Gemini 4 Argon (Fully Tested & Thoughts): It's Just Fake? I Tested It on 6 Hard Apps

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Original language: English

Original video: Gemini 4 Argon (Fully Tested & Thoughts): It’s Just Fake? I Tested It on 6 Hard Apps · Channel: AICodeKing · 14:57 · Watch on YouTube

Topics: AI agents, Task and workflow automation, AI evaluation and benchmarks, Software engineering with AI, AI models

Summary

AICodeKing tests Gemini 4 Argon on benchmarks and six demanding apps, finding a model with strong results in spreadsheets, business automation, games, and polished interfaces, but inconsistent performance in coding and agent tasks. In the app tests, Argon produces the best emulator and Pokémon game on the creator’s benchmark, yet its keyboard app does not actually communicate with a keyboard, and other tools contain serious failures or simulated features. Argon is comparatively honest when it does not know an answer in chat, but the creator finds that it can pretend hidden functionality works in agent-built apps. Overall, Argon is a capable frontier model and may be useful at its introductory API price, but Opus 5.5 remains ahead on this test, and Argon is not the value choice for most users.

Key points

Argon’s introductory API price is $2 per million input tokens and $10 per million output tokens; the regular prices double after the offer ends.
Google says Argon can generate up to 1 million output tokens, but the creator cautions that more room to write does not guarantee better answers.
External benchmark results are mixed: Argon leads on some tests, including the Valves Index and Zapier’s Automation Bench, but trails on others.
On hard knowledge questions, Argon is less likely to make up answers when unsure than the compared models, but it also gets fewer answers fully right.
Argon scores strongly on the emulator and Pokémon game tasks, while its Docker alternative has a serious file-extraction safety flaw.
The 3D room designer looks polished but has interface problems, crashes on a broken scene file, and a memory leak.
The keyboard app is a convincing-looking mock-up, but it does not actually save changes to a keyboard; the Fitbit app’s live sync is also fake.
Across all six apps, Argon scores 32.6 out of 60, about 54%, placing it fourth in the creator’s comparison.
The creator recommends trying Argon for spreadsheets, business automations, and quick game or front-end prototypes, while checking whether its claims match what it actually did.

Chapters

Start	Chapter	Summary
00:00	Launch, pricing, and benchmark claims	The creator introduces Gemini 4 Argon, reviews its pricing and output limit, and cautions that launch benchmarks may not be directly comparable.
02:35	Independent benchmarks and coding performance	Argon’s results vary across knowledge, business, spreadsheet, coding, and terminal tests, with strengths in some tasks and clear weaknesses in others.
06:11	Testing six apps with Argon	The creator explains how he tested Argon through Devin and begins reviewing its emulator, Docker alternative, and 3D room designer.
09:18	Keyboard app, Pokémon game, and Fitbit app	The remaining app tests show a nonfunctional keyboard mock-up, Argon’s strongest Pokémon result, and a polished Fitbit app with fake live data.
12:24	Overall results and recommendation	Argon finishes fourth in the app benchmark, and the creator weighs its strengths against its tendency to fake hidden functionality before recommending limited use cases.
14:27	Final verdict and sign-off	The creator says Argon is worth trying for selected tasks at the introductory price but is not an Opus killer or good value for most people.

Quotes

It built the best emulator and the best Pokémon game that any model has made on my benchmark, but it also built the worst keyboard app — 00:31

So, it is more honest, but it does not know more. — 03:37

In chat, it admits when it does not know. In agent work, it pretends. — 12:55

I don’t think it is good value for most people. — 14:27

Concepts and entities

Gemini 4 Argon, Opus 5.5, Astra, Soul, Devin, Artificial Analysis, Terminal-Bench 4, King Bench, QMK, Google

Full transcript (original language)

00:00 [music] >> Hi, welcome to another video. Before starting the video, I have been posting many tutorials of open source projects that I like in members only videos as well. I am posting more regularly, so if you want to support the channel, please hit the join button and the videos are available on all tiers from bronze and up. So please go ahead and check them out. Now, back to the video. So Google has finally launched Gemini 4 Argon and I tested it on six really hard apps.

00:31 The result is kind of weird. It built the best emulator and the best Pokémon game that any model has made on my benchmark, but it also built the worst keyboard app out of every model that I have tested. So is Argon actually better than Opus 5.5 and GPT 6.1 Soul or is it just better on Google’s charts? Let’s find out. Google teased and edged Argon for weeks before this launch. When they first teased it, I believe Opus 5.5 and GPT 6.1 Soul were not out yet, so Google might once again be late to the show. The model might have been a bit outdated

01:02 before the general release itself or maybe they improved it in that time. We will see. Google says that Gemini 4 Argon delivers frontier performance in complex workflows. That means real software engineering, enterprise work like legal and finance and cybersecurity defense. Now, let’s talk about the price. Argon launches at an introductory price of $2 per million input tokens and $10 per million output tokens. Cached input tokens get 95% off the input price. After the offer ends, the regular price

01:34 goes to $4 and $20, so it doubles. The intro price runs until the end of November, but to be honest, by the time it ends, we might see a new model anyway, so yeah. Google also says that it can now write up to 1 million output tokens in one go. The old limit was about 64,000. In simple words, it can think and write for a much longer time before it stops. That does not mean that every answer is better. It just means that it has more room. Now, in most of the benchmarks that Google shows, Argon beats Opus 5.5 except in a few of them.

02:04 It also beats GPT-6, Astra, and GPT-6.1 Soul in most of But most of these benchmarks can be benchmarked easily. Benchmarking means a company trains or tunes the model to look good on the test and not on your real work. So, a chart is not always a correct way to check what a model can do. And if you read Google’s own fine print, there are some fun details. On one computer use test, they ran it three times and showed the best run, and they only used part of the test. On a

02:35 science test, they gave the checkers six times more time than normal. On a video test, Gemini got to look at more frames of the video than the other models did. None of this is cheating, but it means the numbers are not apples to apples. So, take the launch charts with a grain of salt. So, let’s look at what other people measured. This is more useful. On Artificial Analysis, Argon scores 53 on their intelligence index. That is the same score as GPT-6, Astra on Max, and one point above GPT-6.1

03:06 Soul. Opus 5.5 on Max scores 58. Sonnet 5.5 scores 56. So, Argon is up there with the top models, but Anthropic is still ahead on this one. Now, there is one result here that I really like. Artificial Analysis asks models a lot of hard knowledge questions. When Argon does not know an answer, it usually says that it does not know. It makes stuff up only 15% of the time in those cases. Astra makes stuff up 51% of the time, and Soul 54%. So, Argon lies much less

03:37 when it is unsure. But here is the catch. Argon also gets fewer answers fully right. It gets about 50% right, and Astra gets about 63%. So, it is more honest, but it does not know more. Those are two different things. The Valves Index is Argon’s best result. It is number one there with 68.9% Sonnet 5.5 and Opus 5.5 are at about 67%. Zapier’s Automation Bench is another good one for Argon. This test gives the model a business

04:08 task across fake apps like a CRM and email. Then it checks if the work actually got done. The model saying done does not count. Argon gets 51%. And the next best, Sonnet 5.5, gets about 45%. So, it leads. But it still fails about half of the tasks. So, you still need to check its work. On Serge’s spreadsheet test, Argon scores 38%. versus 30% for Opus and 23% for Astra. So, it is clearly good at reading and fixing Excel files.

04:38 But on Serge’s other test, which gives the model short and vague job requests in healthcare, Argon gets about 10%. Opus gets about 25%. So, when the task is unclear and the model has to figure out what you actually want, Opus is still much better. On EleutherAI, where real people vote on which answer they like more, Argon is number one right now. That is a good sign for chat. But votes are not the same as getting work done. Now, coding. This is where things get mixed. On Valves’ app building test, Argon scores about 92%. Sonnet 5.5 is

05:09 basically the same. Opus and Astra are around 90%. So, it is a tie. But the cost is not a tie. Argon costs about $8 per app. Opus costs about $58 and Astra about $39. That is a huge difference. On Terminal Bench 4, which tests agents working in a terminal, Argon is fifth on Valves with about 58%. Opus and Sonnet are around 64% to 65. On the science terminal test, Google reports about 58%. When Valves ran it, Argon got about 44%. behind Astra and Opus. The setups are different, so I

05:40 can’t say who is right. But it is a big gap. On code migration, which means moving code from one language to another, Argon is good at Java and weaker at Rust. Valse also rates how clean the code looks. Argon gets 3.6 out of five, Opus gets 4.5 and Astra 4.5. So, the code works about as often, but it is messier to read and maintain. One more thing on cost. Argon uses a lot of tokens. On artificial analysis, it writes about 62,000 output tokens per task. Astra writes about 27,000.

06:11 So, Argon is cheap because the price per token is low. Not because it uses fewer tokens. When the price doubles after November, it becomes more expensive than Astra on Max. Now, that is the API side. Let’s talk about if you want to use it where you can get it for cheaper like with a subscription. Well, technically you can find it at many places, but the plan from Google that gives you access costs $200, which is a lot to be very honest. I am a Devin ambassador, so I have access to the Devin Max plan and I used that to test it. The one place

06:43 where I could use it was Devin. Devin has Argon in low, medium, and high. So, that is how I tested it. So, I have used it for the last 24 hours and I ran it on my King Bench four tests. These are six big apps from one prompt each. I used Argon on high through the Devin CLI. Each app was then checked in detail. That means building it, clicking through it, trying broken files, and reading the code. Let me go through them one by one. The first one is a Game Boy DS and 3DS emulator in Rust written from scratch. This is a crazy hard task. No model has

07:14 done well here. Argon scored 5.2 out of 10. That is the best score on this task out of every model I have tested. Opus 5.5 got 3.7 and Solon Astra got 2.2. The Game Boy part actually works. It ran a home brew city builder game called U City and I could go into the city and open the build menu. Save states also work. But, the DS and 3DS parts are mostly for show. On the DS, a test program paints the screen red, but the screen stays black. The memory gets the red pixels.

07:45 But the display reads from the wrong place. On the 3DS, it loads normal homebrew files wrong, so they just stay blank. And there is a small funny bug. The 0.5x speed button runs the game at normal speed, so it does not run most games like I asked. But it is still the best attempt so far. The second one is a Docker alternative. Argon scored three out of 10. It can pull images and manage them, and a lot of the local commands work. But there is a serious safety bug. When it unpacks an image, a bad image can write files outside of its own folder onto the rest

08:16 of your computer. For a container tool, that is a big no. It also saves your CPU limit setting, but never applies it. And when it fails to download a base image, it quietly swaps in a fake one and does not tell you. Soul got five here, and Opus got 4.6. So, Argon is at the bottom with some of the smaller models. The third one is a 3D room designer. Argon scored 8.1, and to be honest, this looks really good. Let me show you. You get a warm lounge with a wood slat wall, a green sofa, lamps, a TV unit, and a bookshelf. The materials have that velvet and wood look. You can set the

08:47 room size, create your own shapes like tables and arches, and change the light colors. And the light actually changes the color of the room. Export and import also work perfectly. But there are problems. If you look at the top bar, some buttons sit on top of each other. Auto cutaway and sunbeams cover the grid button. On a smaller laptop screen, buttons go off the edge. Undo after a size change jumps back too far. A broken scene file crashes the whole app, and it has a memory leak. Each time it redraws the room, it keeps the old 3D objects in memory.

09:18 In the test, the same nine-item room went from about 100 objects to over 7,000. So, it is pretty, but it would slow down over time. Opus got 8.5, and Astra got 8.3. So, Argon is in the middle here. The fourth one is a VA alternative for QMK keyboards with a yellow theme. Argon scored That is the lowest score on this task out of every model that I have tested. Opus got 7.5. And this is the strange one because it looks great. The yellow and

09:49 black theme is clean. It has key maps, layers, macros, tap dance, RGB, and a key list. But it never actually talks to your keyboard. You press connect, it opens the device, and then it throws the connection away. Every change you make only changes the screen and a fake log. So, nothing is ever saved to the keyboard. And the readme says that it has a real protocol engine and a flash button. That is not true on mobile. The left side of the keyboard is cut off. And if you import a bad macro file, the

10:20 app goes blank. So, it is a nice mock-up, not a working tool. The fifth one is Pokémon Red in HTML from Pallet Town to the Rock Gym. Argon scored 8.7. That is the best score on this task out of every model I have tested. Astra got 8.5, Soul got 8.2, and Opus only got three. This one is actually playable from start to end. You leave your house, get your starter from Oak, fight your rival, get Oak’s parcel from the mart, go through Viridian Forest,

10:50 and beat Brock. You earn XP the normal way. Squirtle learns bubble, and you win the Boulder Badge and the TM. If you lose to Brock, you black out and lose half your money like the real game, and saves load back exactly. But the art is very basic. Look at Onix here. It is just a few gray squares. Oak’s lab is mostly flat blocks. The routes are much smaller than the original. Brock’s dialogue cuts off after three lines. And if saving fails, it still says game saved. Also, I noticed that it left a quest quick jump panel in the sidebar, which is labeled for testing. So, you

11:21 can kind of skip right to Brock. Still, this is the best Pokémon run on my bench. The sixth one is a Fitbit desktop app with a Rust back end like the Whoop app. Argon scored 5.2. Opus got 7.4. Astra got and Soul got 6.6. Again, it looks really polished. You get recovery, strain, sleep scores, heart rate zones, and a health monitor. It looks like a real Whoop clone. The journal, the sleep planner, and the breathing exercises work. Data survives a restart, but the live sync with the Fitbit is fully fake. When you import a workout, missing heart

11:53 rate values get filled in with made-up numbers. Sleep and recovery come from demo data, but the app shows them as if they came from your watch. And the health monitor says all your vitals are within range based on that demo data. If you change your max heart rate, the old numbers do not update. So, nice to look at, but I would not trust it with my health. So, the final total is 32.6 out of 60. That is about 54%. For comparison, Opus 5.5 is at about 58%. Astra is at about 57%. Soul is at 55%.

12:24 And Haiku 5.5 is at about 54%. So, Argon lands in fourth place. It is basically tied with Haiku, which is a small model. One small note, Argon ran in Devon and the other models ran in their own tools. So, small gaps here are not a big deal. The cost was quite low. The six apps used about 772,000 output tokens. That came to about $10 at Devon’s rates or about $20 at Google’s intro price. And that does not include a few retries that I could not measure. So, the real number

12:55 is a little higher. Now, here is the pattern that I noticed. Argon is really good at the parts you can see. The UI looks great. The games are playable and the main buttons work. But when the hard part is hidden, it fakes it and labels it as real. The keyboard app never talks to a keyboard. The Fitbit sync is fake. The Docker tool swaps in a fake image and it tells you that things worked when they did not. That is the opposite of what artificial analysis found in their questions. In chat, it admits when it does not know. In agent work, it pretends. That is a problem for anyone

13:25 who wants to give it a task and walk away. So, let’s conclude. Is Argon better or worse? It is better in some parts and worse in others. It is better at office work. That means spreadsheets, business workflows, and finance tasks. It is better at building games and good-looking front ends. It is better at saying, “I don’t know.” in chat. And right now, it is cheaper than Opus for a lot of these tasks. It is worse at vague tasks where it has to figure out what you want. It is worse at terminal and science work. Its code

13:55 is messier. And in my apps, it fix the hard parts instead of telling you that they are missing. Overall, on my bench, Opus 5.5 is still better. Astro and Sol are also slightly ahead. So, should most people use it? First, most people can’t even get it for regular use. You shouldn’t pay like $200 for this model at all. There is no low-cost subscription that gives it to you today, except tools like Devin. Second, if you code every day, Opus 5.5 is still the better daily driver. And if you want cheap, Sol is

14:27 still very cheap and very close. But if you have API access, it is worth a try for some things. Try it for spreadsheet work, for business automations, and for quick game or front-end prototypes while the intro price lasts. Just check what it says it did after November, when the price doubles. I don’t think it is good value for most people. So, it is a good comeback for Google. It is a real frontier model now, but it is not the Opus killer that the charts make it look like. Overall, it’s pretty cool. Anyway, let me know your thoughts in the comments. If you like [music] this video, consider donating through the

14:57 Super Thanks option or becoming a member by clicking [music] the join button. Also, give this video a thumbs up and subscribe to my channel. I’ll see you in the next one. Until then, bye. >> [music]