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Space Bunny performs TERRIBLE in physics 💀 we tested Space Bunny against GLM 5.3 in a task with a single focus scenes: an explosion in a desert, a tornado, a balloon pop, a water drop fall, and the Newton’s cradle here’s what we got: - the Newton’s cradle is... show more

AI/ML API

4,106 subscribers

26,835 views • 9 days ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

8 Comments

MadeByLupu9 days ago

Not just physics. It's overall reasoning is pretty underwhelming. It's better than MiniMax M3, so if its really M3.1 then it's fitting that they didn't name it M4.

AI/ML API9 days ago

yes

Rohan Paul9 days ago

Space buny news coming from everywhere. was so waiting for your physcis based demos on this.

AI/ML API9 days ago

And here they are!

Kunal Jain9 days ago

Also Space Bunny is terrible at 3D

Haha9 days ago

@MiniMax_AI ？？？你家的？？

Dhaval Makwana8 days ago

Seems cool, check dm!

安叫兽|Bird🕊️ 🔶 BNB9 days ago

水滴看着简单，做起来全是破绽

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Just tested Space Bunny against Gemini 3.8 Flash with the exact same prompt. Space Bunny built this full 3D isometric diorama in just a few minutes: Japanese estate, cherry blossom tree, koi pond, stone paths, and a floating island base. Both got the concept, but Space Bunny impressed me with how quickly it reached a complete result. The first generation was already surprisingly close to what I had in mind.

Just tested Space Bunny against Gemini 3.8 Flash with the exact same prompt. Space Bunny built this full 3D isometric diorama in just a few minutes: Japanese estate, cherry blossom tree, koi pond, stone paths, and a floating island base. Both got the concept, but Space Bunny impressed me with how quickly it reached a complete result. The first generation was already surprisingly close to what I had in mind.

Darshal Jaitwar

48,196 views • 7 days ago

GLM 5.3 Flash vs Hybrid (GLM 5.3 Flash + Jev) on a turn-based strategy game (Halite 2) The hybrid approach is 13x faster, 56% of the pure GLM 5.3 Flash API cost, and gains a slight edge in performance. In the hybrid approach: -GLM 5.3 Flash handles strategic judgment of which planets matter, who expands, who fights, when to re-plan. -Jev handles the ship-by-ship execution. GLM 5.3 Flash alone defeats Jev alone 82% of the time. This is obviously just a single example and some of the first things I've tried to make use of Jev as an augmentation to an LLM. Could potentially make even more gains in cost, speed, and performance, but using what I've figured out here, I am compelled to try some ideas with robotics next.

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53,159 views • 12 days ago

GLM 5.3 Flash running locally makes a Minecraft black hole mod We ran GLM 5.3 Flash Q4 locally on a rented 4x RTX PRO 6000 box and asked it to make a lightning gun mod for the real game using the Fabric API Output: -7.6M tokens -Time: ~9 hours -Decode: ~96 tok/s The mod adds a black hole rifle, when shot it spawns a black hole that pulls in blocks, with light rings that shrink all the way into the singularity, then collapses into an explosion crater that wipes out several chunks Run GLM 5.3 Flash locally in

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atomic.chat

32,515 views • 1 month ago

We tested GLM 5.3 Flash and Qwen 3.8 Flash in Pi. Same task for both: use ego lite to build an interactive 3D solar system. Qwen cost 3.6x more and ran 1.7x longer, but the output tells a different story. Comment "prompt" below and we'll drop it.

We tested GLM 5.3 Flash and Qwen 3.8 Flash in Pi. Same task for both: use ego lite to build an interactive 3D solar system. Qwen cost 3.6x more and ran 1.7x longer, but the output tells a different story. Comment "prompt" below and we'll drop it.

ego

24,535 views • 1 month ago

GLM-5.3 weights from Z.ai are live, with SGLang powering day-0 serving support! GLM-5.3 inherits every optimization and feature we battle-tested for GLM-5.2 over the past months. On real-world multi-turn agentic workloads, we measured 537.6 tok/s/user on NVFP4 and 413 tok/s/user on FP8, at BS=1 with TP8 on 8x B300. It's fast, efficient, and production-ready today on NVIDIA AI Blackwell and Hopper, and AI at AMD MI300X/325X/355X. We believe this is a big step forward for GLM-Series in agentic tasks, with a path toward mythos-class cyber capability. Can't wait to see what people build with GLM-5.3 and SGLang🚀 Cookbook👇

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SGLang

99,455 views • 1 month ago

Fable 5.1 xHigh vs GLM 5.3 Flash Max With Zai’s current promo, GLM 5.3 Flash is around 58x cheaper than Fable 5.1… and just look at the quality It finished the same task in about half the time, while still delivering a genuinely impressive result 58x cheaper. 2x faster. And the quality is this close That’s honestly crazy, Huge credit to Zhipu for bringing us models this efficient

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Iam_

110,563 views • 1 month ago

Space Bunny Alpha mogged by DeepSeek V4.1 Flash 🐳 We asked both to build Minecraft in one HTML file and DeepSeek V4.1 Flash made a forest biome you can walk and dig in while Space Bunny Alpha's ground has holes showing the sky Run AI models locally ->

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atomic.chat

49,485 views • 10 days ago

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Israfil

42,443 views • 9 days ago

glm 5.3 flash is 7.5x cheaper, but 3.4x slower than gemini 3.7 flash Z.ai glm 5.3 flash – shipped aug 26, $0.07/$0.25 per 1m Google DeepMind gemini 3.7 flash – shipped aug 13, $0.38/$1.88 per 1m we put the two models on one job: write one html file that draws an animated 3d scene in the browser. no images, no downloads, and it has to look the same on every load. the setup: three scenes – a glass aquarium in a lit room, the solar system, a night city under a thunderstorm. identical brief word for word, reasoning effort high, 64k output cap. the numbers below are not the whole run. they cover the three scenes we kept – the best one per task from each model, the ones in the video. - total generation time for the three scenes #1 gemini 3.7 flash – 10m 36s #2 glm 5.3 flash – 36m 30s - tokens spent on those three scenes #1 glm 5.3 flash – 110k #2 gemini 3.7 flash – 111k - cost of those three scenes #1 glm 5.3 flash – $0.027 #2 gemini 3.7 flash – $0.202 observations: • glm's first 10 attempts: 7 blank pages. it kept inventing short random helpers and forgetting to define one of them. the fix was one line in the brief: use exactly one random helper, named rand(), and don't invent shorthands next to it. next 12 attempts: 11 alive, 0 crashes. • glm spends 66% of its output on reasoning, gemini 57%. that is the whole speed gap. • gemini's storm came back as a black rectangle in 4 of 6 runs. glm's best storm has a branching bolt, lit rain and wet asphalt – for $0.01. conclusion: same three scenes, same token spend – glm 5.3 flash billed $0.027 and took 36m 30s, gemini 3.7 flash billed $0.202 and took 10m 36s. glm wins gemini on price and made the best storm of the whole run follow thehype. for 24/7 ai news, analysis and breakdowns

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thehype.

16,041 views • 1 month ago

DeepSeek v4.1 Flash vs GLM 5.3 Flash I asked both models to recreate the Psychonauts 2 and Metroid Prime game menus as closely as possible to the originals. Attached are full-sized videos from both models for both games. All were done in a single shot, both at Max thinking, same harness. Tokens used: DeepSeek v4.1 Flash - Psychonauts 2: 412k - Metroid Prime: 466k GLM 5.3 Flash - Psychonauts 2: 134k - Metroid Prime: 111k That's between 3-4x MORE used by DS4.1F. Who do you think won? IMO GLM 5.3 Flash won by FAR on both.

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Mia

23,835 views • 17 days ago

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m0h

101,243 views • 1 month ago

Trailer for our new AI film ‘Newton’s Cradle’. The full film drops here 1-1-25. photek Makewaves audio Powered by MiniMax Design (H3) Performance capture by Act-One. Voices 2 voice 4K youtube link: Synopsis: In a dystopian future where time is stolen and commodified, Newton’s Cradle follows one woman’s journey to uncover the truth behind a system built on control. The Newton’s Cradle, a seemingly innocuous object, becomes a powerful symbol of the choices we make and the hope for a restored balance. This cautionary tale challenges us to reflect on what truly matters in the moments we have.

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Jeff_synthesized

26,728 views • 1 year ago

Dragonfly's Haseeb Qureshi ＞|＜ reveals how GLM 5.3 Abliterated could unlock a new era of AI cyber attacks by training away the model's refusal behavior: "The models are just now getting good enough. Especially open source. For the frontier models, you used to be able to jailbreak them enough to be able to do these kinds of malicious activities, but their safety guardrails have improved dramatically over the last year or two." "But now we have open models. There was a model released yesterday which is an abliteration of GLM 5.3. Abliteration is when you take a model and fine-tune it against the refusal direction, which gets the model to refuse less and less, which ultimately gets you something close to an unrestricted or uncensored model." "So they did that to GLM 5.3, which means this abliterated version will just hack things. It will just do whatever GLM 5.3 will refuse to do. You lose some performance, but this is kind of a killing machine. If you wanna just let this loose on cyber attacks, that's what you use, and that was just released open weights yesterday." "You will see a lot more of this. This is not the end. This is only the beginning of where this is going."

Dragonfly's Haseeb Qureshi ＞|＜ reveals how GLM 5.3 Abliterated could unlock a new era of AI cyber attacks by training away the model's refusal behavior: "The models are just now getting good enough. Especially open source. For the frontier models, you used to be able to jailbreak them enough to be able to do these kinds of malicious activities, but their safety guardrails have improved dramatically over the last year or two." "But now we have open models. There was a model released yesterday which is an abliteration of GLM 5.3. Abliteration is when you take a model and fine-tune it against the refusal direction, which gets the model to refuse less and less, which ultimately gets you something close to an unrestricted or uncensored model." "So they did that to GLM 5.3, which means this abliterated version will just hack things. It will just do whatever GLM 5.3 will refuse to do. You lose some performance, but this is kind of a killing machine. If you wanna just let this loose on cyber attacks, that's what you use, and that was just released open weights yesterday." "You will see a lot more of this. This is not the end. This is only the beginning of where this is going."

MTS

17,726 views • 1 month ago

During the Artemis II mission, astronauts had a fun time playing around with water in the weightlessness of space. Artemis II was @CSA_ASC astronaut Jeremy R. Hansen's first spaceflight — so his crewmates taught him a lot about the physics of water in space.

During the Artemis II mission, astronauts had a fun time playing around with water in the weightlessness of space. Artemis II was @CSA_ASC astronaut Jeremy R. Hansen's first spaceflight — so his crewmates taught him a lot about the physics of water in space.

NASA Artemis

730,918 views • 5 months ago

glm 5.3 vs qwen 3.8 vs gemini 3.7 vs deepseek v4 flash four models designed and built three structures each on a physics-backed site, with no dimensions anywhere in the brief the setup: our own agent loop on OpenRouter, a construction site as the tool set – footings, walls, arches, roofs, scaffold, a lamp. the site enforces physics and nothing else: unsupported brick falls, a roof needs walls under it, a worker reaches 3.2 m above whatever he stands on, an arch needs centring until the keystone is set, concrete cures before it carries. no budget ceiling – material cost is tallied and reported, never blocked. tasks: 1. house – a plot and a palette, no plan. shape, height and material are the model's call 2. lighthouse – a headland cut by a gully, with a rock stack standing 30 m offshore. the lamp must burn, it must be the highest thing built, and the keeper must be able to walk to it 3. bridge – a river with one islet and banks at different heights. cross it however you want models: Z.ai glm 5.3 flash, Qwen qwen 3.8 flash, Google DeepMind gemini 3.7 flash, DeepSeek v4 flash vision all twelve objects were finished and signed off by the models themselves. tallest lighthouse is qwen's at 38.4 m, planted on the offshore stack with a bridge run out to it – the only model that read the site that way. deepseek signed off its bridge on an empty riverbed: 0 bricks, 107 minutes, $1.16m of material tallied - total cost, three builds #1 glm 5.3 flash – $0.201 #2 gemini 3.7 flash – $0.871 #3 qwen 3.8 flash – $1.058 #4 deepseek v4 flash – $1.567 - wall clock, three builds #1 gemini 3.7 flash – 91m #2 glm 5.3 flash – 228m #3 deepseek v4 flash – 502m #4 qwen 3.8 flash – 912m - total tokens #1 gemini 3.7 flash – 3,567,052 #2 glm 5.3 flash – 4,732,748 #3 qwen 3.8 flash – 13,469,333 #4 deepseek v4 flash – 18,230,076 - defects logged by the site #1 deepseek v4 flash – 59 #2 gemini 3.7 flash – 132 #3 glm 5.3 flash – 221 #4 qwen 3.8 flash – 350 - material tallied across three builds #1 gemini 3.7 flash – $359,884 #2 glm 5.3 flash – $583,358 #3 deepseek v4 flash – $1,327,484 #4 qwen 3.8 flash – $2,188,625 observations: • glm is the cheap one and nothing here is close – $0.201 for three buildings, $0.042 per million tokens, 6x under gemini's rate • what glm spends it on is bulk, not care: 166,228 bricks in one house and 156 defect weight, the worst single object in the set • gemini is the efficiency line – 91 minutes and 3.57m tokens for all three and an eighth of qwen's clock • gemini also builds the smallest of everything. its lighthouse is 22.5 m against qwen's 38.4, its house 6.9 m against 19.3 • qwen is the maximalist: 1.18m bricks, $2.19m of material, tallest on all three tasks, and 912 minutes – 15 hours – to get there conclusion: twelve finished objects for $3.80 all in, and a 7.8x price spread between the cheapest model and the priciest! follow thehype. for 24/7 ai news, analysis and breakdowns

glm 5.3 vs qwen 3.8 vs gemini 3.7 vs deepseek v4 flash four models designed and built three structures each on a physics-backed site, with no dimensions anywhere in the brief the setup: our own agent loop on OpenRouter, a construction site as the tool set – footings, walls, arches, roofs, scaffold, a lamp. the site enforces physics and nothing else: unsupported brick falls, a roof needs walls under it, a worker reaches 3.2 m above whatever he stands on, an arch needs centring until the keystone is set, concrete cures before it carries. no budget ceiling – material cost is tallied and reported, never blocked. tasks: 1. house – a plot and a palette, no plan. shape, height and material are the model's call 2. lighthouse – a headland cut by a gully, with a rock stack standing 30 m offshore. the lamp must burn, it must be the highest thing built, and the keeper must be able to walk to it 3. bridge – a river with one islet and banks at different heights. cross it however you want models: Z.ai glm 5.3 flash, Qwen qwen 3.8 flash, Google DeepMind gemini 3.7 flash, DeepSeek v4 flash vision all twelve objects were finished and signed off by the models themselves. tallest lighthouse is qwen's at 38.4 m, planted on the offshore stack with a bridge run out to it – the only model that read the site that way. deepseek signed off its bridge on an empty riverbed: 0 bricks, 107 minutes, $1.16m of material tallied - total cost, three builds #1 glm 5.3 flash – $0.201 #2 gemini 3.7 flash – $0.871 #3 qwen 3.8 flash – $1.058 #4 deepseek v4 flash – $1.567 - wall clock, three builds #1 gemini 3.7 flash – 91m #2 glm 5.3 flash – 228m #3 deepseek v4 flash – 502m #4 qwen 3.8 flash – 912m - total tokens #1 gemini 3.7 flash – 3,567,052 #2 glm 5.3 flash – 4,732,748 #3 qwen 3.8 flash – 13,469,333 #4 deepseek v4 flash – 18,230,076 - defects logged by the site #1 deepseek v4 flash – 59 #2 gemini 3.7 flash – 132 #3 glm 5.3 flash – 221 #4 qwen 3.8 flash – 350 - material tallied across three builds #1 gemini 3.7 flash – $359,884 #2 glm 5.3 flash – $583,358 #3 deepseek v4 flash – $1,327,484 #4 qwen 3.8 flash – $2,188,625 observations: • glm is the cheap one and nothing here is close – $0.201 for three buildings, $0.042 per million tokens, 6x under gemini's rate • what glm spends it on is bulk, not care: 166,228 bricks in one house and 156 defect weight, the worst single object in the set • gemini is the efficiency line – 91 minutes and 3.57m tokens for all three and an eighth of qwen's clock • gemini also builds the smallest of everything. its lighthouse is 22.5 m against qwen's 38.4, its house 6.9 m against 19.3 • qwen is the maximalist: 1.18m bricks, $2.19m of material, tallest on all three tasks, and 912 minutes – 15 hours – to get there conclusion: twelve finished objects for $3.80 all in, and a 7.8x price spread between the cheapest model and the priciest! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

26,360 views • 1 month ago

A British startup has designed a microgravity exercise device designed to help astronauts stay fit in space, and has tested the machine with the support of the European Space Agency and the UK Space Agency

A British startup has designed a microgravity exercise device designed to help astronauts stay fit in space, and has tested the machine with the support of the European Space Agency and the UK Space Agency

Reuters

82,593 views • 6 months ago

I was skeptical about giving GLM-5.2 the task to build a super mario snes style game in a single HTML file so i ran the test on Opus and also on GLM-5.2 Opus didnt even try to make a game or made something but it wasn't a game GLM-5.2 one shotted a pretty functional game.. WILD

I was skeptical about giving GLM-5.2 the task to build a super mario snes style game in a single HTML file so i ran the test on Opus and also on GLM-5.2 Opus didnt even try to make a game or made something but it wasn't a game GLM-5.2 one shotted a pretty functional game.. WILD

Hermes Agent Tips

32,883 views • 3 months ago

GLM 5.3 is surprisingly very good @ 3D representation & modeling, despite being blind Plugged it in to our Lucky Robots mujoco asset gen system, asked for a Kubota tractor with an articulating front loader and bucket w/ a rotary cutter 2nd image shows all the composite parts

GLM 5.3 is surprisingly very good @ 3D representation & modeling, despite being blind Plugged it in to our Lucky Robots mujoco asset gen system, asked for a Kubota tractor with an articulating front loader and bucket w/ a rotary cutter 2nd image shows all the composite parts

Harrison Kinsley

14,242 views • 1 month ago

GLM-5.3 Flash in already nerfed? I compared Ox Alpha in it's prime vs today just before it got revealed as GLM-5.3 Flash using the same prompt to build 3d raptor engine using three.js OxAlpha on 24th August gave far more accurate output compared to today which looks way worse prompt i used: Create a 3d SpaceX raptor engine using three.js, use white theme background so the main object is clearly visible

GLM-5.3 Flash in already nerfed? I compared Ox Alpha in it's prime vs today just before it got revealed as GLM-5.3 Flash using the same prompt to build 3d raptor engine using three.js OxAlpha on 24th August gave far more accurate output compared to today which looks way worse prompt i used: Create a 3d SpaceX raptor engine using three.js, use white theme background so the main object is clearly visible

Tim Jayas

82,975 views • 1 month ago