Earlier quoted context omitted.
> The "let's make money by selling/renting out TPUs" faction has won and the "let's make money by training and selling a frontier model" faction has lost. Citation needed. also, why can't a massive company do two things?
With all due respect, did you read my comment beyond the first paragraph? It addresses both points, TPU economics/pivot to sales + internal shortages making it hard to train models, to the extent they can be addressed based on public sources. There are other factors at play, but they're more recent/second-order.
Gemini 3.7 Flash
251–260 of 525 posts
Re: Gemini 3.7 Flash
#252Earlier quoted context omitted.
> does not bloat up the context window too fast with reasoning tokens How much does that matter if it's reset at every turn?
what do you mean by reset at every turn? context stays until compaction. if you remove the reasoning tokens after every turn you will be constantly blowing cache which is far worse than filling up context.
Your Prompt 1: Prompt Content 1 -> cache-1
LLM Response 1: Thinking Content 1 Response Content 1
Your Prompt 2 (client side): prompt-1 + response-without-thinking-1 + Prompt Content 2
Your Prompt 2 (server side): cache-1 + response-without-thinking-1 + Prompt Content 2 -> cache-2
LLM Response 2: Thinking Content 2 Response Content 2
Etc...
So reasoning gets dropped from context and you still get cache from the accumulating requests.Edit:
I've realised I was incorrect, the thinking doesn't get passed back and forth but the latent snapshot does which result in using memory just the same.
Re: Gemini 3.7 Flash
#253Earlier quoted context omitted.
> does not bloat up the context window too fast with reasoning tokens How much does that matter if it's reset at every turn?
Does it reset at every turn? From my experience in Codex for example, Luna (Max) fills the 256k token window relatively quick. The only thing lowering the context window again is the compaction.
Re: Gemini 3.7 Flash
#254Earlier quoted context omitted.
Can you help me understand how it is hard to get an API key from Google? You just head on over to http://aistudio.google.com/api-keys and create a key... not any different from platform.openai.com? Disclaimer: I work in Google so it might be that this link is not publicly well known
> Can you help me understand how it is hard to get an API key from Google? Using Google products in general is an effing nightmare as soon as you have to give them money. The one thing you want in a business is to remove friction when people want to give you money, a concept Google has never been able to understand.
Re: Gemini 3.7 Flash
#255Earlier quoted context omitted.
Other thoughts: I really think Google has fallen behind here. Even as a high speed offering (this build took ~7min, which is pretty good!), it wont be able to claim dominance for long with cerebras announcing the Sol preview today: https://www.cerebras.ai/blog/accelerating-gpt-5-6-sol-ultraf... . It's not a bad model by any means, but I just don't know what situation I'd reach for 3.7 Flash first for. Google really n…
Can you help me understand how it is hard to get an API key from Google? You just head on over to http://aistudio.google.com/api-keys and create a key... not any different from platform.openai.com? Disclaimer: I work in Google so it might be that this link is not publicly well known
Eventually I gave up and run a few hundred million tokens (edit a few billion) through openrouter.ai using Gemini Flash 1.5 to Flash 2.5
Every since price increases on Flash 3.0 I've stopped using Gemini, too expensive for basic classification, sentiment detection, ocr etc.
As other posters said Google assumes you are some bigcorp trying to use their products. The Vertex versus AI studio confusion did not help.
Re: Gemini 3.7 Flash
#256Here's a image->html test. Gemini has always swung above its weight class for vision work, so I'm always eager to try it with this. Original images: https://image.non.io/neonRamenDesigns.webp Gemini 3.7 build: https://html.non.io/neonRamenGemini3.7 Opus 5 build for comparison: https://html.non.io/neonRamen Opus is still best in class for this, but it's worth noting how well Gemini 3.7 does vs a more comparable LLM pr…
Other thoughts: I really think Google has fallen behind here. Even as a high speed offering (this build took ~7min, which is pretty good!), it wont be able to claim dominance for long with cerebras announcing the Sol preview today: https://www.cerebras.ai/blog/accelerating-gpt-5-6-sol-ultraf... . It's not a bad model by any means, but I just don't know what situation I'd reach for 3.7 Flash first for. Google really n…
Re: Gemini 3.7 Flash
#257Here's a image->html test. Gemini has always swung above its weight class for vision work, so I'm always eager to try it with this. Original images: https://image.non.io/neonRamenDesigns.webp Gemini 3.7 build: https://html.non.io/neonRamenGemini3.7 Opus 5 build for comparison: https://html.non.io/neonRamen Opus is still best in class for this, but it's worth noting how well Gemini 3.7 does vs a more comparable LLM pr…
Plus is the ramen in HK even any good?
Re: Gemini 3.7 Flash
#258Here's a image->html test. Gemini has always swung above its weight class for vision work, so I'm always eager to try it with this. Original images: https://image.non.io/neonRamenDesigns.webp Gemini 3.7 build: https://html.non.io/neonRamenGemini3.7 Opus 5 build for comparison: https://html.non.io/neonRamen Opus is still best in class for this, but it's worth noting how well Gemini 3.7 does vs a more comparable LLM pr…
How are you doing this with Opus. Clearly I’m missing something. I always turn to ChatGPT when I need images because Opus typically refuses. I’ve tried Claude Code and Claude online in the past. I’m pretty sure neither created images for me and I thought this was because Anthropic was focused on code. I guess I need to try harder. :)
Re: Gemini 3.7 Flash
#259Ever since the insane discount with GPT-5.6 Luna, not much excites me anymore. I mean just look at the benchmarks, even though Gemini 3.7 Flash performs well on the DeepSWE 1.1, Luna (Max) still performs way better. I personally have stuck to Luna (Xhigh) because its been more than enough and does not bloat up the context window too fast with reasoning tokens. https://deepswe.datacurve.ai > Starting January 1, 2027,…
GPT-5.6 Luna is an insanely powerful model for its price. It's been great for coding workflows where I guide the LLM's hand step by step. It's also insane to see my weekly limit drop by than 2% after an hour of coding ever since the discount. However, I've noticed 2 drawbacks with Luna. Context rot is much more palpable than Terra and Sol. It tends to get confused and go into rabbit holes when it's context gets fille…
Re: Gemini 3.7 Flash
#260They need to release benchmarks against Luna/Terra. Luna is much cheaper which feels like it undercuts the need for Flash. I've always considered the Flash series of models to be for low-cost, high-volume, mostly text-based use cases (e.g. summarization, parsing, formatting), emphasis on low-cost. [edit: ah, benchmarks here: https://blog.google/innovation-and-ai/models-and-research/ge... more of a Terra than Luna com…
gemini flash is probably the best model for visual tasks right now. they also make it really easy to ingest videos