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This is f*cking Dangerous Cline opened Gemini 3.8 Flash, DeepSeek V4.1 Flash, and three more for free no API key, right inside VS Code and your terminal pick a free model from the dropdown and start coding, debugging, and running terminal commands without ever touching a billing page what...

264,070 просмотров • 1 день назад •via X (Twitter)

Комментарии: 14

Фото профиля Rivon
Rivon1 день назад

Tg channel :

Фото профиля CDG
CDG1 день назад

damn, no billing?

Фото профиля Rivon
Rivon1 день назад

Yess sir

Фото профиля Ahmer
Ahmer23 часов назад

Cline makes experimenting with powerful AI coding models easier

Фото профиля Psycho
Psycho1 день назад

is that stealth model also on cline??

Фото профиля Blog2Video.ai
Blog2Video.ai1 день назад

Zero billing is insane, just watch the context limits

Фото профиля Israfil
Israfil1 день назад

already using it since 2 days

Фото профиля Robin | Poker x AI
Robin | Poker x AI1 день назад

Looks like a solid hack, love the zero billing flow, but any hint on latency when you swap models?

Фото профиля 𝐑𝐢𝐫𝐢👾
𝐑𝐢𝐫𝐢👾1 день назад

definitely testing this before the free tiers change

Фото профиля Nahid
Nahid1 день назад

tried it, quota gone in 20 min

Фото профиля Trn
Trn1 день назад

This is actually wild

Фото профиля Haleemah
Haleemah1 день назад

Cline has become my go to for some models

Фото профиля JOY
JOY1 день назад

cool man

Фото профиля J.𝙳𝚛𝚊𝚟𝚎𝚗
J.𝙳𝚛𝚊𝚟𝚎𝚗1 день назад

No doubt it's wild

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

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union alpha (unbiased pareto) vs deepseek v4.1 flash vs muse spark 1.3 – three paintings in three.js the setup: one four-line prompt plus the painting as an image, through OpenRouter. no agent loop, no renders, no feedback – the model writes one html file blind and we open it. Three.js from a cdn, every texture generated in code. when a provider cut the stream early we sent the partial back and said continue exactly where you stopped tasks: 1. the starry night – van gogh, 1889 2. the persistence of memory – dalí, 1931 3. poppies at argenteuil – monet, 1873 two rules in every brief: keep the painting's palette, brushwork and mood, and reply with the code only models: Unbiased AI union alpha (stealth, free), DeepSeek deepseek v4.1 flash, AI at Meta muse spark 1.3 total cost, three scenes #1 union alpha – free (list price: $1.04) #2 muse spark 1.3 – $0.117 #3 deepseek v4.1 flash – $0.162 generation time, three scenes #1 muse spark 1.3 – 4m 45s #2 deepseek v4.1 flash – 11m 30s #3 union alpha – 29m 13s total completion tokens #1 muse spark 1.3 – 26,502 #2 union alpha – 123,756 #3 deepseek v4.1 flash – 156,028 lines of code shipped #1 muse spark 1.3 – 862 #2 union alpha – 1,715 #3 deepseek v4.1 flash – 2,816 observations: • union alpha reads the painting like an art historian. it named every work unprompted, then broke each into parts: dalí's watches deformed along a bezier curve, monet's poppies as instanced brush dabs under a wind shader. no other model went that deep on a one-shot • it is the only model that made the paintings move the way they were painted. in the monet, the woman and the child walk the field on catmull-rom paths, pollen drifts, poppies are brush dabs in a point shader that sway in the wind. deepseek and muse left the figures standing • its dalí is an inventory of the canvas: three soft clocks draped along one parametric curve, a drip falling off the hanging one, a fly, ants on the pocket watch as an instanced mesh. 17 named parts in all. nobody else drew the drip • its starry night is shader work end to end: shared glsl noise, a vortex field for the sky, billboarded shader quads for the moon and stars, a painterly surface shader for the hills, and windows that flicker on their own timers. the file reads like a demoscene entry, not a model output what union alpha is: • we asked it. the stealth window had closed a day after launch and the api answered: "this model was unbiased's pareto". pareto is from circuit & chisel, an ex-stripe team that raised $19.2m in sep 2025 per fortune, and now sells "frontier intelligence for 75% less" • pareto is not one model. per unbiased's site it "runs a mix of frontier and open source models against each other on every request" and keeps the best answer. that is the 300-second first token, the tokenizer listed as "other", and the missing reasoning field – a race, not a model • listed at $2.50 in and $7.50 out per million. our three scenes would have cost $1.04 – 6.4x deepseek, 8.9x muse. asked for its cutoff, it dated nothing past may 2025 follow thehype. for 24/7 ai news, analysis and breakdowns

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23,479 просмотров • 11 дней назад

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

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