Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

DeepSeek V4.1 Flash vs Kimi K3 This is not one-shot from DeepSeek btw. The first result was boxy and not realistic, so I iterated with a $6 cap. Kimi did this in one shot, costing $6.95. Not as good as Kimi K3, but it did better than the other...

Bhavani_00007's profile picture

Bhavy☄️

7,146 subscribers

33,428 Aufrufe • vor 1 Tag •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

DeepSeek V4.1 Flash (High) vs Kimi K3 (Low) Same farming scene prompt. This is the result. > DeepSeek High took 1 min 15s and cost $0.45. > Kimi K3 took 2m 10s and cost $1.20. Almost as good as Kimi, but honestly, one of the best Flash models ever released.
0:33

DeepSeek V4.1 Flash (High) vs Kimi K3 (Low) Same farming scene prompt. This is the result. > DeepSeek High took 1 min 15s and cost $0.45. > Kimi K3 took 2m 10s and cost $1.20. Almost as good as Kimi, but honestly, one of the best Flash models ever released.

Bhavy☄️

55,814 Aufrufe • vor 1 Tag

GLM 5.3 Flash vs Kimi K3 tested both models on same prompt at highest reasoning available but results came out really different > 5.3 flash took 20 minutes to complete this and costed $0.7 via AIhubMix API > kimi k3 took 30 minutes to complete this and costed $4.32 via Kimi Plan which one do you think did better here?
0:39

GLM 5.3 Flash vs Kimi K3 tested both models on same prompt at highest reasoning available but results came out really different > 5.3 flash took 20 minutes to complete this and costed $0.7 via AIhubMix API > kimi k3 took 30 minutes to complete this and costed $4.32 via Kimi Plan which one do you think did better here?

J A Z I I

23,105 Aufrufe • vor 16 Tagen

DeepSeek v4 Flash (0731) vs Kimi K3 (10x more weights) i gave both the exact same prompt, in the exact same harness: one-shot a luxury product landing page ($10,000 "ARC-01" concept object). results in the video. my take: Kimi K3: wins on polish. Better typography hierarchy, more confident use of negative space, and the hero product shot integration is genuinely beautiful DeepSeek v4 Flash: very close. The structure is right, the copy is right, the layout logic is right. It loses on finish, not on fundamentals. a 10x smaller model getting ~90% of the way there. a year ago this gap would have been embarrassing. mind you it cost less than $0.10 for 6 build iterations and 8 QA passes. small models aren't "good for their size" anymore. they're just good.
0:32

DeepSeek v4 Flash (0731) vs Kimi K3 (10x more weights) i gave both the exact same prompt, in the exact same harness: one-shot a luxury product landing page ($10,000 "ARC-01" concept object). results in the video. my take: Kimi K3: wins on polish. Better typography hierarchy, more confident use of negative space, and the hero product shot integration is genuinely beautiful DeepSeek v4 Flash: very close. The structure is right, the copy is right, the layout logic is right. It loses on finish, not on fundamentals. a 10x smaller model getting ~90% of the way there. a year ago this gap would have been embarrassing. mind you it cost less than $0.10 for 6 build iterations and 8 QA passes. small models aren't "good for their size" anymore. they're just good.

filipe

26,329 Aufrufe • vor 1 Monat

Wow, I asked kimi k3 to produced interstellar style wormhole in Three.js, it worked for literally an hour and gave me this stunning thing btw i asked fable for the same thing and it was not as good as this one🤯
0:49

Wow, I asked kimi k3 to produced interstellar style wormhole in Three.js, it worked for literally an hour and gave me this stunning thing btw i asked fable for the same thing and it was not as good as this one🤯

Scott

36,428 Aufrufe • vor 1 Monat

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

26,166 Aufrufe • vor 1 Monat

Fable 5.1 vs Kimi K3 Tested both models with the same prompt at the highest reasoning level available. > Fable took 18 minutes to complete this test and cost $12.60 > Kimi K3 took 10 minutes and cost around $6.95 Which one wins here?
0:20

Fable 5.1 vs Kimi K3 Tested both models with the same prompt at the highest reasoning level available. > Fable took 18 minutes to complete this test and cost $12.60 > Kimi K3 took 10 minutes and cost around $6.95 Which one wins here?

Bhavy☄️

146,932 Aufrufe • vor 9 Tagen

Everyone keeps talking about how good Kimi K3 is. So I gave it one of my favorite frontend tests: one prompt + one reference image. The task: rebuild a 3D globe dashboard. 🌎 The result was almost too good. It did not just build a working page. The texture, lighting, spacing, depth, glass panels, and overall layout were all remarkably close to the reference. Some parts felt nearly pixel-perfect. My honest first impression: for this kind of frontend work, Kimi K3 might be slightly better than Fable 5. All at Sonnet prices.
0:31

Everyone keeps talking about how good Kimi K3 is. So I gave it one of my favorite frontend tests: one prompt + one reference image. The task: rebuild a 3D globe dashboard. 🌎 The result was almost too good. It did not just build a working page. The texture, lighting, spacing, depth, glass panels, and overall layout were all remarkably close to the reference. Some parts felt nearly pixel-perfect. My honest first impression: for this kind of frontend work, Kimi K3 might be slightly better than Fable 5. All at Sonnet prices.

Kai

405,113 Aufrufe • vor 1 Monat

Kimi K3 just beat Fable 5 on the BridgeBench Horror House game test. I did not expect this at all. Kimi K3 is better than Fable 5 at game development and UI design. The two things Fable 5 was supposed to own. The 5x price increase suddenly makes sense.
1:13

Kimi K3 just beat Fable 5 on the BridgeBench Horror House game test. I did not expect this at all. Kimi K3 is better than Fable 5 at game development and UI design. The two things Fable 5 was supposed to own. The 5x price increase suddenly makes sense.

BridgeMind

149,482 Aufrufe • vor 1 Monat

Kimi-K3 vs Opus-4.8 Flappybird test. Kimi is significantly better than Opus. That’s the reason why I claimed it as Opus-5 level. Test done in Arena.ai
0:20

Kimi-K3 vs Opus-4.8 Flappybird test. Kimi is significantly better than Opus. That’s the reason why I claimed it as Opus-5 level. Test done in Arena.ai

Jun Song

118,502 Aufrufe • vor 1 Monat

i just compared DeepSeek-v4.1-Flash against Opus 5 gave same prompt to both models to build ocean sandbox using three.js DeepSeek-v4.1-Flash was almost 90% cheaper and 50% faster than Opus 5 💀 maybe the benchmarks are not broken.. do you think DeepSeek is better?
0:52

i just compared DeepSeek-v4.1-Flash against Opus 5 gave same prompt to both models to build ocean sandbox using three.js DeepSeek-v4.1-Flash was almost 90% cheaper and 50% faster than Opus 5 💀 maybe the benchmarks are not broken.. do you think DeepSeek is better?

Tim Jayas

21,130 Aufrufe • vor 1 Tag

🚨 You can use GPT-6 Astra as the orchestrator and DeepSeek V4.1 Flash as the agents to cut costs by more than 88% while maintaining the same level of quality. And now it’s even better, since DeepSeek V4.1 Flash is one of the best models for cybersecurity at an incredibly low price
0:40

🚨 You can use GPT-6 Astra as the orchestrator and DeepSeek V4.1 Flash as the agents to cut costs by more than 88% while maintaining the same level of quality. And now it’s even better, since DeepSeek V4.1 Flash is one of the best models for cybersecurity at an incredibly low price

Iam_

25,437 Aufrufe • vor 1 Tag

Kimi K3 vs GPT-5.6 Sol Difference in taste is so stark , like if i swap kimi k 3 name with fable 5 people will trust it but this is not only about visuals , its also about function , you can see both achieve same result but the way to achieve is different kimi is more creative
0:39

Kimi K3 vs GPT-5.6 Sol Difference in taste is so stark , like if i swap kimi k 3 name with fable 5 people will trust it but this is not only about visuals , its also about function , you can see both achieve same result but the way to achieve is different kimi is more creative

Chetaslua

684,520 Aufrufe • vor 1 Monat

It worked!! Kimi k3 Oauth is now wired directly into codex. The Kimi k3 model is insane but their app is not. So I figure a better way to use k3 by hooking my sub straight into codex instead. K3 now sits in the model picker next to Sol 5.6. Same subscription i was already paying for, no api key, just have to do OAuth in Kimi Code. Links down below 👇
0:40

It worked!! Kimi k3 Oauth is now wired directly into codex. The Kimi k3 model is insane but their app is not. So I figure a better way to use k3 by hooking my sub straight into codex instead. K3 now sits in the model picker next to Sol 5.6. Same subscription i was already paying for, no api key, just have to do OAuth in Kimi Code. Links down below 👇

Ziwen

276,639 Aufrufe • vor 1 Monat

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 the wall. 🔹 Gemini 3.6 Flash is bad (took 5–6 attempts), but it has features the others don’t, like dropping coins for power-up balls and increasing the bar length. Ranking (DX, features, and cost): 🔹 Kimi K3: 10/10 · $0.10 🔹 GPT-5.6 Sol: 9/10 · $0.52 🔹 Gemini 3.6 Flash: 6/10 · $0.45
0:29

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 the wall. 🔹 Gemini 3.6 Flash is bad (took 5–6 attempts), but it has features the others don’t, like dropping coins for power-up balls and increasing the bar length. Ranking (DX, features, and cost): 🔹 Kimi K3: 10/10 · $0.10 🔹 GPT-5.6 Sol: 9/10 · $0.52 🔹 Gemini 3.6 Flash: 6/10 · $0.45

Command Code

61,412 Aufrufe • vor 1 Monat

Kimi K3 vs Fable 5. $0.45 vs $1.85. same prompt, same one-shot. the task: a cinematic 3D animation of an army helicopter flying through the Vietnam jungle during the war. both built it. K3 did it for a quarter of the cost. which one actually nailed it?
0:31

Kimi K3 vs Fable 5. $0.45 vs $1.85. same prompt, same one-shot. the task: a cinematic 3D animation of an army helicopter flying through the Vietnam jungle during the war. both built it. K3 did it for a quarter of the cost. which one actually nailed it?

Kirill

21,132 Aufrufe • vor 1 Monat

One of the first Kimi K3 outputs for y'all, tried it on frontend 👀 First impressions is that it's VERY slow, even slower than Fable. This took 35 minutes to finish. However, this is one of the best outputs I've ever seen from this prompt, better than many frontier models.
1:00

One of the first Kimi K3 outputs for y'all, tried it on frontend 👀 First impressions is that it's VERY slow, even slower than Fable. This took 35 minutes to finish. However, this is one of the best outputs I've ever seen from this prompt, better than many frontier models.

Lentils

104,085 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.

84,777 Aufrufe • vor 1 Monat

Opus 5 vs Grok 4.6 xHigh vs Gemini 3.6 Flash vs Kimi K3 Guys… the gap is actually ridiculous 😭 Opus 5 is in a completely different world here. Especially compared to Gemini 3.6 Flash — it’s not even remotely close.
0:28

Opus 5 vs Grok 4.6 xHigh vs Gemini 3.6 Flash vs Kimi K3 Guys… the gap is actually ridiculous 😭 Opus 5 is in a completely different world here. Especially compared to Gemini 3.6 Flash — it’s not even remotely close.

OmedTheVibeCoder

12,823 Aufrufe • vor 28 Tagen

Kimi K3 vs GLM 5.3 “make the ghost of tsushimas main menu from scratch” What’s funny is I thought Kimi K3 was being really lazy when you would go into the options and switch the language and it wouldn’t actually change anything. However, the graphics were stunning. The visuals were nice. You could go into the settings. You could change the options the brightness, the ambience. But when I saw how terrible GLM did, I instantly forgave Kimi for not adding that feature. Not even close
0:21

Kimi K3 vs GLM 5.3 “make the ghost of tsushimas main menu from scratch” What’s funny is I thought Kimi K3 was being really lazy when you would go into the options and switch the language and it wouldn’t actually change anything. However, the graphics were stunning. The visuals were nice. You could go into the settings. You could change the options the brightness, the ambience. But when I saw how terrible GLM did, I instantly forgave Kimi for not adding that feature. Not even close

Chris

22,514 Aufrufe • vor 23 Tagen

Kimi K3 also mogs Fable 5 on frontend design! this time it's not even close, Fable 5 didn't even try to produce something half as good as Kimi's result. the prosthetic hand still needs polishing but it's way more capable and Kimi deployed more feature than Fable did. no need to wonder what model to use for frontend anymore, the choice is clear.
0:26

Kimi K3 also mogs Fable 5 on frontend design! this time it's not even close, Fable 5 didn't even try to produce something half as good as Kimi's result. the prosthetic hand still needs polishing but it's way more capable and Kimi deployed more feature than Fable did. no need to wonder what model to use for frontend anymore, the choice is clear.

filipe

40,760 Aufrufe • vor 1 Monat