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__jl__

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__jl__
·قبل شهرين·discuss
This understates the cost increase. 3.5 Flash also uses more tokens. artificialanalysis.ai shows these difference to run the whole eval, which I think is more realistic pricing:

Gemini 2.5 flash (27 score): $172 (1.0x)

Gemini 2.5 pro (35 score): $649 (3.8x)

Gemini 3.0 Flash (46 score): $278 (1.6x)

Gemini 3.5 Flash (55 score): $1,552 (9.0x or 2.4x compared to 2.5 pro)

This is a massive price increase... 5.6x compared to Gemini 3.0 Flash
__jl__
·قبل شهرين·discuss
In our experience, caching is not very reliable with google. We always get random cache misses that don't happen with other providers. We find OpenAI, Anthropic and Fireworks (which we use a lot) all have higher cache hit rates. So it's not only about the costs of cached token but also what kind of cached hit rate you get.
__jl__
·قبل 4 أشهر·discuss
I see your point. I do find Anthropic's approach more clean though particularly when you add in mini and nano. That makes 5 models priced differently. Some share the same core name, others don't: gpt 5 nano, gpt 5 mini, gpt 5.1, gpt 5.2, gpt 5.4. And we are not even talking about thinking budget.

But generally: These are not consumer facing products and I agree that someone who uses the API should be able to figure out the price point of different models.
__jl__
·قبل 4 أشهر·discuss
What a model mess!

OpenAI now has three price points: GPT 5.1, GPT 5.2 and now GPT 5.4. There version numbers jump across different model lines with codex at 5.3, what they now call instant also at 5.3.

Anthropic are really the only ones who managed to get this under control: Three models, priced at three different levels. New models are immediately available everywhere.

Google essentially only has Preview models! The last GA is 2.5. As a developer, I can either use an outdated model or have zero insurances that the model doesn't get discontinued within weeks.
__jl__
·قبل 5 أشهر·discuss
Another preview release. Does that mean the recommended model by Google for production is 2.5 Flash and Pro? Not talking about what people are actually doing but the google recommendation. Kind of crazy if that is the case
__jl__
·قبل 5 أشهر·discuss
Impressive jump for GPT-5.3-codex and crazy to see two top coding models come out on the same day...
__jl__
·قبل 6 أشهر·discuss
Yes you can and I really like it as a feature. But it ties you to OpenAI…
__jl__
·قبل 7 أشهر·discuss
I will have to try that. Cursor bill got pretty high with Opus 4.5. Never considered opus before the 4.5 price drop but now it's hard to change... :)
__jl__
·قبل 7 أشهر·discuss
Mostly at the time of release except for 1.5 Flash which got a price drop in Aug 2024.

Google has been discontinuing older models after several months of transition period so I would expect the same for the 2.5 models. But that process only starts when the release version of 3 models is out (pro and flash are in preview right now).
__jl__
·قبل 7 أشهر·discuss
This is awesome. No preview release either, which is great to production.

They are pushing the prices higher with each release though: API pricing is up to $0.5/M for input and $3/M for output

For comparison:

Gemini 3.0 Flash: $0.50/M for input and $3.00/M for output

Gemini 2.5 Flash: $0.30/M for input and $2.50/M for output

Gemini 2.0 Flash: $0.15/M for input and $0.60/M for output

Gemini 1.5 Flash: $0.075/M for input and $0.30/M for output (after price drop)

Gemini 3.0 Pro: $2.00/M for input and $12/M for output

Gemini 2.5 Pro: $1.25/M for input and $10/M for output

Gemini 1.5 Pro: $1.25/M for input and $5/M for output

I think image input pricing went up even more.

Correction: It is a preview model...
__jl__
·قبل 8 أشهر·discuss
API pricing is up to $2/M for input and $12/M for output

For comparison: Gemini 2.5 Pro was $1.25/M for input and $10/M for output Gemini 1.5 Pro was $1.25/M for input and $5/M for output
__jl__
·قبل 8 أشهر·discuss
API pricing is up to $2/M for input and $12/M for output

For comparison: Gemini 2.5 Pro was $1.25/M for input and $10/M for output Gemini 1.5 Pro was $1.25/M for input and $5/M for output
__jl__
·قبل 8 أشهر·discuss
Same here. They have been aggressively increasing prices with each iteration (maybe because they started so low). Still hope that is not the case this time. GPT 5.1 is priced pretty aggressively so maybe that is an incentive to keep the current gemini API prices.
__jl__
·قبل 8 أشهر·discuss
The prompt caching change is awesome for any agent. Claude is far behind with increased costs for caching and manual caching checkpoints. Certainly depends on your application but prompt caching is also ignored in a lot of cost comparisons.
__jl__
·قبل 9 أشهر·discuss
Since we have cursor people joining, let me bring up my constant problems around applying code changes. For background, I mostly work with "chat":

1. The apply button does not appear. This used to be mostly a problem with Gemini 2.5 Pro and GPT-5 but now sometimes happens with all models. Very annoying because I have to apply manually

2. Cursor doesn't recognize which file to apply changes to and just uses the currently open file. Also very annoying and impossible to change the file to which I want to apply changes after they were applied to one file.
__jl__
·السنة الماضية·discuss
Here are my two cents on cursors versus windsurf approach:

CURSOR shifted to a more agentic approach even for chat requests to reduce input tokens.

Previously, they used the good old RAG pattern with code dumps: Request with user added files -> Retrieval (when Codebase enabled) -> LLM requests with combined context from user and retrieval.

Now they seem to be doing something like this: Request -> LLM with tools to search code base and/or user-added files

I get constant search tool calls even for user-added files. Big reduction in input token but I think performance suffers as well.

WINDSURF is still willing to dump code into the context, which gives them an edge in some cases (presumably at a cost of input tokens).

Windsurf is willing to spent to acquire customers (lower subscription cost, higher expenses for llm calls). Cursor has a huge customer base and is working on making it sustainable by a) reducing costs (see above) and b) increasing revenue (e.g. "Pro" requests for 0.05 with more input and output token).