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A synthesis of 7 perspectives on AI, machine learning, models release, models benchmarks, trending AI products
AI-Generated Episode
On this episode of The NeuralNoise Podcast, we dig into Google’s new “workhorse” model Gemini 3 Flash, OpenAI’s upgraded GPT Image 1.5, and what all this means for the price of intelligence in 2025.
Google’s latest release, Gemini 3 Flash, is a clear shot at the middle of the market: a frontier‑level model tuned for speed and price, not just bragging rights.
Benchmarks tell most of the story. On Humanity’s Last Exam (no tools), Gemini 3 Flash scores 33.7%, up from 11% for 2.5 Flash and close to GPT‑5.2’s 34.5%. On MMMU‑Pro, a multimodal and reasoning benchmark, it actually outperforms all rivals with 81.2%. For coding, Google says the sibling Pro model hits 78% on SWE‑Bench Verified, second only to GPT‑5.2.
The strategy: make Flash the everyday default. It’s now the standard model in the Gemini app and in AI mode for search worldwide. Pro remains available when you explicitly need heavier math or coding. Flash is also deeply multimodal:
It now leans harder into visual answers, mixing images and tables into responses, and powers rapid app prototyping when paired with Google’s Opal “vibe‑coding” tool inside Gemini.
On the enterprise side, JetBrains, Figma, Cursor, Harvey and Latitude are already using Gemini 3 Flash via Vertex AI and Gemini Enterprise. Developers can access it through the API and Google’s Antigravity coding environment. Pricing lands at $0.50 per million input tokens and $3.00 per million output tokens—more than 2.5 Flash, but Google argues that 3x speed and ~30% fewer thinking tokens per task can make total job cost go down, not up.
Underneath the launch is a clear competitive backdrop: Google says it’s now processing over 1 trillion tokens per day on its API, and OpenAI reportedly triggered a “code red” internally as Gemini models began to erode ChatGPT traffic.
OpenAI’s answer on the vision front is GPT Image 1.5, a major upgrade to ChatGPT Images and a direct response to Google’s Nano Banana Pro. Where Gemini 3 Flash focuses on fast general intelligence, GPT Image 1.5 focuses on fidelity and control.
The new model:
OpenAI also redesigned the experience around the model. There’s now a dedicated Images space inside ChatGPT, with preset styles, trending prompts, and a one‑time likeness upload so you can reuse your face across creations. You can generate while other images are still in progress, encouraging more exploratory workflows.
On the API side, GPT‑Image‑1.5 brings the same gains with 20% cheaper image in/out costs versus GPT Image 1. That matters for teams generating large catalogs of product variants, branded graphics or marketing visuals at scale. Early adopters like Wix report that prompt adherence and visual consistency are strong enough to treat it as a flagship image model.
In parallel, OpenAI’s broader GPT‑5.2 launch is framed as the frontier engine for long‑running agents and professional work, with state‑of‑the‑art scores on benchmarks like GDPval, SWE‑Bench, GPQA Diamond and AIME 2025.
Ben Tossell’s recent newsletter, “Cheap intelligence, expensive AI,” captures the emerging paradox of 2025: capability per dollar is exploding, but headline prices for top‑tier models are drifting up.
Gemini 3 Flash is emblematic. It outperforms earlier “Pro‑class” models on many tasks at a fraction of the latency and, in some cases, total task cost. Yet unit pricing has climbed steadily across the Gemini Flash line. The same pattern holds elsewhere: GPT‑5.2 Pro, Claude Opus 4.5, and top creative or coding tiers command premium rates, even as lower‑end and open models (from Mistral or DeepSeek, for example) offer staggering value at the bottom.
For builders, the new game is no longer “Which is the single best model?” but “What’s the cheapest model that is good enough for this workflow?” That’s driving:
The competitive pressure is already reshaping strategy. Google is positioning Flash as the bulk‑task “workhorse” for enterprises. OpenAI is doubling down on polished UX, richer multimodal experiences, and a platform model for third‑party apps. Anthropic and others are racing to keep agentic coding and long‑horizon reasoning as their home turf.
We’re entering a phase where frontier‑level intelligence is no longer scarce, but high‑quality packaging of that intelligence—into fast, cheap, reliable workflows—is. Gemini 3 Flash and GPT Image 1.5 show how both Google and OpenAI are now optimizing for speed, control and total cost of ownership, not just benchmark peaks. For users and developers, the winners won’t necessarily be whoever has the single “smartest” model, but whoever can deliver the right mix of capability, latency and price for specific, real‑world jobs.