GLM-5.3 vs GLM-5.2: build your own landing page @Zai_org says their new model is built to code — so we ran a head-to-head. Both models got the exact same brief: build a landing page for yourself, one self-contained HTML file each. The typing terminal, the springy benchmark charts, the working tabs and FAQ, the 3D backgrounds — all their own code. No frameworks, no templates. GLM-5.3: 161,971 tokens, $0.80. GLM-5.2: 197,853 tokens, $0.98.

NVIDIA's new 3B model just turned coffee stains into planets Nemotron 3.5 Lightning dropped today: a 30B mixture-of-experts model with only 3B active parameters, a 1M-token context window, and open weights. NVIDIA claims up to 4x faster output than competing models in its class — light enough to run on a single GPU! We put it through our napkin benchmark: the model gets a photo of a napkin with three coffee ring stains and one prompt — turn the stains into an animated drawing, one self-contained HTML file. Output: 9,600 tokens The model read the position and size of every stain and drew a planet exactly over each ring — one with orbiting moons, one with an asteroid field, one big and glowing. Then it added a pencil that sketches them in, stroke by stroke. No missed rings, no misaligned circles — the stains became the planets Nemotron 3.5 Lightning is already live on aimlapi{.}com for FREE

Grok 4.5 just beat Kimi K3 at 13x cheaper price! $0.15 vs $1.98 — same task, same prompt, one shot. We'll miss Nikita Bier — the best Head of Product X ever had. So we had four models honor him the only way AI can: by building a 3D plush Nikita Boar in his signature suit 🐗 Cost per figure: Grok 4.5 — $0.15 GPT 5.6 Sol — $0.60 Qwen 3.8 Max — $0.67 Kimi K3 — $1.98 Kimi spent ~19 minutes thinking and billed 13x more. Grok just shipped. Everyone argues about which model is smartest. Nobody checks the receipt. And then we made the hogs dance with Grok 🕺 All four models, one API key — AI/ML API, 1000+ models.

Ling-3.0-flash is live on AI/ML API 💎 Created by @AntLingAGI , Ling-3.0-flash is a hybrid-reasoning MoE built for production-scale agents, delivering flagship-level results at a fraction of the compute. Try it for free until August 6:

We've tested the Qwen 3.8 Max preview and it absolutely rocks! Each scene is built in one shot, a single Three.js file with nothing else added: • Odysseus' war galley riding the waves • Trojan horse • Greek war helmet Qwen managed to execute the task faster than the other models, while output quality is relatively the same across all of them. If the pricing stays close to Alibaba's previous flagships, we'll get one of the best speed/quality ratios on the market — perfect for running agents at scale. Soon live on AI/ML API.

Yup, a football video. The World Cup made us do it Luma rebuilt image generation from scratch — reasoning first, pixels second. And it beats Google's Nano Banana 2 and GPT Image 1.5 on reasoning benchmarks All 3 new models are now live on AI/ML API luma/uni-1 plans before it draws. The model generates autoregressively: it works out layout, composition and text placement first, then renders the pixels. $0.052/image luma/uni-1-max — same prompts, same params, max fidelity. 2K output + editing with up to 9 reference images. Built for hero shots and ad creative. $0.13/image luma/ray-3-2 — up to 16 keyframes per clip, 20s, 1080p, native HDR + 16-bit EXR export. The video in this post came straight out of it model ids "luma/uni-1" "luma/uni-1-max" "luma/ray-3-2" @LumaLabsAI cooked. We serve

kimi k3 vs gpt 5.6 sol vs fable 5 vs grok 4.5 @Kimi_Moonshot just dropped kimi k3 – a 2.8t param native multimodal model, the first open 3t-class release. key facts: • 1m token context. stable latentmoe activating 16 of 896 experts, built on kimi delta attention (kda) and attention residuals • quantization-aware training from the sft stage onward – mxfp4 weights, mxfp8 activations. moonshot claims ~2.5x scaling efficiency over k2 • max thinking effort by default. low- and high-effort modes are "coming in updates" – there is no way to turn the thinking down today, and you feel it in every run • pricing: $0.30/mtok cache-hit input, $3.00/mtok cache-miss, $15.00/mtok output. claims >90% cache hit rate on coding workloads • benchmarks: swe marathon 42.0 (1st – fable 5: 35.0, sol: 39.0, opus 4.8: 40.0), terminal bench 2.1 88.3, browsecomp 91.2 (1st), program bench 77.8 (1st), gpqa-diamond 93.5. loses frontierswe 81.2 vs fable's 86.6, and deepswe 67.5 vs sol's 73.0 our test – 3 prompts, single-file html, @threejs, fully procedural, no assets: 1. photorealistic european roulette wheel – 37 pockets in the real sequence, mahogany clearcoat bowl, chrome turret, diamond deflectors, flick-to-spin, ball that spirals inward and settles on a mathematically real number 2. las vegas slot machine – 3 reels behind transmissive glass, drag the chrome lever to play, mechanical odometer counters modelled in 3d, coin physics on win 3. full pinball table – 6.5° tilted playfield, flipper impulse physics, spline ramps, drop targets, 6 bumpers, mechanical score reels in the backbox we ran the test on @aimlapi platform results: - cost #1# grok 4.5 – $0.30 #2# kimi k3 – $0.71 #3# gpt 5.6 sol – $2.05 #4# fable 5 – $7.69 - tokens #1# grok 4.5 – 34,241 #2# gpt 5.6 sol – 51,748 #3# fable 5 – 144,126 #4# kimi k3 – 157,999 - lines of code #1# gpt 5.6 sol – 3,054 #2# grok 4.5 – 3,047 #3# kimi k3 – 2,255 #4# fable 5 – 1,950 - generation time #1# grok 4.5 – 5.1 min #2# gpt 5.6 sol – 22.0 min #3# fable 5 – 31.5 min #4# kimi k3 – 75.6 min observations: • kimi k3 is cheap and it is slow. 75.6 minutes across three prompts against grok's 5.1. it is 2.4x grok's price and 15x grok's wall clock. the roulette took 15 min, the slot 18, the pinball 42 • it failed 2 of 3. only the roulette works. the slot machine has reel cutouts on both faces of the cabinet and the symbols face backwards – you can only read your spin by walking around to the rear of the machine. the pinball table stands vertically on its edge with the legs floating detached beside it. • 81% of kimi's output tokens are reasoning, not code. grok: 22%. you are not paying for a bigger answer, you are paying for a longer argument with itself • price per 100 shipped lines – grok $0.010, kimi $0.031, sol $0.067, fable $0.394. a 39x spread for the same three files kimi k3's code quality: upsides: • the roulette is genuinely good – procedural wood grain with real specular breakup, correct european sequence (0-32-15-19-4...), chrome turret, diamond deflectors, clean console • the pinball artwork is the best in the test – a synthwave "nova strike / deep space" field with six individually coloured neon bumper rings, a retro sun on a grid horizon, a nova burst, and a scoring legend printed on the apron. no other model printed the rules on the machine. it is a beautiful texture on a broken object • physics reasoning is real – it derived a 480hz substep for the collider, worked out ball settle conditions and termination guarantees, and checked every ramp exit vector by hand before writing any of it • it is the only model that saw the importmap trap coming. sol shipped a blank white page twice because three.js addons import the bare specifier 'three' and die without an import map downsides: • it dodged that trap on the slot by loading three.js r128 through classic script tags – a 2021 build with no working transmission. its slot glass rendered fully opaque and buried all three reels behind a white pane. the code asks for transmission: 0.93, ior: 1.5 – correct, and silently ignored by a renderer that predates the feature • after 42 minutes and 212k characters of reasoning, the pinball cabinet is not assembled. the table stands vertically on its edge like a wardrobe – the prompt asked for 6.5° from horizontal, it delivered 90°. the legs float detached in the void beside it. head-on it photographs beautifully; orbit ten degrees and it is a painted slab with four chrome rods hovering nearby • the playfield z-fights with the glass – hard black banding across the whole field as soon as you pull the camera back a note on the pinball, in fairness to kimi: nobody passed it. every model shipped broken ball physics and controls you cannot trust. it is the hardest prompt we have run and the whole field failed it, each in its own way kimi k3 reasons better than anything else here and it shows exactly where reasoning pays – physics constants, sequences, edge cases, traps the others walked into follow @thehypedotnews for 24/7 ai news, analysis and breakdowns