Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

We ran a test between GPT-5.6 Sol, Kimi K3, and Gemini 3.6 Flash. One prompt. Across all three models. Using our /design command. Results (gameplay, UX, and UI): 🔹 Kimi K3 performed well across all three. 🔹 GPT-5.6 Sol is good, but it gets annoying when the ball hits...

CommandCodeAI's profile picture

Command Code

18,594 subscribers

61,412 Aufrufe • vor 1 Monat •via X (Twitter)

Wissenschaft & TechnologieGaming
LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Kimi K3 vs GPT-5.6 Sol vs Fable 5 Three top-tier models. Same /design prompt across all. Parameters reviewed: Pace, design sense, gameplay feel Result: Kimi K3 nails the design sense and knows exactly what to add in-game. Pace and gameplay held up well. Fable 5 and GPT-5.6 Sol both play too fast, video isn't sped up. Ranking (DX, Features & Cost): → Kimi K3: 9.5/10 · $0.030 → Fable 5: 7.5/10 · $0.38 → GPT-5.6 Sol: 7/10 · $0.11
0:28

Kimi K3 vs GPT-5.6 Sol vs Fable 5 Three top-tier models. Same /design prompt across all. Parameters reviewed: Pace, design sense, gameplay feel Result: Kimi K3 nails the design sense and knows exactly what to add in-game. Pace and gameplay held up well. Fable 5 and GPT-5.6 Sol both play too fast, video isn't sped up. Ranking (DX, Features & Cost): → Kimi K3: 9.5/10 · $0.030 → Fable 5: 7.5/10 · $0.38 → GPT-5.6 Sol: 7/10 · $0.11

Command Code

376,967 Aufrufe • vor 1 Monat

I gave Kimi K3, Gemini 3.7 Flash, GPT 5.6 Sol, and Claude Opus 5 a dice and asked them to draw a herbivorous animal integrated with it here's how they imagined the animal fused with the dice
0:21

I gave Kimi K3, Gemini 3.7 Flash, GPT 5.6 Sol, and Claude Opus 5 a dice and asked them to draw a herbivorous animal integrated with it here's how they imagined the animal fused with the dice

Ann Nguyen

407,963 Aufrufe • vor 6 Tagen

I gave a lil slice of lime and asked Gemini 3.7 Flash, Kimi K3, Claude Opus 5, and GPT 5.6 Sol to draw a human pose integrated with the object and here is how the human pose looks through their eyes 😆
0:24

I gave a lil slice of lime and asked Gemini 3.7 Flash, Kimi K3, Claude Opus 5, and GPT 5.6 Sol to draw a human pose integrated with the object and here is how the human pose looks through their eyes 😆

Ann Nguyen

575,587 Aufrufe • vor 11 Tagen

🤯Kimi K3 mogs GPT-5.6 Sol on frontend design The features are similar but Kimi has much better taste and 3D capabilities. The design overall is also way better and more elegant on Kimi's side. open-source has a really bright future
0:29

🤯Kimi K3 mogs GPT-5.6 Sol on frontend design The features are similar but Kimi has much better taste and 3D capabilities. The design overall is also way better and more elegant on Kimi's side. open-source has a really bright future

filipe

137,563 Aufrufe • vor 1 Monat

Just tested Kimi.ai K3 against GPT-5.6 and Grok 4.5 on the same task: build a Subway Surfers game. Kimi K3 was my favorite. Better UI, smoother gameplay, and the overall experience felt more polished. GPT-5.6 was solid too, while Grok 4.5 fell behind on the UI. The interesting part is that all three needed at least one follow-up prompt. Kimi also took a bit longer to generate, but the extra time paid off. Ran Kimi K3 through Nebius Token Factory. Low inference cost + a really capable open source model is a great combo.
0:42

Just tested Kimi.ai K3 against GPT-5.6 and Grok 4.5 on the same task: build a Subway Surfers game. Kimi K3 was my favorite. Better UI, smoother gameplay, and the overall experience felt more polished. GPT-5.6 was solid too, while Grok 4.5 fell behind on the UI. The interesting part is that all three needed at least one follow-up prompt. Kimi also took a bit longer to generate, but the extra time paid off. Ran Kimi K3 through Nebius Token Factory. Low inference cost + a really capable open source model is a great combo.

Arindam Majumder 𝕏

46,107 Aufrufe • vor 1 Monat

Kimi K3 just 3 shotted a whole walkable voxel town with drivable cars — Voxelville, around $3.24 in API usage. The same token cost would be $10.80 with Fable 5 and $6 with GPT 5.6 Sol. Fable 5 built its own Maplewood, GPT 5.6 Sol built Willowwick, but on price/quality Kimi K3 just cooked both of them. The era of free indie game development is closer than you think!
0:28

Kimi K3 just 3 shotted a whole walkable voxel town with drivable cars — Voxelville, around $3.24 in API usage. The same token cost would be $10.80 with Fable 5 and $6 with GPT 5.6 Sol. Fable 5 built its own Maplewood, GPT 5.6 Sol built Willowwick, but on price/quality Kimi K3 just cooked both of them. The era of free indie game development is closer than you think!

Kirill

63,180 Aufrufe • vor 1 Monat

I used Fable 5 to bring Command & Conquer: Red Alert 2 + Yuri's Revenge to the iPhone and iPad! EA never released RA2's source, so there was nothing to port. Gemini 3.6 Flash play-tested it for hours, GPT-5.6 Sol rebuilt the skirmish AI. Open sourcing it all below
0:26

I used Fable 5 to bring Command & Conquer: Red Alert 2 + Yuri's Revenge to the iPhone and iPad! EA never released RA2's source, so there was nothing to port. Gemini 3.6 Flash play-tested it for hours, GPT-5.6 Sol rebuilt the skirmish AI. Open sourcing it all below

Ammaar Reshi

278,270 Aufrufe • vor 20 Tagen

DeepSeek V4 Flash completely failed this test. Compared to Opus 4.8, GPT-5.6 Sol, Kimi K3, and the other current top models, it’s honestly not good. The gap is massive. Against Luna, however, it performs similarly well. Both have different strengths and weaknesses, so I still need to test them more. The weird part: the Pi harness performed worse than OpenCode for DeepSeek. More tests are coming, guys. Don’t worry
0:38

DeepSeek V4 Flash completely failed this test. Compared to Opus 4.8, GPT-5.6 Sol, Kimi K3, and the other current top models, it’s honestly not good. The gap is massive. Against Luna, however, it performs similarly well. Both have different strengths and weaknesses, so I still need to test them more. The weird part: the Pi harness performed worse than OpenCode for DeepSeek. More tests are coming, guys. Don’t worry

OmedTheVibeCoder

25,980 Aufrufe • vor 28 Tagen

Who said LLMs can only generate text? I gave 5 frontier models the ABC notation of Canon in D (the fast part) and asked each to play it in their own style. > GPT 5.6, Fable 5 & Opus 5 extended it and wrote their own endings > Gemini 3.6 Flash kept the notes, swapped the instruments > Kimi K3 rewrote the whole thing My pick: Fable's version sounds surprisingly rich. Opus's version is great too. Sound on 🔊
1:47

Who said LLMs can only generate text? I gave 5 frontier models the ABC notation of Canon in D (the fast part) and asked each to play it in their own style. > GPT 5.6, Fable 5 & Opus 5 extended it and wrote their own endings > Gemini 3.6 Flash kept the notes, swapped the instruments > Kimi K3 rewrote the whole thing My pick: Fable's version sounds surprisingly rich. Opus's version is great too. Sound on 🔊

stevibe

11,961 Aufrufe • vor 1 Monat

CLAUDE OPUS 5, GPT-5.6 SOL AND KIMI K3 ARE ALL SITTING IN A FREE TIER WITH 7 MILLION TOKENS A DAY • NaraRouter, the gateway > 7M tokens every 24 hours, no card, no subscription: > Claude Opus 5, Sonnet 5 and Fable 5, GPT-5.6 Sol, Terra and Luna, Kimi K3, Qwen3.8 Max, GLM 5.2, DeepSeek V4 Pro and MiniMax M3. > Anthropic-compatible /v1/messages alongside the OpenAI route, so it drops into Claude Code without a proxy. • the multiplier is the real price list > Each model drains the allowance at its own rate -- Sol at 4x, DeepSeek V4 Pro at 3x, Kimi K3 at 1.5x. > Opus 5, Sonnet 5, Fable 5 and Luna carry no multiplier at all. So 7M on Luna is 7M, and 7M on Sol is closer to 1.75M -> pick by the badge, not by the name. Sign up with Google, copy the key once, point your base url at and you are running ↓
0:28

CLAUDE OPUS 5, GPT-5.6 SOL AND KIMI K3 ARE ALL SITTING IN A FREE TIER WITH 7 MILLION TOKENS A DAY • NaraRouter, the gateway > 7M tokens every 24 hours, no card, no subscription: > Claude Opus 5, Sonnet 5 and Fable 5, GPT-5.6 Sol, Terra and Luna, Kimi K3, Qwen3.8 Max, GLM 5.2, DeepSeek V4 Pro and MiniMax M3. > Anthropic-compatible /v1/messages alongside the OpenAI route, so it drops into Claude Code without a proxy. • the multiplier is the real price list > Each model drains the allowance at its own rate -- Sol at 4x, DeepSeek V4 Pro at 3x, Kimi K3 at 1.5x. > Opus 5, Sonnet 5, Fable 5 and Luna carry no multiplier at all. So 7M on Luna is 7M, and 7M on Sol is closer to 1.75M -> pick by the badge, not by the name. Sign up with Google, copy the key once, point your base url at and you are running ↓

slash1s

43,053 Aufrufe • vor 19 Tagen

New Kimi K3 beat Opus 4.8 at making retro games for 2x cheaper! We gave three models the same task: make three old arcade games that play by themselves. Each game is one HTML file with a bot that plays it Prompts: – Road Fighter – Battle City – Q*bert Outputs: Kimi K3: 18.4K tokens, $0.28 GPT-5.6: 18.1K tokens, $0.28 Opus 4.8: 21.3K tokens, $0.54 Kimi K3 made the best games. Its Q*bert is the best of all three. The player jumps on the cubes, paints them and runs from the purple snake. Its Battle City looks just like the real game and plays right. The tanks move, aim, shoot and break the walls. GPT-5.6 could not handle the cars. Its Battle City broke too. The tank died on its own and the base got hit. But GPT had the nicest textures of the three
0:27

New Kimi K3 beat Opus 4.8 at making retro games for 2x cheaper! We gave three models the same task: make three old arcade games that play by themselves. Each game is one HTML file with a bot that plays it Prompts: – Road Fighter – Battle City – Q*bert Outputs: Kimi K3: 18.4K tokens, $0.28 GPT-5.6: 18.1K tokens, $0.28 Opus 4.8: 21.3K tokens, $0.54 Kimi K3 made the best games. Its Q*bert is the best of all three. The player jumps on the cubes, paints them and runs from the purple snake. Its Battle City looks just like the real game and plays right. The tanks move, aim, shoot and break the walls. GPT-5.6 could not handle the cars. Its Battle City broke too. The tank died on its own and the base got hit. But GPT had the nicest textures of the three

atomic.chat

100,082 Aufrufe • vor 1 Monat

Qwen 3.8 will be benchmaxxed slop second to fable 5 is such a hype statement , its not even close to kimi k3 and GPT-5.6 sol you can test it yourself on the qwen chat website currently available > token hungry > not that good as advertised , will test more The best part of kimi was that in blog they themselves wrote its not comparable to fable 5 and sol 5.6 in bunch of user experience stuff We need more truth like this in our industry , other than that i will run my vision test
0:22

Qwen 3.8 will be benchmaxxed slop second to fable 5 is such a hype statement , its not even close to kimi k3 and GPT-5.6 sol you can test it yourself on the qwen chat website currently available > token hungry > not that good as advertised , will test more The best part of kimi was that in blog they themselves wrote its not comparable to fable 5 and sol 5.6 in bunch of user experience stuff We need more truth like this in our industry , other than that i will run my vision test

Chetaslua

127,047 Aufrufe • vor 1 Monat

qwen 3.8 max vs deepseek v4 flash 0731 vs kimi k3 vs gpt 5.6 sol – on rubik's cube and chess four frontier models built a rubik's cube stand and solved it, then built a chess board and played claude opus 5 on it the setup: Nous Research's hermes agent cli on OpenRouter tasks: 1. cube – build a 3d rubik's cube with a cli and a Three.js viewer, then solve an identical scrambled position on your own stand 2. chess – build a 3d chess stand, then play white against claude opus 5 as black, live, one move at a time. no engine, no solver, no opening book on either side. stockfish depth 14 grades every chess ply afterwards; neither player sees the score models: DeepSeek v4 flash 0731, OpenAI gpt-5.6 sol, Kimi.ai kimi k3, Qwen qwen 3.8 max gpt-5.6 sol and deepseek v4 flash solved their cubes – sol in 24 moves and seventeen seconds, deepseek in 32. qwen and kimi never got there, giving up at 96 and 207 moves then all four built chess stands and played white against claude opus 5 on them, and all four resigned: deepseek on move 13, sol on 19, kimi on 21, qwen holding out longest at 29 - build time, both stands #1 gpt-5.6 sol – 16m 43s #2 deepseek v4 flash – 97m 39s #3 kimi k3 – 166m 09s #4 qwen 3.8 max – 215m 08s - build attempts before a working stand #1 gpt-5.6 sol – 3 #2 qwen 3.8 max – 4 #3 kimi k3 – 4 #4 deepseek v4 flash – 5 - total tokens #1 gpt-5.6 sol – 6,713,754 #2 qwen 3.8 max – 17,272,507 #3 kimi k3 – 22,427,504 #4 deepseek v4 flash – 27,417,442 - total price #1 deepseek v4 flash – $0.557 #2 gpt-5.6 sol – $6.319 #3 qwen 3.8 max – $10.270 #4 kimi k3 – $16.667 observations: • deepseek v4 flash is the cheapest model here by a margin nobody else is near, and it got there while being the least efficient of the four. it burned 27.4m tokens – more than anyone, 5m more than kimi – and still finished both benchmarks for $0.557. that is $0.02 per million tokens against kimi's $0.74. it also needed the most passes to produce working stands, five, and that did not matter: all five deepseek passes together cost a thirtieth of kimi's two • so what deepseek cannot do is get it right the first time. what it can do is get it right the fifth time, for half a dollar. that is a different thing to be buying – not a good first draft, but the option to keep asking • gpt-5.6 sol is the opposite profile and the strongest of the four on pure efficiency. 16m 43s to build both stands, 6.7m tokens, three passes – under 40% of the next lowest token count and a quarter of deepseek's, on an eighth of qwen's clock. it also solved the cube fastest of anyone, 24 moves in seventeen seconds. sol is what you reach for when you want the answer now and can absorb $0.94 per million • sol's weakness is in what it does not check. its chess viewer deleted the capturing piece instead of the captured one, so pieces disappeared off the board mid-game – a defect the fifty-cent deepseek stand did not have. fast and terse turns out to be the same dial as fast and unverified • qwen 3.8 max is not the cheap open-weights option it gets treated as. $10.270 across the two benchmarks, second most expensive of the four, 18x deepseek, and by a distance the slowest – 215 minutes of build time, nearly thirteen times sol's. what the money buys is judgment: it played eighteen moves without a single error worth a hundredth of a pawn, then made exactly one bad move in the whole game, and averaged 44.6 centipawns lost across the longest game any of the four managed. it also could not solve a rubik's cube in 96 tries • kimi k3 is the one line with no reading that flatters it. most expensive at $16.667, last on the cube at 207 moves, last at chess at 478 centipawns lost per move. it is also the model that verified hardest – on the cube it wrote its own integrity check instead of trusting its output. that makes the result worse rather than better: the checking was real, and the reasoning underneath it still was not follow thehype. for 24/7 ai news, analysis and breakdowns
1:03

qwen 3.8 max vs deepseek v4 flash 0731 vs kimi k3 vs gpt 5.6 sol – on rubik's cube and chess four frontier models built a rubik's cube stand and solved it, then built a chess board and played claude opus 5 on it the setup: Nous Research's hermes agent cli on OpenRouter tasks: 1. cube – build a 3d rubik's cube with a cli and a Three.js viewer, then solve an identical scrambled position on your own stand 2. chess – build a 3d chess stand, then play white against claude opus 5 as black, live, one move at a time. no engine, no solver, no opening book on either side. stockfish depth 14 grades every chess ply afterwards; neither player sees the score models: DeepSeek v4 flash 0731, OpenAI gpt-5.6 sol, Kimi.ai kimi k3, Qwen qwen 3.8 max gpt-5.6 sol and deepseek v4 flash solved their cubes – sol in 24 moves and seventeen seconds, deepseek in 32. qwen and kimi never got there, giving up at 96 and 207 moves then all four built chess stands and played white against claude opus 5 on them, and all four resigned: deepseek on move 13, sol on 19, kimi on 21, qwen holding out longest at 29 - build time, both stands #1 gpt-5.6 sol – 16m 43s #2 deepseek v4 flash – 97m 39s #3 kimi k3 – 166m 09s #4 qwen 3.8 max – 215m 08s - build attempts before a working stand #1 gpt-5.6 sol – 3 #2 qwen 3.8 max – 4 #3 kimi k3 – 4 #4 deepseek v4 flash – 5 - total tokens #1 gpt-5.6 sol – 6,713,754 #2 qwen 3.8 max – 17,272,507 #3 kimi k3 – 22,427,504 #4 deepseek v4 flash – 27,417,442 - total price #1 deepseek v4 flash – $0.557 #2 gpt-5.6 sol – $6.319 #3 qwen 3.8 max – $10.270 #4 kimi k3 – $16.667 observations: • deepseek v4 flash is the cheapest model here by a margin nobody else is near, and it got there while being the least efficient of the four. it burned 27.4m tokens – more than anyone, 5m more than kimi – and still finished both benchmarks for $0.557. that is $0.02 per million tokens against kimi's $0.74. it also needed the most passes to produce working stands, five, and that did not matter: all five deepseek passes together cost a thirtieth of kimi's two • so what deepseek cannot do is get it right the first time. what it can do is get it right the fifth time, for half a dollar. that is a different thing to be buying – not a good first draft, but the option to keep asking • gpt-5.6 sol is the opposite profile and the strongest of the four on pure efficiency. 16m 43s to build both stands, 6.7m tokens, three passes – under 40% of the next lowest token count and a quarter of deepseek's, on an eighth of qwen's clock. it also solved the cube fastest of anyone, 24 moves in seventeen seconds. sol is what you reach for when you want the answer now and can absorb $0.94 per million • sol's weakness is in what it does not check. its chess viewer deleted the capturing piece instead of the captured one, so pieces disappeared off the board mid-game – a defect the fifty-cent deepseek stand did not have. fast and terse turns out to be the same dial as fast and unverified • qwen 3.8 max is not the cheap open-weights option it gets treated as. $10.270 across the two benchmarks, second most expensive of the four, 18x deepseek, and by a distance the slowest – 215 minutes of build time, nearly thirteen times sol's. what the money buys is judgment: it played eighteen moves without a single error worth a hundredth of a pawn, then made exactly one bad move in the whole game, and averaged 44.6 centipawns lost across the longest game any of the four managed. it also could not solve a rubik's cube in 96 tries • kimi k3 is the one line with no reading that flatters it. most expensive at $16.667, last on the cube at 207 moves, last at chess at 478 centipawns lost per move. it is also the model that verified hardest – on the cube it wrote its own integrity check instead of trusting its output. that makes the result worse rather than better: the checking was real, and the reasoning underneath it still was not follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

84,595 Aufrufe • vor 23 Tagen

Free is the part people are underpricing. Google just made Gemini 3.6 Flash the new default. Not a toy model hiding in a free tier. A near-frontier coding model normal users can try in Gemini and AI Studio without touching enterprise pricing. This is landing while people compare paid frontier APIs: > GPT-5.6 Sol at $5/$30 > Claude Sonnet 5 at $3/$15 > Grok 4.5 at $2/$6 > Gemini 3.5 Flash at $1.50/$9 Benchmarks matter. But a model people can actually use for free changes behavior faster than a model they only admire from pricing tables.
1:25

Free is the part people are underpricing. Google just made Gemini 3.6 Flash the new default. Not a toy model hiding in a free tier. A near-frontier coding model normal users can try in Gemini and AI Studio without touching enterprise pricing. This is landing while people compare paid frontier APIs: > GPT-5.6 Sol at $5/$30 > Claude Sonnet 5 at $3/$15 > Grok 4.5 at $2/$6 > Gemini 3.5 Flash at $1.50/$9 Benchmarks matter. But a model people can actually use for free changes behavior faster than a model they only admire from pricing tables.

ＺＥＦＩ

13,074 Aufrufe • vor 1 Monat

🚨 More DeepSeek V4 Pro GA Leaks and it's looking seriously impressive. It also looks like DeepSeek may have heavily distilled from Fable 5 the coding style, iteration behavior, and overall output feel very similar. It was tested it on the same prompt used for Kimi K3 and GPT-5.6 Sol, and the result had strong scene composition, solid environmental detail, and surprisingly good design choices. Still early, but this could become one of the most disruptive coding models yet. 👀🔥 cc huangserva
0:54

🚨 More DeepSeek V4 Pro GA Leaks and it's looking seriously impressive. It also looks like DeepSeek may have heavily distilled from Fable 5 the coding style, iteration behavior, and overall output feel very similar. It was tested it on the same prompt used for Kimi K3 and GPT-5.6 Sol, and the result had strong scene composition, solid environmental detail, and surprisingly good design choices. Still early, but this could become one of the most disruptive coding models yet. 👀🔥 cc huangserva

WorldofAI

28,089 Aufrufe • vor 1 Monat

Rockstar spent 7 years, 2,000+ developers, and $500 million to build Red Dead Redemption 2. Kimi K3 rebuilt the same scene in 10 hours. One prompt. 4 million tokens. It's open source. 2.8 trillion parameters. A 1 million token context window. It beats Claude Opus 4.8 and GPT-5.6. It sits on par with Fable 5. Fable 5 results, at Sonnet pricing. The wall between you and a AAA game used to be a studio. Now it's a prompt.
0:32

Rockstar spent 7 years, 2,000+ developers, and $500 million to build Red Dead Redemption 2. Kimi K3 rebuilt the same scene in 10 hours. One prompt. 4 million tokens. It's open source. 2.8 trillion parameters. A 1 million token context window. It beats Claude Opus 4.8 and GPT-5.6. It sits on par with Fable 5. Fable 5 results, at Sonnet pricing. The wall between you and a AAA game used to be a studio. Now it's a prompt.

Dep

99,354 Aufrufe • vor 1 Monat

KIMI K3 is here, and it blew my mind 🤯 yes, it is expensive and very slow Took over 30 minutes, and blew an ENTIRE $20 kimi sub before it even finished the one prompt for this game. BUT OMG... the output geniuinly has fable 5 level magic built into it, this model falls between gpt 5.6 and fable 5 imo. you can play the game at kimisurfers (dot) com right now, and see what I mean. This model is too expensive to replace fable 5, BUTT it shows that the chinese open source labs are CATCHING anthropic and open ai FASTTT.
1:19

KIMI K3 is here, and it blew my mind 🤯 yes, it is expensive and very slow Took over 30 minutes, and blew an ENTIRE $20 kimi sub before it even finished the one prompt for this game. BUT OMG... the output geniuinly has fable 5 level magic built into it, this model falls between gpt 5.6 and fable 5 imo. you can play the game at kimisurfers (dot) com right now, and see what I mean. This model is too expensive to replace fable 5, BUTT it shows that the chinese open source labs are CATCHING anthropic and open ai FASTTT.

Max Blade

128,924 Aufrufe • vor 1 Monat

you can now use Ox Alpha, Kimi K3, gemini 3.7 flash and 47 other models for FREEE with no credit card 😳 aihubmix just opened a 50-model free catalog, every model $0/M in and out. the models: -Ox Aplha -gemini-3.7-flash -glm-5.2 -kimi-k3 -minimax-m3 how to set it up (2 min): step 1: sign up at email or oauth, no card step 2: create an api key one key, all models, free and paid alike step 3: call any -free model base url: model: coding-glm-5.2-free, gpt-5.5-free, whatever that's it the free catalog is live in 2 minutes works in any openai-compatible tool. save this if you want a simple multi model setup later
0:31

you can now use Ox Alpha, Kimi K3, gemini 3.7 flash and 47 other models for FREEE with no credit card 😳 aihubmix just opened a 50-model free catalog, every model $0/M in and out. the models: -Ox Aplha -gemini-3.7-flash -glm-5.2 -kimi-k3 -minimax-m3 how to set it up (2 min): step 1: sign up at email or oauth, no card step 2: create an api key one key, all models, free and paid alike step 3: call any -free model base url: model: coding-glm-5.2-free, gpt-5.5-free, whatever that's it the free catalog is live in 2 minutes works in any openai-compatible tool. save this if you want a simple multi model setup later

painn

76,972 Aufrufe • vor 6 Tagen

Opus 5 crushed Fable 5 at 3D destruction physics for 2x cheaper! We gave four models the same task: build three self-contained HTML scenes with real physics Prompts: - A tornado that sucks in a whole field - A wrecking ball taking down an apartment block - An overloaded truck collapsing a truss bridge Outputs: - Opus 5: 55.9K tokens, $1.40 - Fable 5: 55.1K tokens, $2.82 - Kimi K3: 35.7K tokens, $0.55 - GPT 5.6: 20.1K tokens, $0.31 Opus got all three right unlike the other models. Houses fly up the funnel and out the top, the wall breaks where the ball hits and the rubble piles up, the bridge drops the truck into the river. Fable had almost nothing on the ground for the tornado to pick up, its building collapsed on its own before the ball even touched it and its bridge blew into sticks all at once. GPT is the cheapest here but its ball never reached the building at all and its bridge fell apart in a way nothing falls apart in real life. Kimi K3, the new Chinese frontier model, ended up in the same place as GPT
0:22

Opus 5 crushed Fable 5 at 3D destruction physics for 2x cheaper! We gave four models the same task: build three self-contained HTML scenes with real physics Prompts: - A tornado that sucks in a whole field - A wrecking ball taking down an apartment block - An overloaded truck collapsing a truss bridge Outputs: - Opus 5: 55.9K tokens, $1.40 - Fable 5: 55.1K tokens, $2.82 - Kimi K3: 35.7K tokens, $0.55 - GPT 5.6: 20.1K tokens, $0.31 Opus got all three right unlike the other models. Houses fly up the funnel and out the top, the wall breaks where the ball hits and the rubble piles up, the bridge drops the truck into the river. Fable had almost nothing on the ground for the tornado to pick up, its building collapsed on its own before the ball even touched it and its bridge blew into sticks all at once. GPT is the cheapest here but its ball never reached the building at all and its bridge fell apart in a way nothing falls apart in real life. Kimi K3, the new Chinese frontier model, ended up in the same place as GPT

atomic.chat

1,481,112 Aufrufe • vor 1 Monat