This is it. The models are okay as it is, but the apps are honestly trash and literally years behind the competitors. I’d be happy with Google models in Claude/ChatGPT app.
Adequate tools calling. The app actively refuses to use Google search for i can't imagine why, so the model can't have fresh data. It also never uses Canvas when not prompted. The same with script execution and working with files.
Actually working file uploads. Every time i upload even a tiny csv into the chat (literally - 11 lines csv) - it NEVER sees the full file content, the model is always fed with some "snippet" and hallucinates the remaining file
Same with notebooks. It allows you to upload files into notebook but rarely actually reads them before answer
UX is just generally not good, but it's expected from Google, so not much complaints here
This list goes on and on..
You see, in Claude i can create a project, feed it with files, then start a chat, upload some data into it and Claude will parse it with either Python or JS, find patterns and give me real insights. Gemini will just make the data up.
I'd like it to just work. Especially the new notebook area. Generating files and images are often ending on errors, can't use deep research results from chat directly in notebooklm, mobile experience loses a lot on features too. On paper there are a lot of great things, but it kinda falls apart when trying to power use a bit
People are lazy, if everyone actually follow the workflow of Pro planning, Flash execute, and babysit regularly, everything would work just fine. In fact for works that need to be done ASAP I would just use flash in Antigravity/Gemini CLI. When you know what you are doing there are like 95% of works can be done faster with Flash. Save the first tiers of Opus, Codex xhigh or Gemini Pro for genuinely hard problem-solving tasks, which you would get a feel for quickly if you actually spend time with smaller models. No this is not just advice to safe cost, it is an actual way of accomplish things much faster. Given a big project you would have to babysit everything anyway, if anyone actual time their own performance using big model for only 5% in planning and flash for execution vs go fully Opus all the time they would realize they're literally wasting their time on the big ones.
People just go to the route of "allow all edits" so they started to compare performance after like 15 mins letting the models runs wild, and they think smaller model is trash, because they can spend another 15 mins fixing the great opus results while the smaller models would break everything beyond repaired, but they just skip that part that if they actually babysit the small model a bit more the task would be done in like 5 mins. Of course, you can babysit bigger models also but the speed is so slow that it would take you longer.
Deepseek V4 Flash is quite similar, but they need to get vision in for me to consider a switch, of course you should still have the big models subscription backup when needed, but the workhorse that you daily drive should not be a >1T model, because it is seriously slowing you down.
Yeah and skills always help with this too, setup skills so that it uses the small/cheap llm's first and spin up the bigger ones if they cant resolve the issue in x attempts and stuff like that.
I believe you, I've just played around with Flash enough to know that it makes a lot of errors constantly. It is great for things like chat bots, but in terms of quality, I wouldn't trust it with anything.
They added branching and Notebooks to the Gemini app last month, but I guess not everyone has it yet.
I also hope they started on agentic AI because that appears to be a huge talking point at this year's Google I/O later this month, which is where they usually announce a lot of new things.
Agreed on both counts. 3.0 flash is actually pretty impressive for the speed and incredibly low cost. I honestly prefer it to 3.1 Pro, especially in a better harness, AKA anything but the Gemini app.
The speed is really an advantage in this age of agentic workflows where you need a lot of tokens, not just for reasoning before the reply, but for tool use and double-checking the output and planning in that type of thing and planning in that type of thing.
Models that are cheap, fast, and smart enough are the future for the majority of tokens, IMO
I use claude code and gemini cli for unreal engine C++, i leave the architecture and visual design to claude code but they aren't that far apart and I have very few issues with 3 flash doing 90% of the work
I experience 0 hallucination.
It does crap the bed and goes into an infinite loop every 300 prompts or so, it will "cheat"/shortcut a solution every 50 requests and it causes easy-to-fix-itself compile errors every ~5 change sets. And once or twice in 6 months of very high usage, it has deleted something it shouldnt (git saves the day). It has some minor annoying habbits you learn over time, but those are easily resolved with gemini.md
but those are not big issues for me.
Over the past week or two its written about 10k lines of code, basically recreating CSS in Unreal Engine slate C++ and while its constantly refactoring the design at my request, that's only natural for a rapidly growing codebase and I'm quite happy wit the results
And they still hallucinate too much. By including things to solve the benchmarks you can improve their performance but day to day performance would not get the benefits. I think og 2.5 was very good, and I think they improved with 3 pro in terms of writing but 3.1 pro? Have no difference at all.
I encourage anyone to compare any query that involves searching the web between Gemini and ChatGPT (Thinking, Extended).
Gemini does what you said - searches a handful of pages, treats them as gospel truth no matter the quality, and rarely even includes links in the reply...
In comparison, ChatGPT will search and search, prioritizing higher quality sources. It's better about not citing low-effort "listicles" and will do additional searches to confirm what it finds - you can see the numerous queries it does in the thinking trace. It'll even open and read PDFs!
More complex queries might take several minutes with extended thinking, but in my experience, the quality of the reply is just outrageously better than Gemini. Hell, "AI Mode" (with pro thinking) is better than the Gemini app.
The only time I actually get decent results from Gemini that include web search are when using deep research, and that takes a very long time. And includes so much irrelevant fluff that it's frustrating to read.
Care to share any of these really important hard legal cases or academic papers to ACTUALLY compare outputs or else this is just another unfounded claim
Here’s an easy one. Ask Gemini 3.1 Pro and ChatGPT Thinking “Is GPT-5.5 an omnimodal model?” Gemini will respond and say that yes, it is an omnimodal model every single time and cite some random SEO-optimized blogs. ChatGPT thinking actually looks and verifies to see if it’s true and discards the SEO blogs as untrustworthy and gets the answer right every single time. For more complex and less black and white questions it’s even more noticeable, but this is a super simple question that Gemini fumbles.
Super interesting, I tried 15 times and all 15 times it told me it was an omnimodal model. Do you have any custom instructions and do you have personalization enabled?
Gemini for day to day and family sharing (plus conversational stuff when brain storming thanks to the limits). ChatGPT for actual work and output. I would use Claude, but those limits...
I was using Thinking in the Gemini app to ask questions about codex-sdk. Specifically about the memory function and how to adjust it in the config.
It blatantly lied about it and doubled down with fake citations when asked. Even provided fake code snippets.
Finally it admitted that the whole thing was made up. I’ve been using these tools since gpt-3.5 and never seen a model outright lie so bad even when challenged. Until they figure that out it’s nothing but a recreational tool.
same. i use basically nothing but google services/apps (because i just dont need much to get work done), and gemini by itself is absolutely a fine model if you use it through API, but gemini in the app is borderline useless. the whole gemini web interface/android app is just not good
I have been using 3.0 flash on PiPar for chats and voice calls. It is excellent for its price - fast and surprisingly fluent for basic chats. It seems to have access to large knowledgebase since it know the address of closest pharmacy without searching web.I live on small town in Finland.
I was using Preplixty for some fixes for my car. Not only Gemine 3.1 pro was super bad, it litary lost track of what we were talking about after two messages. Sonnet was better than 3.1 pro. Like dam, what was that.
I was once very impressed with Gemini (pro 2.5). Until 3.1 Pro came out, I stop believing it. Model tend to over-think and wasted precious time + tokens. Kimi 2.6 took half the time and done better than 3.1Pro.
Flash Lite also skipped 3.0 and went straight from 2.5 to 3.1. So it's not strange to see they skip 3.1 altogether and go to 3.5 as a new base line to then later update Pro and Flash Lite from 3.1 to 3.5 and then have the full family on 3.5.
It exists, it's just that the 3.1 flash LLM version is no longer being released.
The first time a reference to 3.1 flash was seen was with NB 2 (which, in fact, the original 3.0 flash also really had imaging capabilities that was never released). Then came AVM, and finally, TTS. All omnimodal systems have been released, except for LLM, which types and responds with text.
My guess is This is 3.1 flash. Not 3.5 flash. Because thet will release first 3.5 pro 20th of may and 20th of June 3.5 flash or 1st of July. They didn't want the contrast of 3.0 flash and 3.5 pro.
Nah, it's been too long. NB 2 has been out for almost 3 months, Gemini 3.1 Flash is only going to offer omnimodal capabilities, and LLM isn't coming out anymore.
The 3.5 flash makes sense since, well, they would still have plenty of room to do something "better" than that.
The first time Gemini 3.1 flash was heard was in Nano banana 2, the image generation and editing feature offered by that model (the 3.0 flash theoretically had this function but it was never publicly released)
What is the point if it is always "currently experiencing demand spikes" and returning errors in your applications. A model that is available is more important than one that works better.
I have tried the new updated flash model and i'm speechless. This thing outperforms Opus 4.6 in all my benchmarks, which is insane because Opus outperforms even 3.1 Pro
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u/Passloc May 02 '26
I have been using Flash for all my coding because of its generous limits in Antigravity.
It is serviceable for 90% of the time.
I use it to write most of the code and get the same reviewed by Opus/Codex to find bugs and see if my design principles are being followed.