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Now compare the monthly plans for business users who want the CLI agent but who don’t want the models trained on their data.

OpenAI: no big deal — sign up, pick your number of seats, and you’re all set.

Anthropic: also no big deal but there’s an obnoxious minimum purchase.

Google: first you have to try to figure out what the product is called. Then you need to figure out how to set the correct IAM rules. Then you have to sign up and pay for it. Maybe you succeed. Maybe you give up after an hour or two of cursing. Gemini is, of course, completely unable to help. (OpenAI clearly has not trained their models on how to operate their tools. Google’s models hallucinate Google’s product offerings so outrageously that I’m not sure I could tell. I haven’t asked Claude about Claude Code.)

At least the monthly pricing is similar once you get over the hurdles.

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There's a reason Google model usage on OpenRouter is so high - it's easier to pay the OpenRouter tax than it is to figure out how to pay Gemini directly.
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Well some are using Anthropic on AWS Bedrock which is a bit more like the Google paragraph. Perhaps a good thing that Nova models aren't competitive (and many here are asking "What's a Nova model?"). And remember, many businesses aren't flinching at IAM controls and are asking for data privacy contracts.
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Well some are masochists.
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I can confirm the products bit, I tried to use Gemini to help with G Suite admin.
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If we don't see a huge gain on the long-term horizon thinking reflected with the Vendor-Bench 2, I'm not going to switch away from CC. Until Google can beat Anthropic on that front, Claude Code paired with the top long-horizon models will continue to pull away with full stack optimizations at every layer.
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still no minimal reasoning in G3.1P :(

(this is why Opus 4.6 is worth the price -- turning off thinking makes it 3x-5x faster but it loses only a small amount of intelligence. nobody else has figured that out yet)

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Thinking is just tacked on for Anthropic's models and always has been so leaving it off actually produces better results everytime.
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What about for analysis/planning? Honestly I've been using thinking, but if I don't have to with Opus 4.6 I'm totally keen to turn it off. Faster is better.
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Looks like its cheaper than codex ??? this might be interesting then
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It's not trained for agentic coding I don't think
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> Knowledge cutoff is unchanged at Jan 2025.

Isn't that a bit old?

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Old relative to its competitors, but the Search tool can compensate for it.
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Sounds like the update is mostly system prompt + changes to orchestration / tool use around the core model, if the knowledge cutoff is unchanged
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knowledge cutoff staying the same likely means they didn't do a new pre-train. We already knew there were plans from deepmind to integrate new RL changes in the post training of the weights. https://x.com/ankesh_anand/status/2002017859443233017
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This keeps getting repeated for all kinds of model releases, but isn’t necessarily true. It’s possible to make all kinds of changes without updating the pretraining data set. You can’t judge a model’s newness based on what it knows about.
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