Google’s Redemption Arc Continues With Gemini 2.5 Flash
Until recently, Google’s position in the AI race felt uncertain. However, the company’s redemption arc changed it all for the tech giant. The turning point arguably began with Gemini 2.0 Flash, proving that Google could deliver competitive performance with a lightweight and efficient model. Then came Gemini 2.5 Pro, garnering significant acclaim, particularly within the developer community, for its exceptional coding prowess. Many analysts and users ranked it among the most capable general-purpose AI models. Amplifying its appeal, the integration of the Deep Research tool, which cited hundreds of sources (more than any other competing tool) for a single report, is a key differentiator that reportedly convinced a notable number of users to explore it as a serious alternative to established platforms like OpenAI. And with the release of Gemini 2.5 Flash, Google demonstrated a new strategy that goes beyond simply improving the performance and efficiency of the model. The company is now focusing on the API pricing aspect, and Gemini 2.5 Flash is offering an impressive price-to-performance ratio, as noted by several developers. The reason Google’s Gemini 2.5 Pro’s pricing matters isn’t just that it is significantly lower than the competition, but it also outperforms several competing models, both inside and outside its segment, on standard benchmarks. Cheap, Clever and Canny For instance, consider the GPQA (General and Professional Question Answering) benchmark, which tests the advanced reasoning and knowledge capabilities of AI models. Gemini 2.5 Flash scored a 59%, with the reasoning variant scoring a 70%. This is comparable to to models Claude 3.7 Sonnet Thinking (77%), OpenAI’s o3-mini (75%), and OpenAI’s o1 (75%), and OpenAI’s GPT 4.1 (67%). Besides, the Gemini 2.5 Flash models also excel at various coding-based benchmarks. In the LiveCodeBench benchmark, Gemini 2.5 Flash reasoning scored 51%, marginally outperforming Anthropic’s Claude 3.7 Sonnet Thinking (47%), and the GPT-4.1 model (46%), which was explicitly aimed at developers. Here’s how some of the other popular models perform on the benchmarks. Source: Artificial Analysis However, Gemini 2.5 Flash models blow the competition away with their pricing. It costs just $0.15 (input) / $0.6 (output) per million tokens, and the reasoning variant costs $0.15 (input) / $3.5 (output). Source: Artificial Analysis This contrasts sharply with the other high-performing models. GPT 4.1 is priced at $2/$8, o3-mini at $1.1/$4.4, Claude 3.7 Sonnet at $3/$15, and the top-tier o1 model at a significant $15/$60 per million input/output tokens, respectively. In addition to the low pricing, Google has also enabled a ‘thinking budget’ which developers can control while using the model. This means that one can limit the number of tokens the model can generate while thinking. This lets developers keep the costs and latency in check. But Gemini 2.5 Flash’s magic doesn’t end there. Gemini 2.5 Flash is One of the Fastest AI Models Gemini 2.5 Flash, the reasoning and the non-reasoning models are the fastest. Artificial Analysis also revealed that with 346 tokens per second, it outperforms models like OpenAI’s o4-mini (64 tok/s), o3-mini (162 tok/s), and other models like GPT-4o (169 tok/s). Note that these numbers account for the performance of the model’s first-party API. Source: Artificial Analysis Gemini 2.5’s speed can be attributed to the fact that it runs on Google’s Tensor Processing Units (TPUs), which are hardware systems designed to handle AI workloads at high performance and efficiency. With all of the above advantages, the model has won praise from developers across the internet. Roo Coder with Gemini 2.5 Flash Preview Thinking is the first time I've felt like I'm commanding a real software engineer to do work for me. Claude Code comes close but it does too much silly stuff and is extremely expensive. Check it out in this little demo! @cline @roo_code pic.twitter.com/7PrgqgvJ3Y— paralinq (@paralinq) April 24, 2025 Andrew Jefferson, a software developer, said on X, “Gemini 2.5 Flash as a smart full-codebase search is surprisingly practical and affordable.” “I asked questions of codebases in the 230k-260k token range, and I get great answers in under 10s for less than 5 cents each,” he added. Besides, the model seems to offer a pleasant experience in the conversational aspect as well. Recently, OpenAI came under fire as its GPT-4o model was found to offer flattering responses to users, and let them hear what they wanted. The company eventually had to roll back the update. With regards to this, a user on X noted that “I have found Gemini 2.5 Flash to be both excellent at analysing large texts and not flattering at all.”
The model excels at coding, general-purpose tasks, with ridiculously low API pricing and outputs 200 + tokens per second.
The model excels at coding, general-purpose tasks, with ridiculously low API pricing and outputs 200 + tokens per second. 
["AI (Artificial Intelligence)", "Google"]
["Anthropic", "Go", "Gemini 2.0", "TPU", "OpenAI", "AI", "GPT-4o", "Gemini 2.5", "Aim", "Google", "R", "AI (Artificial Intelligence)"]
["AI", "GPT-4o", "OpenAI", "Anthropic", "Gemini 2.5", "Gemini 2.0", "Aim", "TPU", "R", "Go"]
Supreeth is an engineering graduate who is curious about the world of artificial intelligence and loves to write stories on how it is solving problems and shaping the future of humanity.