here:

elvis

60,091 просмотров • 4 месяцев назад

I just had to make a new video of GLM-4.7-Flash - Helping me refactor VLLM studio - Did a data analytics report for work - Managed to search my tweets - Made me a fully playable Pacman in 1 shot - Great at browser use This model is too good to be this small, the full thing will fit on a macbook, it's fast, precise and can do pretty much anything Sonnet can. It somehow benches higher than Sonnet 4, 3.7, Opus 4.5 no thinking, all the GPT models from last year and more.

I just had to make a new video of GLM-4.7-Flash - Helping me refactor VLLM studio - Did a data analytics report for work - Managed to search my tweets - Made me a fully playable Pacman in 1 shot - Great at browser use This model is too good to be this small, the full thing will fit on a macbook, it's fast, precise and can do pretty much anything Sonnet can. It somehow benches higher than Sonnet 4, 3.7, Opus 4.5 no thinking, all the GPT models from last year and more.

0xSero

38,263 просмотров • 7 месяцев назад

I paired Cloudflare OS with self hosted deepseek-v4-flash and the result is freakin amazing Imagine running this setup inside DGX spark, you get fully private work companion solving all your work stuff The thing about this type of software is it already have a good harness and it probably can work out of the box with every open weight model Cant wait for the future

I paired Cloudflare OS with self hosted deepseek-v4-flash and the result is freakin amazing Imagine running this setup inside DGX spark, you get fully private work companion solving all your work stuff The thing about this type of software is it already have a good harness and it probably can work out of the box with every open weight model Cant wait for the future

Farhan Helmy

57,953 просмотров • 23 дней назад

Man, what a model. I have not seen any mode below 200B act like this. It's really doing a good job in a pretty novel environment. The ZAI team is doing a great job I'm very happy they still open source all this. It's very impressive.

Man, what a model. I have not seen any mode below 200B act like this. It's really doing a good job in a pretty novel environment. The ZAI team is doing a great job I'm very happy they still open source all this. It's very impressive.

0xSero

41,620 просмотров • 7 месяцев назад

HERMES DESKTOP APP JUST GOT A NEW ULTRA MODE FOR DEEPSEEK V4 PRO – AND IT COSTS ABOUT $1 A DAY TO RUN If you're using Hermes desktop app, you're probably already running DeepSeek – it's one of the top models available. The update: → DeepSeek V4 Pro now has thinking mode, fast mode, and a brand new ultra mode → There's also an extra high mode, but the real upgrade is ultra The actual cost: roughly $1/day for a normal workflow. That's about $20-25/month – basically the same as before, just with a significantly faster mode unlocked. The verdict after a full day of testing: it flies through tool calling. Noticeably faster, same price range. If you're already paying for DeepSeek through Hermes, this is a free upgrade sitting in your settings right now. Update Hermes, grab the DeepSeek API if you don't have it yet, and try V4 Pro on ultra. Bookmark this, you'll want to come back to it later.

SCOTTY BEAM

24,032 просмотров • 1 месяц назад

$🇨🇳 🇺🇸 CHINA'S AI STACK IS GETTING DANGEROUSLY COMPETITIVE. Huawei's Ascend chips are now powering DeepSeek at a fraction of Western inference costs. The result: DeepSeek just made its 75% API price cut permanent on DeepSeek-V4-Pro. This is not a promotion. This is the new floor. The full vertical stack outside US sanctions and outside Nvidia's margins. DeepSeek can keep cutting. Chinese tech gets cheaper every quarter. A massive global undercut is no longer a question of if, only when. Western AI labs are running on $30,000 Nvidia chips at full markup. DeepSeek is running on Huawei silicon at cost. The unit economics aren't even in the same conversation. Every export ban that pushed China toward Huawei is paying off, for China.$

🇨🇳 🇺🇸 CHINA'S AI STACK IS GETTING DANGEROUSLY COMPETITIVE. Huawei's Ascend chips are now powering DeepSeek at a fraction of Western inference costs. The result: DeepSeek just made its 75% API price cut permanent on DeepSeek-V4-Pro. This is not a promotion. This is the new floor. The full vertical stack outside US sanctions and outside Nvidia's margins. DeepSeek can keep cutting. Chinese tech gets cheaper every quarter. A massive global undercut is no longer a question of if, only when. Western AI labs are running on $30,000 Nvidia chips at full markup. DeepSeek is running on Huawei silicon at cost. The unit economics aren't even in the same conversation. Every export ban that pushed China toward Huawei is paying off, for China.

CryptoGoos

43,154 просмотров • 3 месяцев назад

I have found myself using MiniMax more and more recently, it's very fast locally and works great with stuff that requires some level of privacy. Using about 6m tokens a day locally. It's also going way up now. This model is surprisingly capable in many unexpected places.

I have found myself using MiniMax more and more recently, it's very fast locally and works great with stuff that requires some level of privacy. Using about 6m tokens a day locally. It's also going way up now. This model is surprisingly capable in many unexpected places.

0xSero

33,919 просмотров • 7 месяцев назад

GPT-5.6 LUNA AND DEEPSEEK V4 FLASH ARE BOTH FREE RIGHT NOW -- ONE IN A CHATBOT, THE OTHER IN A BROWSER IDE • ChatGPT, the chatbot > GPT-5.6 Luna is now the default on Free and Go: > Unlimited text chats and a Think button land next week. • MonkeyCode, the browser IDE > 30M tokens a day, resets daily, no card: > DeepSeek V4 Flash, Qwen, GLM, Kimi and MiniMax behind it. > Cloud workspace at 1 vCPU and 4GB, nothing to install. Luna posts 62% fewer factual errors than the model it replaces. MonkeyCode is open source from Chaitin and runs on their cloud, so aim it at side projects. One is live today -> The other arrives next week.

GPT-5.6 LUNA AND DEEPSEEK V4 FLASH ARE BOTH FREE RIGHT NOW -- ONE IN A CHATBOT, THE OTHER IN A BROWSER IDE • ChatGPT, the chatbot > GPT-5.6 Luna is now the default on Free and Go: > Unlimited text chats and a Think button land next week. • MonkeyCode, the browser IDE > 30M tokens a day, resets daily, no card: > DeepSeek V4 Flash, Qwen, GLM, Kimi and MiniMax behind it. > Cloud workspace at 1 vCPU and 4GB, nothing to install. Luna posts 62% fewer factual errors than the model it replaces. MonkeyCode is open source from Chaitin and runs on their cloud, so aim it at side projects. One is live today -> The other arrives next week.

slash1s

33,804 просмотров • 20 дней назад

How did they make him so fast. Yesterday I got really excited about the inference side of Cerebras. This is the highest quality fast model I've tried so far. All of this is in it's infancy, imagine your world built as soon as you express what you want. Video games would slap

How did they make him so fast. Yesterday I got really excited about the inference side of Cerebras. This is the highest quality fast model I've tried so far. All of this is in it's infancy, imagine your world built as soon as you express what you want. Video games would slap

0xSero

17,965 просмотров • 2 месяцев назад