Google releases Nano Banana 2.1 image model: $1.50/$30 per 1M tokens, 66K context

Google's Nano Banana 2.1 (google/gemini-nano-banana-2.1) is an image generation and editing model on the Flash tier, listed on OpenRouter at $1.50 per 1M input tokens and $30 per 1M output tokens with a 66K context window. The listing gives a release date of October 6, 2026.

Key specifications

• Model: Nano Banana 2.1 (Gemini Nano Banana 2.1), Flash tier
• Inputs: text and images
• Outputs: images, with optional text
• Output resolution: 1K, 2K, and 4K
• Aspect ratios: extended ratios, set via the image_config API parameter
• Context window: 66K
• Pricing: $1.50 input / $30 output per 1M tokens. The provider table also shows a $7.50 per 1M figure under an "Output" column; its exact meaning is not clarified in the listing.
• Parameter count, training cutoff, benchmark scores: not disclosed

What Google says changed

The listing describes Nano Banana 2.1 as the successor to both Nano Banana 2 and Nano Banana Pro. It claims improvements in product recontextualization, mask- and ink-based editing, and factual accuracy. It also says the model renders photorealistic skin tones, detailed materials, lighting, and coherent backgrounds. No benchmark data or independent evaluations accompany these claims.

Pricing against the Nano Banana family

Using OpenRouter's listed rates for the other Google image models:

Model	Context	Input / Output per 1M
Nano Banana 2 Lite	66K	$0.25 / $30
Nano Banana 2	131K	$0.50 / $60
Nano Banana 2.1	66K	$1.50 / $30
Nano Banana Pro	131K	$2 / $120

Nano Banana 2.1 charges half the output rate of Nano Banana 2 and a quarter of Nano Banana Pro's. Its input rate is three times that of Nano Banana 2. Its context window is half that of both predecessors.

Performance and availability

OpenRouter lists Google AI Studio as the sole provider, with a P50 end-to-end latency of 19.08 seconds. OpenRouter's availability figure for the model over the last 24 hours is 68.62%. The page notes that it can reroute to another healthy provider after an upstream error, but only one provider is currently listed, so that fallback does not apply here. Usage data for apps is not yet available.

The listing does not state whether the model carries SynthID watermarking. Google's smaller Nano Banana 2 Lite is described as doing so.

What this means

Google appears to be splitting the Nano Banana line by cost structure rather than by a single quality ladder. Nano Banana 2.1 pairs a higher input price with a much lower output price than Nano Banana 2 and Pro. Image output tokens dominate generation costs, so per-image costs should fall compared with Nano Banana 2 and Pro, though the listing does not give per-image pricing. Workloads that send many reference images or long prompts will pay more on the input side than they would on Nano Banana 2.

The halved context window (66K versus 131K) is a trade-off for multi-image composition and long-prompt workflows, and teams should test before migrating.

The 68.62% availability and single-provider routing are the main production risks at launch. Until Google publishes benchmarks or third parties run evaluations, the editing and factual-accuracy improvements remain unverified claims.