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“it’s-a-lemon”—openai’s-largest-ai-model-ever-arrives-to-mixed-reviews

“It’s a lemon”—OpenAI’s largest AI model ever arrives to mixed reviews

Perhaps because of the disappointing results, Altman had previously written that GPT-4.5 will be the last of OpenAI’s traditional AI models, with GPT-5 planned to be a dynamic combination of “non-reasoning” LLMs and simulated reasoning models like o3.

A stratospheric price and a tech dead-end

And about that price—it’s a doozy. GPT-4.5 costs $75 per million input tokens and $150 per million output tokens through the API, compared to GPT-4o’s $2.50 per million input tokens and $10 per million output tokens. (Tokens are chunks of data used by AI models for processing). For developers using OpenAI models, this pricing makes GPT-4.5 impractical for many applications where GPT-4o already performs adequately.

By contrast, OpenAI’s flagship reasoning model, o1 pro, costs $15 per million input tokens and $60 per million output tokens—significantly less than GPT-4.5 despite offering specialized simulated reasoning capabilities. Even more striking, the o3-mini model costs just $1.10 per million input tokens and $4.40 per million output tokens, making it cheaper than even GPT-4o while providing much stronger performance on specific tasks.

OpenAI has likely known about diminishing returns in training LLMs for some time. As a result, the company spent most of last year working on simulated reasoning models like o1 and o3, which use a different inference-time (runtime) approach to improving performance instead of throwing ever-larger amounts of training data at GPT-style AI models.

OpenAI's self-reported benchmark results for the SimpleQA test, which measures confabulation rate.

OpenAI’s self-reported benchmark results for the SimpleQA test, which measures confabulation rate. Credit: OpenAI

While this seems like bad news for OpenAI in the short term, competition is thriving in the AI market. Anthropic’s Claude 3.7 Sonnet has demonstrated vastly better performance than GPT-4.5, with a reportedly more efficient architecture. It’s worth noting that Claude 3.7 Sonnet is likely a system of AI models working together behind the scenes, although Anthropic has not provided details about its architecture.

For now, it seems that GPT-4.5 may be the last of its kind—a technological dead-end for an unsupervised learning approach that has paved the way for new architectures in AI models, such as o3’s inference-time reasoning and perhaps even something more novel, like diffusion-based models. Only time will tell how things end up.

GPT-4.5 is now available to ChatGPT Pro subscribers, with rollout to Plus and Team subscribers planned for next week, followed by Enterprise and Education customers the week after. Developers can access it through OpenAI’s various APIs on paid tiers, though the company is uncertain about its long-term availability.

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cutting-edge-chinese-“reasoning”-model-rivals-openai-o1—and-it’s-free-to-download

Cutting-edge Chinese “reasoning” model rivals OpenAI o1—and it’s free to download

Unlike conventional LLMs, these SR models take extra time to produce responses, and this extra time often increases performance on tasks involving math, physics, and science. And this latest open model is turning heads for apparently quickly catching up to OpenAI.

For example, DeepSeek reports that R1 outperformed OpenAI’s o1 on several benchmarks and tests, including AIME (a mathematical reasoning test), MATH-500 (a collection of word problems), and SWE-bench Verified (a programming assessment tool). As we usually mention, AI benchmarks need to be taken with a grain of salt, and these results have yet to be independently verified.

A chart of DeepSeek R1 benchmark results, created by DeepSeek.

A chart of DeepSeek R1 benchmark results, created by DeepSeek. Credit: DeepSeek

TechCrunch reports that three Chinese labs—DeepSeek, Alibaba, and Moonshot AI’s Kimi—have now released models they say match o1’s capabilities, with DeepSeek first previewing R1 in November.

But the new DeepSeek model comes with a catch if run in the cloud-hosted version—being Chinese in origin, R1 will not generate responses about certain topics like Tiananmen Square or Taiwan’s autonomy, as it must “embody core socialist values,” according to Chinese Internet regulations. This filtering comes from an additional moderation layer that isn’t an issue if the model is run locally outside of China.

Even with the potential censorship, Dean Ball, an AI researcher at George Mason University, wrote on X, “The impressive performance of DeepSeek’s distilled models (smaller versions of r1) means that very capable reasoners will continue to proliferate widely and be runnable on local hardware, far from the eyes of any top-down control regime.”

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