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.

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 As a developer, I can either use an outdated model or have zero insurances that the model doesn't get discontinued within weeks.

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).

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...

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

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

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.

Now 2.0 -> 2.5 is another hefty price increase.

My concern: voyage api has been unreliable. They were bought by mango db, which makes me a little uneasy.

Gemini embeddings look like a great model but it’s in preview and there haven’t been any updates for a while (including at io). Also not sure how committed Google is to embeddings models.

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).