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Gemini 3.7 Flash

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Re: Gemini 3.7 Flash

#341
post #141

The "introductory pricing" for this 3.7 Flash model is really weird. It's scheduled to double in price on December 31, 2026, but who would anticipate still using this model five months from now? Especially since 3.6 Flash came out just three weeks ago! My first effort with default thinking level produced an ambitious pelican, let down by a flawed bicycle: https://tools.simonwillison.net/markdown-svg-renderer#url=ht..…

At $work we still have some places using Opus 4.5. Even places using Qwen 2.5-VL, which is now 18 months old. It works, and upgrading is work (we'd have to validate the new model performs comparable in all the corner cases that currently work just fine) Those kind of workloads would be hit by an end of introductory pricing. And it's exactly the kind of cases that are not very price sensitive. Where we are price sensi…

Especially for minor workloads that’s like using a dollar of tokens a day. Not worth it unless you’re unhappy with performance or you have nothing else to do.

Re: Gemini 3.7 Flash

#342
post #335

Earlier quoted context omitted.

I practically switched to doing everything with Luna or DeepSeek V4 flash. I haven't feel the need for the more expensive models.

Of the two, which do you find better?

I really, really like DSv4 Flash because you see the full, real thinking text. That’s been so useful for helping steer the model; as well as seeing its thoughts and correcting any errors, or expanding on it. It’s so difficult for me to use closed models with no or summarised thinking now — it feels so painful and gimped.

You don’t know what you’re missing until you’ve seen it. For me it’s almost like going from standard def to HD for the first time.

(This applies to other open models too — Kimi K3 in real world feels below Opus 5 in terms of raw intelligence, but significantly above Opus 5 in usability and personality. And no silly refusals — the model feels like it’s working for me; not working for Anthropic who’s always holding a leash over the model while I pay for it).

Re: Gemini 3.7 Flash

#343

Earlier quoted context omitted.

On DeepSwe it's strictly beaten by Luna on max, cost and result. Damn, Luna on max is as good on DeepSWE as Kimi k3, I think I dismissed this model unjustly.

This is why benchmarks are scary, since Artificial Analysis puts it a fair bit behind Kimi K3. Kimi K3 is a beast though, just costly.

Still cheaper than API rates for Opus!

Re: Gemini 3.7 Flash

#344
post #244
post #133

Earlier 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…

> but I just don't know what situation I'd reach for 3.7 Flash You reach for it every time you do a Google search

> You reach for it every time you do a Google search

[my self-important Kagi shtick awakens, pokes at it's restraints]

Re: Gemini 3.7 Flash

#345

i just wish google cloud ux was remotely as good as their models. they made some progress with their studio, but then in a true google fashion, product names keep changing (Gemini, Anti-gravity, Vertex, Google AI,...) as well as confusion and complexity for something as simple as registering agy cli with a Google cloud project. today i wanted to link agy to a google cloud project, for that i had to enable 5 different…

Gemini is the model family.

Antigravity is their agentic coding app / IDE. There is two products, one is chat-only the other is more standard IDE.

Google AI Studio is a consumer/developer playground with a in-browser IDE meant for prototypes or demos, there is a gallery of demos etc. Easily shared, easy key access.

Vertex is the AI offering from the GCP side of the company, that is going to target more enterprise or business solutions (scaling, data governance, security, production deployents, etc)

Re: Gemini 3.7 Flash

#346
post #271
post #261

Earlier quoted context omitted.

It doesn't. It's called preserved reasoning and every recent reasoning model does it

Sorry, I've realised I was only partially correct. Gemini[0] for example passes along a snapshot of the reasoning state but it's not the equivalent to keeping all the reasoning tokens in the context. [0] https://ai.google.dev/gemini-api/docs/thinking#signatures Edit: Apparently it does take the same space in the LLM latent space so I was wrong.

Yeah, I remember reading about Anthropic's experiments with dropping out different things, and dropping the thinking is ok for compaction but pretty awful while it still fits in the context window. I could imagine doing it adaptively -- take a snapshot before the thinking, have a lesser model detect if there's a lot of spinning going on and reset to snapshot + result if so, otherwise accumulate. It'd also be interesting to have a lesser model rewrite thinking to be more streamlined (let's pretend the AI went directly down the right path on the first try). But it may be a disaster anyway -- isn't the thinking section something like a 1d best-logit slice of something like a 2d process, where the real processing could easily be happening under the visible surface?

I'm not sure if that's right. I only just recently learned that the "snapshots" (aka cached tokens) necessarily contain the entire context history, not just an image of a "state as of the final token" (well, it is the state as of the final token, but that state contains the whole history). So I'm not confident of my grasp of the structures here.

Re: Gemini 3.7 Flash

#347
post #182

I don't get it, Google could heavily subsidy their Gemini models to make it more attractive, but they prefer to not do it. I don't know one soul who is using Gemini models to code. Even OpenAI who doesn't have money or capacity is offering their Luna model at $1.2 per 1M/out.

Why would they? Unless they have lots of unused tpu real estate that they could host it on “for free” they would be bumping more profitable workloads off of machines to give away that capacity to people with zero long term loyalty. There is no business reason for google to subsidize these models. OpenAI has too much money. They’re spending their money in stupid ways.

Having people use the model generates real world training data which could be useful. Other than that I think you're right that there is little reason to artificially boost users with subsidized pricing.

Re: Gemini 3.7 Flash

#348
I just subbed to Gemini a week ago and have been using antigravity and 3.6 flash. The speed is absolutely a differentiator compared to Claude.

Re: Gemini 3.7 Flash

#349

I was going to cancel my gemini membership today ..... still going ahead. In my experience, gemini 3.1 pro, 3.5, 3.6 flash constantly lie too much about completing their tasks whereas sol (even though equally dumb) never claims something has been done when it hasn't been.

That's a good point and something I encountered yesterday. On a multi-agent task, Gemini was the only model that got near the end, ran tests, saw it had issues, took a screenshot, saw the issues, and then said, "I'll mark it complete" and delivered.

I was paying for Ultra, then downgraded to Pro and at this point I'm near abandoning it. Agy as a harness also has a tendency to constantly request significant elevations to perform routine operations.

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