标签：#googlegemini

Google added two new models to the Gemini API today: Nano Banana 2 Lite (image generation) and Gemini Omni Flash (video generation + editing). Neither is the Gemini 3.5 Pro release people have been waiting for, so it's easy to miss. Here's what's actually in them. TL;DR Nano Banana 2 Lite: gemini-3.1-flash-lite-image = text-to-image in ~4s, $0.034/1K images Gemini Omni Flash: gemini-omni-flash-preview = video gen + conversational editing, $0.10/sec Both are built to be chained: generate an image fast, then animate it into video Neither model is positioned as a quality upgrade = both are cost/speed plays Nano Banana 2 Lite Model ID: gemini-3.1-flash-lite-image Text-to-image output in about 4 seconds $0.034 per 1K-resolution image Positioned as the direct replacement for the original Nano Banana ( gemini-2.5-flash-image ) - if you're on that model, this is a drop-in upgrade Available in Google AI Studio, Gemini API, Gemini Enterprise Agent Platform, and consumer surfaces (Search AI Mode, Gemini app, Photos, NotebookLM, Flow, Google Ads) Gemini Omni Flash Model ID: gemini-omni-flash-preview Public preview in Google AI Studio and the Gemini API Conversational editing - refine a generated video using plain-language instructions instead of re-prompting from zero Multimodal referencing - combine text, image, and video inputs to keep a scene consistent $0.10 per second of video output (same rate as Veo 3.1 Fast) Known limitations right now Generations capped at 10 seconds No audio reference uploads yet No scene extension yet Video references under 3 seconds are accepted by the API schema but not correctly processed yet Character consistency across scene changes/pans still has rough edges Google says longer durations are coming. The part worth paying attention to: chaining them Generate an image with Nano Banana 2 Lite (fast, cheap) Pass that image as a reference into Omni Flash Omni Flash animates it into a video Both models are optimized for throughput and cost, not for to

Gemini 3.5 Pro goes general-availability in late June 2026 with a 2-million-token context window and a Deep Think reasoning mode that positions it against the most capable frontier models currently live — at a moment when the field is unusually thin. Claude Fable 5 was disabled globally on June 12 under a U.S. export control directive. GPT-5.6 remains a release candidate in Codex backend logs under the codename kindle-alpha . As of June 19, 2026, Gemini 3.5 Pro is the next major frontier model with a confirmed launch window, and it’s already live for select enterprise customers on Vertex AI. This is what’s confirmed, what’s still unknown, and what developers should do before GA drops. The Timing Isn’t an Accident Google announced Gemini 3.5 Pro at I/O on May 19 with a June general-availability target. At the time, that framing put it in direct competition with Claude Fable 5 (released June 9 before the shutdown) and the anticipated GPT-5.6. That competitive calculus shifted on June 12 when Anthropic disabled Fable 5 for all customers worldwide following an export control order. Claude Opus 4.8 is still live — it hits 88.6% on SWE-Bench and is a legitimate coding workhorse — but its 200K context ceiling blocks the entire category of codebase-scale and multi-document workloads that Fable 5 had been handling at 200K. The gap Gemini 3.5 Pro steps into isn’t hypothetical. Teams that built agent pipelines around Fable 5’s coding accuracy have been on Opus 4.8 stopgaps or migrating to GPT-5.5 since June 12. Neither alternative offers 2M context. Neither has a Deep Think mode native to the same model. Gemini 3.5 Pro is arriving into the most favorable competitive opening Google has had at the frontier in 18 months. The 2M Token Context: Where the Ceiling Disappears Gemini 3.5 Flash shipped with a 1M-token context window, doubling Gemini 3.1 Pro’s 500K limit. Pro doubles Flash again. At 2 million tokens, a single API call can hold: A 2,000-file TypeScript monorepo at 200 lin