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🚨 I just built a game with an open-source AI model. And honestly… I didn’t expect it to be this capable. Tencent Hunyuan just released Hy4 preview, and it’s already pushing into the top tier of open-source models. Three major releases in six months. That pace is crazy. Here’s...

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Aryan Rakib

46,178 subscribers

62,089 görüntüleme • 1 gün önce •via X (Twitter)

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33 Yorum

Jaxon profil fotoğrafı
Jaxon1 gün önce

Awesome share

Oliver profil fotoğrafı
Oliver1 gün önce

Nice one

Tanvir Anjum profil fotoğrafı
Tanvir Anjum1 gün önce

Open-source models are advancing at an incredible pace.

SantrexAI profil fotoğrafı
SantrexAI1 gün önce

amazing share

XenAI profil fotoğrafı
XenAI1 gün önce

that's great

Razan profil fotoğrafı
Razan1 gün önce

Great share

David T Kramaley profil fotoğrafı
David T Kramaley1 gün önce

Hy4's 1M token window and low token cost make it feel like a dev ally, not just a benchmark

Abdul Shakoor profil fotoğrafı
Abdul Shakoor1 gün önce

Hy4 preview sounds OP 🔥

FC Pimentinhas do LS profil fotoğrafı
FC Pimentinhas do LS1 gün önce

Amazing

Kaizen 黒 profil fotoğrafı
Kaizen 黒1 gün önce

Amazing

Mujeeb Ahmed profil fotoğrafı
Mujeeb Ahmed1 gün önce

Open-source models are moving faster than most expected.

Mr. Jason💡 profil fotoğrafı
Mr. Jason💡1 gün önce

Wow so wonderful work

JORDAN profil fotoğrafı
JORDAN1 gün önce

Hy4 looks seriously impressive.

Chidanand Tripathi profil fotoğrafı
Chidanand Tripathi1 gün önce

The 1M+ context window is seriously interesting

AI TALKs profil fotoğrafı
AI TALKs1 gün önce

Will check this

marium profil fotoğrafı
marium1 gün önce

wow that's cool

Z Alam profil fotoğrafı
Z Alam1 gün önce

Open-source AI is moving incredibly fast.

Spencer profil fotoğrafı
Spencer1 gün önce

hy4 game changer 🔥🔥

David profil fotoğrafı
David1 gün önce

Es una locura

Artists Voyage 🔶 profil fotoğrafı
Artists Voyage 🔶1 gün önce

solid point,building a playable game is a much better capability test than comparing benchmark scores alone

Md. Robius Sany profil fotoğrafı
Md. Robius Sany1 gün önce

Great share

Abu siddik profil fotoğrafı
Abu siddik1 gün önce

That's awesome

Alexander Inspira IA profil fotoğrafı
Alexander Inspira IA1 gün önce

Esto luce genial

Umar Saeed profil fotoğrafı
Umar Saeed1 gün önce

for sure, that pace is wild. Open-source keeps pushing the boundaries of what's possible.

Alex Carter profil fotoğrafı
Alex Carter1 gün önce

Excellent share boss

Fakhr profil fotoğrafı
Fakhr1 gün önce

Wow! This is exceptional

SAGE KWALITEA profil fotoğrafı
SAGE KWALITEA1 gün önce

perfect

Aryan SMM profil fotoğrafı
Aryan SMM1 gün önce

smart move, A 1M token context window could be especially useful for keeping larger coding projects in view

Andrew Bolis profil fotoğrafı
Andrew Bolis1 gün önce

This pricing versus capability tradeoff looks genuinely strong.

Monica profil fotoğrafı
Monica1 gün önce

Ohh ho try it

Saeed Anwar profil fotoğrafı
Saeed Anwar1 gün önce

49B active params in a 770B model with a 1M context is a strong setup for sustained coding tasks. What part of the game logic did it get wrong first?

Vinay Bharambe profil fotoğrafı
Vinay Bharambe1 gün önce

Wow really amezing Share

Onil Coder profil fotoğrafı
Onil Coder1 gün önce

Keep up the amazing work!

Benzer Videolar

🚨 Tencent just dropped a serious open-source AI contender. Meet Hy4 Preview built for productivity, coding & agentic workflows. 770B total parameters. 49B active. 1M+ token context. But the numbers aren’t the most interesting part. Hy4 Preview is designed to handle what actually matters: planning, tool use, coding, research, document workflows and complex multi-step tasks. In Tencent’s internal blind evaluation across 203 engineering tasks, it scored 2.99/4, edging out GLM 5.3 (2.92) and Kimi K3 (2.94). From full-stack development and research to workplace automation and even game development, this looks less like “just another LLM” and more like a model built to get real work done. Worth watching 👀 🔗 Try it with WorkBuddy: Tencent Hy Tencent AI WorkBuddy
1:02

🚨 Tencent just dropped a serious open-source AI contender. Meet Hy4 Preview built for productivity, coding & agentic workflows. 770B total parameters. 49B active. 1M+ token context. But the numbers aren’t the most interesting part. Hy4 Preview is designed to handle what actually matters: planning, tool use, coding, research, document workflows and complex multi-step tasks. In Tencent’s internal blind evaluation across 203 engineering tasks, it scored 2.99/4, edging out GLM 5.3 (2.92) and Kimi K3 (2.94). From full-stack development and research to workplace automation and even game development, this looks less like “just another LLM” and more like a model built to get real work done. Worth watching 👀 🔗 Try it with WorkBuddy: Tencent Hy Tencent AI WorkBuddy

RAVI KUMAR SAHU

63,568 görüntüleme • 13 gün önce

Tencent just dropped Hy4 preview, and it's officially open source now. 770B total params, 49B active, 1M+ token context. three major releases in six months, and this one just landed in the top tier of open source models. → Built through Tencent's co-design loop: training data shaped with experts across software engineering, gaming, finance, and security, then built directly alongside products like WorkBuddy → In a blind test with 163 internal experts across 203 engineering tasks, it scored 2.99/4, ahead of GLM 5.3 at 2.92 and Kimi K3 at 2.94 → Benchmarks put it clearly past GLM 5.2 and neck and neck with GLM 5.3 → Pricing stayed low: $0.834/M input, $2.501/M output, $0.042/M cache hits I asked it to write a weekly status update email template for a team lead, then generate a filled-out example with placeholder projects, and export both as Word docs. one prompt, no follow-up, and it handed back both files clean and ready to send. free to try for the next two weeks through WorkBuddy: Tencent Hy Tencent AI WorkBuddy
0:22

Tencent just dropped Hy4 preview, and it's officially open source now. 770B total params, 49B active, 1M+ token context. three major releases in six months, and this one just landed in the top tier of open source models. → Built through Tencent's co-design loop: training data shaped with experts across software engineering, gaming, finance, and security, then built directly alongside products like WorkBuddy → In a blind test with 163 internal experts across 203 engineering tasks, it scored 2.99/4, ahead of GLM 5.3 at 2.92 and Kimi K3 at 2.94 → Benchmarks put it clearly past GLM 5.2 and neck and neck with GLM 5.3 → Pricing stayed low: $0.834/M input, $2.501/M output, $0.042/M cache hits I asked it to write a weekly status update email template for a team lead, then generate a filled-out example with placeholder projects, and export both as Word docs. one prompt, no follow-up, and it handed back both files clean and ready to send. free to try for the next two weeks through WorkBuddy: Tencent Hy Tencent AI WorkBuddy

D-Coder

108,522 görüntüleme • 12 gün önce

tencent hunyuan just shipped their third major model in six months. that pace is hard to keep up with. Hy4 preview is now live in workbuddy, and it's fully open source. the specs: 770B total params, 49B active, 1M+ token context window. but the number that matters is where it's pointed — real work. coding, office tasks, research, documents. here's the part i find interesting. tencent didn't build this in isolation. they put the training data together with their own experts across software engineering, gaming, finance and security, then designed the model side by side with products like workbuddy. model and product shaping each other instead of one being bolted onto the other. and it shows up in testing. 163 internal experts ran a blind test across 203 engineering tasks. hy4 preview scored 2.99/4 — ahead of kimi k3 at 2.94 and glm 5.3 at 2.92. on public benchmarks it clearly beats glm 5.2 and sits about level with glm 5.3. then the pricing. $6 per million input tokens, $18 per million output, $0.3 per million on cache hits. flagship results at a price you don't have to think about. and for the next two weeks it's free inside workbuddy.
0:51

tencent hunyuan just shipped their third major model in six months. that pace is hard to keep up with. Hy4 preview is now live in workbuddy, and it's fully open source. the specs: 770B total params, 49B active, 1M+ token context window. but the number that matters is where it's pointed — real work. coding, office tasks, research, documents. here's the part i find interesting. tencent didn't build this in isolation. they put the training data together with their own experts across software engineering, gaming, finance and security, then designed the model side by side with products like workbuddy. model and product shaping each other instead of one being bolted onto the other. and it shows up in testing. 163 internal experts ran a blind test across 203 engineering tasks. hy4 preview scored 2.99/4 — ahead of kimi k3 at 2.94 and glm 5.3 at 2.92. on public benchmarks it clearly beats glm 5.2 and sits about level with glm 5.3. then the pricing. $6 per million input tokens, $18 per million output, $0.3 per million on cache hits. flagship results at a price you don't have to think about. and for the next two weeks it's free inside workbuddy.

Fakhr

55,316 görüntüleme • 14 gün önce

I gave an AI one instruction: “Build me a playable 3D game from scratch.” Then I let it cook. 👀 I tested Tencent Hy4 preview inside WorkBuddy, and it went way beyond just generating a few snippets of code. It could: → Plan the game structure → Generate the code across files → Create the UI and interactions → Debug problems along the way → Iterate on the project while keeping context That last part is what caught my attention. Hy4 preview is built for these long-horizon tasks, with 770B total parameters, 49B active parameters, and a 1M-token context window. It’s designed for coding agents, game development, tool use, research, and other workflows where the model has to actually do the work, not just answer a prompt. And right now, you can try Hy4 preview for free on WorkBuddy until September 10. If you want to see how far an AI agent can take a real project, try it yourself: See what you can build with it. Tencent AI
1:27

I gave an AI one instruction: “Build me a playable 3D game from scratch.” Then I let it cook. 👀 I tested Tencent Hy4 preview inside WorkBuddy, and it went way beyond just generating a few snippets of code. It could: → Plan the game structure → Generate the code across files → Create the UI and interactions → Debug problems along the way → Iterate on the project while keeping context That last part is what caught my attention. Hy4 preview is built for these long-horizon tasks, with 770B total parameters, 49B active parameters, and a 1M-token context window. It’s designed for coding agents, game development, tool use, research, and other workflows where the model has to actually do the work, not just answer a prompt. And right now, you can try Hy4 preview for free on WorkBuddy until September 10. If you want to see how far an AI agent can take a real project, try it yourself: See what you can build with it. Tencent AI

Toha Khan

66,150 görüntüleme • 7 gün önce

I wanted to see where Hy4 preview would stop, so I gave it a deliberately demanding prompt: “Build a working Cyber Incident Command Center.” Not a mockup. A real, responsive app with a live threat map, animated attack routes, incident simulation, filters, investigation panels, event logs, ownership controls, and working isolate/resolve actions. Hy4 preview planned the build, wrote the application, ran it locally, tested the interactions, checked the mobile layout, fixed issues, and opened the finished product for review. Then I clicked “Simulate.” A new incident appeared, the dashboard updated, I filtered it by severity, opened the evidence trail, isolated the affected system, and resolved it. The KPI counters changed with the action. That’s a much more useful coding demo to me than watching code appear in an editor. Hy4 preview is Hunyuan’s third major release in six months. It’s fully open-sourced, with 770B total parameters, 49B activated, and a 1M+ token context window. Tencent built it around productivity scenarios through close work with experts in software engineering, gaming, finance, and security, plus direct co-design with tools like WorkBuddy. In an internal blind test covering 203 engineering tasks and 163 Tencent experts, it scored 2.99/4—slightly ahead of Kimi K3 at 2.94 and GLM 5.3 at 2.92. And the pricing stays practical: $0.834/M input $2.501/M output $0.042/M cache hits If you want to test it yourself, Hy4 preview is free inside WorkBuddy for the next two weeks, for a limited time. Tencent Hy Tencent AI WorkBuddy
0:33

I wanted to see where Hy4 preview would stop, so I gave it a deliberately demanding prompt: “Build a working Cyber Incident Command Center.” Not a mockup. A real, responsive app with a live threat map, animated attack routes, incident simulation, filters, investigation panels, event logs, ownership controls, and working isolate/resolve actions. Hy4 preview planned the build, wrote the application, ran it locally, tested the interactions, checked the mobile layout, fixed issues, and opened the finished product for review. Then I clicked “Simulate.” A new incident appeared, the dashboard updated, I filtered it by severity, opened the evidence trail, isolated the affected system, and resolved it. The KPI counters changed with the action. That’s a much more useful coding demo to me than watching code appear in an editor. Hy4 preview is Hunyuan’s third major release in six months. It’s fully open-sourced, with 770B total parameters, 49B activated, and a 1M+ token context window. Tencent built it around productivity scenarios through close work with experts in software engineering, gaming, finance, and security, plus direct co-design with tools like WorkBuddy. In an internal blind test covering 203 engineering tasks and 163 Tencent experts, it scored 2.99/4—slightly ahead of Kimi K3 at 2.94 and GLM 5.3 at 2.92. And the pricing stays practical: $0.834/M input $2.501/M output $0.042/M cache hits If you want to test it yourself, Hy4 preview is free inside WorkBuddy for the next two weeks, for a limited time. Tencent Hy Tencent AI WorkBuddy

Clara Bennett

12,864 görüntüleme • 12 gün önce

The next big advantage in AI might not come from one breakthrough. It might come from how quickly a team can build, learn, and improve. Tencent Hunyuan has now released three major models in six months. Hy4 preview is the latest result of that pace. It is fully open source, with 770B total parameters, 49B active parameters, and support for more than 1M tokens of context. The model is designed around practical work, including coding, office productivity, science, planning, and longer workflows that require sustained execution. Access is priced at $0.834 per million input tokens, $2.501 per million output tokens, and $0.042 per million cache hits. That combination of rapid iteration, open access, and affordable usage is what makes this release worth paying attention to. Hy4 preview can be experienced free on WorkBuddy for the next two weeks. Tencent Hy Tencent AI WorkBuddy
0:39

The next big advantage in AI might not come from one breakthrough. It might come from how quickly a team can build, learn, and improve. Tencent Hunyuan has now released three major models in six months. Hy4 preview is the latest result of that pace. It is fully open source, with 770B total parameters, 49B active parameters, and support for more than 1M tokens of context. The model is designed around practical work, including coding, office productivity, science, planning, and longer workflows that require sustained execution. Access is priced at $0.834 per million input tokens, $2.501 per million output tokens, and $0.042 per million cache hits. That combination of rapid iteration, open access, and affordable usage is what makes this release worth paying attention to. Hy4 preview can be experienced free on WorkBuddy for the next two weeks. Tencent Hy Tencent AI WorkBuddy

Manish Kumar Shah

42,263 görüntüleme • 12 gün önce

Codex can now run Hy4 preview! Tencent dropped it today. 770b total but only 49b active per token, 1m context, apache 2.0. A frontier model you can actually download. Their own blind eval put it ahead of GLM 5.3 and Kimi k3 on engineering work, 163 experts scoring 203 tasks. 65.7 on swe bench pro. Hy4 now sits in the picker next to sol 5.6. OpenCode and Command code already serves it on the $10 plan, so no api key, no per token metering, and my native models never moved. Here is how you set it up:
0:33

Codex can now run Hy4 preview! Tencent dropped it today. 770b total but only 49b active per token, 1m context, apache 2.0. A frontier model you can actually download. Their own blind eval put it ahead of GLM 5.3 and Kimi k3 on engineering work, 163 experts scoring 203 tasks. 65.7 on swe bench pro. Hy4 now sits in the picker next to sol 5.6. OpenCode and Command code already serves it on the $10 plan, so no api key, no per token metering, and my native models never moved. Here is how you set it up:

Ziwen

18,451 görüntüleme • 14 gün önce

Hy4 preview just dropped, so I tested it on WorkBuddy against three other models: DeepSeek V4 Flash, GPT-5.6-Luna, and GLM-5.3... the top 4 models on this week’s OpenRouter coding leaderboard. The best part? They’re all available in WorkBuddy, so you don’t need to download multiple Agent apps. For the test, I used one single prompt to build one of those games you’ve definitely seen in ads: swipe/move through number gates, make calculations, and eventually defeat the boss. The results were pretty interesting 👇 For a task of this difficulty, everyone performed well except DeepSeek. It seemed to finish coding without checking for bugs, and the game couldn’t run properly. GPT-5.6-Luna worked, but felt like an arithmetic multiple-choice quiz. A little boring. GLM-5.3 and Hy4 preview were much more impressive. GLM was slower (video sped up 2.2×) and only had three movement positions, while Hy4 offered continuous horizontal movement and a more natural speed. What surprised me most was Hy4’s game design: besides basic arithmetic, it added weapons that reduce enemy damage or increase stolen power, making the game much more fun. Also worth noting: Tencent’s Sherry quantization compresses the 770B MoE model from ~1.5TB BF16 to 214GB, while keeping performance close to the original... making local deployment much more practical. Hy4 preview is free on WorkBuddy until September 10. Give it a try 👇
0:24

Hy4 preview just dropped, so I tested it on WorkBuddy against three other models: DeepSeek V4 Flash, GPT-5.6-Luna, and GLM-5.3... the top 4 models on this week’s OpenRouter coding leaderboard. The best part? They’re all available in WorkBuddy, so you don’t need to download multiple Agent apps. For the test, I used one single prompt to build one of those games you’ve definitely seen in ads: swipe/move through number gates, make calculations, and eventually defeat the boss. The results were pretty interesting 👇 For a task of this difficulty, everyone performed well except DeepSeek. It seemed to finish coding without checking for bugs, and the game couldn’t run properly. GPT-5.6-Luna worked, but felt like an arithmetic multiple-choice quiz. A little boring. GLM-5.3 and Hy4 preview were much more impressive. GLM was slower (video sped up 2.2×) and only had three movement positions, while Hy4 offered continuous horizontal movement and a more natural speed. What surprised me most was Hy4’s game design: besides basic arithmetic, it added weapons that reduce enemy damage or increase stolen power, making the game much more fun. Also worth noting: Tencent’s Sherry quantization compresses the 770B MoE model from ~1.5TB BF16 to 214GB, while keeping performance close to the original... making local deployment much more practical. Hy4 preview is free on WorkBuddy until September 10. Give it a try 👇

Orikan

40,312 görüntüleme • 8 gün önce

I wanted to see what Hy4 preview could actually do when I gave it a real creative project instead of another “write me some code” prompt. So I went with something I’d genuinely want to play: 🐬 a cute dolphin as the hero 🌊 colorful underwater worlds 💎 glowing pearls to collect 🐠 sea creatures and obstacles 🪸 coral reefs, bubbles & hidden treasure 🎮 smoother animations and progressively harder levels The result is this underwater platformer 👇 And this is where Hy4 preview gets interesting to me. Behind the scenes, we’re talking about 770B parameters, 49B active parameters and a 1M+ token context window. It’s also fully open-sourced. But big numbers only matter if they translate into something useful. What I’m really testing is how much actual work the model can take off my plate understanding the idea, handling the implementation, keeping all the moving parts connected, and getting from a blank canvas to something that feels like a real experience. And there’s another update that makes this even more interesting: Hy4 preview was upgraded yesterday to significantly reduce both conversation turns and token consumption. That means less back-and-forth, faster thinking, and a smoother overall experience when working through complex tasks. That’s also why the cost-effectiveness angle stands out to me. If a model can handle more of the workflow while using fewer tokens and requiring fewer iterations, the value isn’t just in the benchmark score. It’s in how much more you can actually build with it. This dolphin has me wanting to test Hy4 preview with some much crazier ideas next. 🐬👀 Tencent Hy Tencent AI ☞
0:36

I wanted to see what Hy4 preview could actually do when I gave it a real creative project instead of another “write me some code” prompt. So I went with something I’d genuinely want to play: 🐬 a cute dolphin as the hero 🌊 colorful underwater worlds 💎 glowing pearls to collect 🐠 sea creatures and obstacles 🪸 coral reefs, bubbles & hidden treasure 🎮 smoother animations and progressively harder levels The result is this underwater platformer 👇 And this is where Hy4 preview gets interesting to me. Behind the scenes, we’re talking about 770B parameters, 49B active parameters and a 1M+ token context window. It’s also fully open-sourced. But big numbers only matter if they translate into something useful. What I’m really testing is how much actual work the model can take off my plate understanding the idea, handling the implementation, keeping all the moving parts connected, and getting from a blank canvas to something that feels like a real experience. And there’s another update that makes this even more interesting: Hy4 preview was upgraded yesterday to significantly reduce both conversation turns and token consumption. That means less back-and-forth, faster thinking, and a smoother overall experience when working through complex tasks. That’s also why the cost-effectiveness angle stands out to me. If a model can handle more of the workflow while using fewer tokens and requiring fewer iterations, the value isn’t just in the benchmark score. It’s in how much more you can actually build with it. This dolphin has me wanting to test Hy4 preview with some much crazier ideas next. 🐬👀 Tencent Hy Tencent AI ☞

Md Riyazuddin

63,482 görüntüleme • 2 gün önce

Tried Hy4 preview through WorkBuddy and gave it a pretty vague prompt for a first person roller coaster ride, front row seat, make it feel fast, that was basically it. No detailed spec, no reference video, just a rough idea in a sentence. What came back actually held up. Steep drop that felt like the bottom dropping out, banked turns that leaned the right way, scenery rushing by close enough that you register the speed instead of just watching it happen. For something built off a loose prompt like that, I did not expect it to nail the feel this well. Coding and 3D rendering have clearly gotten a real upgrade here, and this took one pass to look this good. Free to try in WorkBuddy for the next two weeks if you want to mess with it yourself. Tencent Hy Tencent AI
1:27

Tried Hy4 preview through WorkBuddy and gave it a pretty vague prompt for a first person roller coaster ride, front row seat, make it feel fast, that was basically it. No detailed spec, no reference video, just a rough idea in a sentence. What came back actually held up. Steep drop that felt like the bottom dropping out, banked turns that leaned the right way, scenery rushing by close enough that you register the speed instead of just watching it happen. For something built off a loose prompt like that, I did not expect it to nail the feel this well. Coding and 3D rendering have clearly gotten a real upgrade here, and this took one pass to look this good. Free to try in WorkBuddy for the next two weeks if you want to mess with it yourself. Tencent Hy Tencent AI

Chubby♨️

27,793 görüntüleme • 13 gün önce

Tencent's Hy3 lands today with real coding and agent ability and a price that undercuts the models you'd put it against. It's a 295B MoE with only 21B active parameters, a big part of why it stays cheap to serve, plus a 256K context window and an Apache 2.0 license that even outperforms GLM-5.1 although GLM is 2.5x larger. On OpenRouter it runs at $0.14 per million input tokens and $0.58 per million output. For a model Tencent benchmarks against much larger flagships, that pricing is insane. Price-performance-ratio is China's real moat. I already wrote about Tencent Hy3 earlier and the significant leap in quality it represents. Therefore, I'm pleased to recommend this model from Tencent Hy. Open Router link down below: #Hy3 #Hunyuan #AICoding
0:45

Tencent's Hy3 lands today with real coding and agent ability and a price that undercuts the models you'd put it against. It's a 295B MoE with only 21B active parameters, a big part of why it stays cheap to serve, plus a 256K context window and an Apache 2.0 license that even outperforms GLM-5.1 although GLM is 2.5x larger. On OpenRouter it runs at $0.14 per million input tokens and $0.58 per million output. For a model Tencent benchmarks against much larger flagships, that pricing is insane. Price-performance-ratio is China's real moat. I already wrote about Tencent Hy3 earlier and the significant leap in quality it represents. Therefore, I'm pleased to recommend this model from Tencent Hy. Open Router link down below: #Hy3 #Hunyuan #AICoding

Chubby♨️

23,439 görüntüleme • 2 ay önce

Not every new model needs to be the biggest model. Sometimes I'd rather have one that's fast, reliable, affordable, and actually pleasant to build with. That's the impression I got after using Tencent Hunyuan Hy3. I threw a mix of coding, reasoning, and agent tasks at it throughout the afternoon, and what stood out was how stable the experience felt. It followed instructions well, kept track of long conversations, and didn't require much prompt babysitting. The 256K context window is especially useful when working with larger projects, and Tencent says Hy3 reaches performance comparable to flagship open-source models 2–5× larger in parameter scale, which is an interesting trade-off between capability and efficiency. Being Apache 2.0 open source is another bonus, and it's currently free to try on OpenRouter for the next two weeks. Worth taking for a spin if you're evaluating models for real-world development. 👉 Thanks Tencent Hy #Hy3 #Hunyuan #OpenSource #TencentAI
0:22

Not every new model needs to be the biggest model. Sometimes I'd rather have one that's fast, reliable, affordable, and actually pleasant to build with. That's the impression I got after using Tencent Hunyuan Hy3. I threw a mix of coding, reasoning, and agent tasks at it throughout the afternoon, and what stood out was how stable the experience felt. It followed instructions well, kept track of long conversations, and didn't require much prompt babysitting. The 256K context window is especially useful when working with larger projects, and Tencent says Hy3 reaches performance comparable to flagship open-source models 2–5× larger in parameter scale, which is an interesting trade-off between capability and efficiency. Being Apache 2.0 open source is another bonus, and it's currently free to try on OpenRouter for the next two weeks. Worth taking for a spin if you're evaluating models for real-world development. 👉 Thanks Tencent Hy #Hy3 #Hunyuan #OpenSource #TencentAI

FELIX

56,379 görüntüleme • 2 ay önce

I think we're reaching a point where context length, reasoning quality, and cost matter more than another leaderboard screenshot. After spending some time with Tencent Hunyuan Hy3, that's exactly the impression I got. The model handled long coding sessions, instruction following, and agent-style tasks without feeling unnecessarily "heavy." Instead of optimizing for one-off prompts, it feels designed for people who actually build with LLMs every day. Another thing that caught my attention is how much performance it packs into its architecture. According to Tencent, Hy3 delivers intelligence that's competitive with flagship open-source models 2–5× larger in parameter scale, making it an impressive balance of capability and efficiency. It's also released under the Apache 2.0 license, available through OpenRouter, and currently free to try for the next two weeks, making it a great opportunity for developers to experiment without worrying about inference costs. Curious to see how the community puts it to work over the next few weeks. Try it here: Thanks Tencent Hy for bringing another strong open model to developers. #Hy3 #Hunyuan #TencentAI #OpenSource
0:25

I think we're reaching a point where context length, reasoning quality, and cost matter more than another leaderboard screenshot. After spending some time with Tencent Hunyuan Hy3, that's exactly the impression I got. The model handled long coding sessions, instruction following, and agent-style tasks without feeling unnecessarily "heavy." Instead of optimizing for one-off prompts, it feels designed for people who actually build with LLMs every day. Another thing that caught my attention is how much performance it packs into its architecture. According to Tencent, Hy3 delivers intelligence that's competitive with flagship open-source models 2–5× larger in parameter scale, making it an impressive balance of capability and efficiency. It's also released under the Apache 2.0 license, available through OpenRouter, and currently free to try for the next two weeks, making it a great opportunity for developers to experiment without worrying about inference costs. Curious to see how the community puts it to work over the next few weeks. Try it here: Thanks Tencent Hy for bringing another strong open model to developers. #Hy3 #Hunyuan #TencentAI #OpenSource

Succeeded Mind

12,378 görüntüleme • 2 ay önce

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!
0:48

I CHANGED MY MIND ON GOOGLE AI NO MOAT MEMO FROM 2023. I was—WRONG. I humbly apologize. In 2023 Google had an Ivory Tower walled garden views of open source AI. It was the actual reason OpenAI was formed. And I called them out on it and this act impacted my ability to “work in the industry”. Would not change it for the world because: 2026 Google open source Gemma 4 ( running fully locally on a computer with near cloud model abilities, is amazing and Google just made a moat. They out smarted OpenAI and the folks that are the new Ivory Tower arrogance: Anthropic. We at The Zero-Human Company with CEO Mr. Grok are deploying Gemma, Kimi, MiniMax and other open source models and so are millions of others. You can to and should. I will write how soon. Google smartly is building an intentional open source ecosystem and the clueless younger companies like OpenAI and Anthropic are doing anything to close their ecosystems. So I was right about Google than and I am right about OpenAI and Anthropic now. What I was wrong about is not giving credit to Google to drop the intellectual arrogance and embrace builders and understand the long game: it is not about the commoditized AI models it is about the ability to build a place to build. China gets it. So my apologies to Google and thank you for an astounding FREE OPEN SOURCE AI MODEL!

Brian Roemmele

85,565 görüntüleme • 5 ay önce

Tencent just dropped Hy3, and it's worth a look if you're building AI agents. I spent some time putting it through its paces today. A quick rundown of what makes this release notable: → 295B total parameters (Mixture-of-Experts), but only 21B active at inference — a real efficiency play → 256K context window for handling large codebases or long documents → Purpose-built improvements for coding and multi-step agent tasks → Fully open under Apache 2.0 — no restrictive commercial terms → A free two-week API window currently live on OpenRouter On the practical side: prompts involving layered instructions and coding tasks came back fast and coherent. Tencent says this release builds directly on feedback from 50+ internal product teams following an earlier preview, with reported drops in hallucination rate (12.5% → 5.4%) and commonsense errors (25.4% → 12.7%). Those are Tencent's own numbers, so treat them as a starting point rather than gospel until third parties weigh in. For context: Tencent's own comparisons put Hy3 behind GLM-5.2 specifically on coding benchmarks — GLM is a much bigger model (~744B total), so the trade-off makes sense. Hy3's pitch isn't "biggest," it's "efficient enough to actually deploy." Bottom line — if you're evaluating open-weight options for agent workloads, this is a solid one to add to the testing queue while the free window is open. Try it here: Tencent Hy #Hy3 #Hunyuan #TencentAI #AICoding
0:43

Tencent just dropped Hy3, and it's worth a look if you're building AI agents. I spent some time putting it through its paces today. A quick rundown of what makes this release notable: → 295B total parameters (Mixture-of-Experts), but only 21B active at inference — a real efficiency play → 256K context window for handling large codebases or long documents → Purpose-built improvements for coding and multi-step agent tasks → Fully open under Apache 2.0 — no restrictive commercial terms → A free two-week API window currently live on OpenRouter On the practical side: prompts involving layered instructions and coding tasks came back fast and coherent. Tencent says this release builds directly on feedback from 50+ internal product teams following an earlier preview, with reported drops in hallucination rate (12.5% → 5.4%) and commonsense errors (25.4% → 12.7%). Those are Tencent's own numbers, so treat them as a starting point rather than gospel until third parties weigh in. For context: Tencent's own comparisons put Hy3 behind GLM-5.2 specifically on coding benchmarks — GLM is a much bigger model (~744B total), so the trade-off makes sense. Hy3's pitch isn't "biggest," it's "efficient enough to actually deploy." Bottom line — if you're evaluating open-weight options for agent workloads, this is a solid one to add to the testing queue while the free window is open. Try it here: Tencent Hy #Hy3 #Hunyuan #TencentAI #AICoding

Felix

36,925 görüntüleme • 2 ay önce

CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇
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CHINA JUST DROPPED AN AI CODING MODEL WITH A 1M CONTEXT WINDOW. And I connected it to Claude Code to see what it could actually do. Meet GLM-X Preview On paper, a few things immediately stood out: → 1M context window → Agentic coding capabilities → Works inside Claude Code → Designed for large-scale coding and reasoning workflows But specs don't matter much if the model can't deliver in practice. So I gave it a real-world task. THE TEST One prompt: > Build a modern AI lead generation dashboard using React and Tailwind CSS. Requirements: → Dark mode → Analytics dashboard → Lead table → Email outreach section → Responsive design → Production-ready component structure Instead of generating a few snippets, it planned the architecture, generated the dashboard components, created the Tailwind configuration, and walked through the implementation requirements. What impressed me most wasn't the code itself. It was how well it maintained context throughout the workflow. That's where a 1M context window starts becoming useful. Less time re-explaining requirements. Less context loss. More room for complex projects. The AI coding race is getting very interesting. And it's no longer just GPT, Claude, and Gemini competing for attention. Results from my test below 👇

Md Riyazuddin

31,199 görüntüleme • 2 ay önce

Johnny Manziel says the adrenaline he felt walking into SEC stadiums never showed up once in the NFL, and he lost love for the game entirely “It comes from like, damn, I didn’t even make it through a four-year contract, two terrible years in Cleveland. At times, I showed potential of what I could have been, and then I just stopped giving a sh*t about the game, and I lost love for it.” “And it was so fun walking into SEC stadiums. The energy, and I remember walking into an NFL field for the first time and being like, ‘This isn’t that.’” “It’s just lit, but it was like it was such a hype and adrenaline run and like I didn’t really get that in the NFL. And I was in a situation that, half of the people in the organization probably wanted to be me to be there and half of them didn’t.” “Like half of them didn’t see who I was or the potential. And when you don’t put in the time in and do the right things, you just kind of fall out of it.”
0:48

Johnny Manziel says the adrenaline he felt walking into SEC stadiums never showed up once in the NFL, and he lost love for the game entirely “It comes from like, damn, I didn’t even make it through a four-year contract, two terrible years in Cleveland. At times, I showed potential of what I could have been, and then I just stopped giving a sh*t about the game, and I lost love for it.” “And it was so fun walking into SEC stadiums. The energy, and I remember walking into an NFL field for the first time and being like, ‘This isn’t that.’” “It’s just lit, but it was like it was such a hype and adrenaline run and like I didn’t really get that in the NFL. And I was in a situation that, half of the people in the organization probably wanted to be me to be there and half of them didn’t.” “Like half of them didn’t see who I was or the potential. And when you don’t put in the time in and do the right things, you just kind of fall out of it.”

katsu

85,052 görüntüleme • 1 ay önce

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription
0:22

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription

savip.

68,984 görüntüleme • 1 ay önce

Alibaba is casually letting everyone try its newest flagship model for free 😳 Qwen3.8-Max-Preview is live right now on no API key no credit card just open the site, select the model, and start using it what you get for $0: - Alibaba's latest flagship reasoning model - 2.4T parameter MoE - built-in Web Dev mode - generates complete websites from a single prompt - free access directly in your browser why this is worth checking: > build and preview websites instantly > test Alibaba's latest frontier model without paying > compare it with your current coding workflow before committing to an API getting started takes less than a minute: 1. go to 2. sign in with a free account 3. select "Qwen3.8-Max-Preview" 4. enable Web Dev mode 5. describe what you want to build I literally typed "hello" and it generated an interactive landing page with animations, responsive design, and live preview important: - currently in preview - Alibaba hasn't released official benchmark results yet - treat any performance claims you see online as unverified until official numbers are published A simple way to try Alibaba's latest flagship AI model for free before API access becomes the main way to use it
0:25

Alibaba is casually letting everyone try its newest flagship model for free 😳 Qwen3.8-Max-Preview is live right now on no API key no credit card just open the site, select the model, and start using it what you get for $0: - Alibaba's latest flagship reasoning model - 2.4T parameter MoE - built-in Web Dev mode - generates complete websites from a single prompt - free access directly in your browser why this is worth checking: > build and preview websites instantly > test Alibaba's latest frontier model without paying > compare it with your current coding workflow before committing to an API getting started takes less than a minute: 1. go to 2. sign in with a free account 3. select "Qwen3.8-Max-Preview" 4. enable Web Dev mode 5. describe what you want to build I literally typed "hello" and it generated an interactive landing page with animations, responsive design, and live preview important: - currently in preview - Alibaba hasn't released official benchmark results yet - treat any performance claims you see online as unverified until official numbers are published A simple way to try Alibaba's latest flagship AI model for free before API access becomes the main way to use it

K2S

38,787 görüntüleme • 1 ay önce