Introduction
Nano Banana — Google’s image generation and editing model that started life as a viral mystery on LMArena — has grown into one of the most requested AI tools developers want to plug into their own products. With Nano Banana 2 now rolling out across the ecosystem, the question isn’t really whether you can get access, but where you should get it from. Direct access through Google AI Studio works fine for prototyping, but most teams shipping real products end up routing through an aggregator or specialized inference host instead. Pricing, latency, regional availability, and the surrounding tooling all start to matter once you go past a few test calls.
This second roundup looks at nine platforms currently serving the Nano Banana API, with a fresh angle on what each one actually does well in practice. We’ll keep things grounded in real use cases, real billing structures, and real trade-offs.
TL;DR — Quick Comparison Table
| Rank | Platform | Nano Banana 2 Price (1K) | What Sets It Apart |
| 1 | ApiPass | $0.0455 / image | Cheapest rate, OpenAI-compatible router |
| 2 | WaveSpeed | $0.08 / image | Edge-accelerated, sub-second outputs |
| 3 | RunComfy | $19.99/mo + GPU | ComfyUI cloud with serverless deploy |
| 4 | Replicate | $0.067 / image | Mature model registry, versioned runs |
| 5 | Poe | Subscription ($4.17+/mo) | Chat-first interface, bot ecosystem |
| 6 | PiAPI | $0.06 / image | Async jobs, no-code workspace |
| 7 | Fal.ai | $0.067 / image | Realtime streaming, JS-first SDK |
| 8 | Evolink | $0.063 / image | Per-component credit billing |
| 9 | AI/ML API | ~$0.07 / image | 300+ models behind one key |
1. ApiPass
Introduction
ApiPass takes the “one router for everything” approach to AI infrastructure. Instead of negotiating with each model vendor separately, you point your code at a single OpenAI-compatible endpoint and switch model names in the request body. The latest Nano Banana 2 is wired in alongside Nano Banana Pro, and the pricing has been one of the more aggressive ones we’ve seen this cycle.
Features
- Single OpenAI-style endpoint covering Nano Banana 2 and hundreds of other models
- 1K, 2K, and 4K Nano Banana 2 resolution support, billed separately
- Credit top-ups instead of monthly commitment
- Built-in usage dashboard with per-model spend tracking
- Same key works across image, video, audio, and LLM endpoints
- Global routing so latency stays reasonable outside the US
Pros & Cons
Pros:
- The 1K price of $0.0455 is the lowest on this list
- Migrating from another OpenAI-compatible provider takes minutes
- No need to maintain multiple billing relationships
Cons:
- Some of the more niche model parameters need to be passed through manually
- Brand awareness is still catching up to the legacy hosts
Pricing
- 1K image: $0.0455 / image
- 2K image: $0.0682 / image
- 4K image: $0.1000 / image
Best For
Indie developers, AI app startups, and small teams that don’t want to spread their billing across five different vendors and just want the cheapest reliable Nano Banana 2 endpoint they can find.
2. WaveSpeed
Introduction
WaveSpeed has built its name around one promise: make hosted inference feel instant. The team puts a lot of engineering into kernel-level optimization and edge GPU placement, and it shows in how Nano Banana 2 performs through their endpoints. If your product is something like a live photo editor or a chat tool that drops images mid-conversation, WaveSpeed is one of the few platforms that won’t make the experience feel laggy.
Features
- Edge-accelerated GPU inference with regional routing
- Single endpoint covering all Nano Banana 2 resolution tiers
- Multiplier-based pricing tied to base 1K rate
- Async polling and webhook callback options
- Detailed timing logs returned with each response
Pros & Cons
Pros:
- Among the fastest cold-start times for hosted Nano Banana
- Pricing math is easy once you know the base rate
- Generous concurrency limits compared to some peers
Cons:
- 4K outputs cost twice the base rate, which adds up on bulk jobs
- Web search add-on is a separate per-request charge
Pricing
- Base rate: $0.08 / image at 1K
- 2K: 1.5x base
- 4K: 2x base
- 0.5K: 0.75x base
- Web search: +$0.015 / request
Best For
Realtime apps, live editors, and any product where users are sitting there waiting for an image to render — and a five-second delay is a problem.
3. RunComfy
Introduction
RunComfy is built around ComfyUI rather than around a flat API, and that shapes everything about the experience. You get a full ComfyUI environment in the browser, hooked into dedicated GPUs, with the option to expose any workflow as a serverless API endpoint. Nano Banana 2 lives inside that graph as a node you can wire up to whatever pre-processing, post-processing, or chaining logic you need.
Features
- Native ComfyUI in the cloud with custom node installs
- GPU options ranging from 16 GB to 141 GB VRAM
- One-click “turn this workflow into an API” deployment
- Persistent storage for workflows, models, and assets
- Built-in trainer for fine-tuning and LoRA work
Pros & Cons
Pros:
- Hard to beat if you already think in ComfyUI graphs
- The serverless deploy flow saves a huge amount of glue code
- Pro plan throws in $10/month in credits plus 20%+ off GPU rates
Cons:
- Billing combines subscription and hourly GPU, which takes some getting used to
- Probably more platform than you need for a single text-to-image call
Pricing
- Pay as You Go: GPU billed hourly, no subscription
- Pro: $19.99/month (billed $239.90/year), 20%+ off GPU, $10 monthly credits, 200 GB storage
Best For
Visual artists, prompt engineers, and studios that already live inside ComfyUI and want to ship those workflows as APIs without rebuilding the logic in Python.
4. Replicate
Introduction
Replicate has been around long enough to be many developers’ default mental model for “running a model in the cloud.” Models are versioned, runs are reproducible, and the API surface barely changes from one model to the next. Nano Banana 2 fits cleanly into that pattern, which is part of why teams already on Replicate tend to just stay there.
Features
- Stable, versioned model endpoints
- Cog-based model packaging if you want to bring your own
- Webhooks and async predictions out of the box
- Detailed logs and prediction history per run
- Strong CLI and integrations with notebooks
Pros & Cons
Pros:
- Versioning makes long-lived production deployments much safer
- Predictable schema across thousands of models
- Documentation and community examples are extensive
Cons:
- Pricing is fair but not the cheapest in this group
- Higher resolutions scale up faster than the per-image average suggests
Pricing
- 1K target resolution: $0.067 / image (~14 images for $1)
- 2K target resolution: $0.101 / image (~99 images for $10)
- 4K target resolution: $0.151 / image (~66 images for $10)
Best For
Teams that value stability, reproducibility, and a model registry they can trust to behave the same next month as it does today.
5. Poe
Introduction
Poe is the odd one on this list because it isn’t really pitched at developers — it’s a consumer app from Quora that aggregates dozens of frontier models into one chat interface. But Nano-Banana-2 from Google sits in there alongside GPT, Claude, and Gemini, and Poe also lets creators build bots that wrap those models. For some workflows — especially content creators iterating on prompts — it’s actually a more productive surface than a raw API.
Features
- Unified chat UI across many top models
- Bot builder for custom prompt-wrapped experiences
- Daily and monthly point budgets per subscription tier
- iOS, Android, web, and desktop apps
- Shared bot directory for community-built tools
Pros & Cons
Pros:
- Smoothest experience for non-developers and prompt iteration
- A single subscription replaces several individual model subscriptions
- Bot framework is surprisingly capable for lightweight tools
Cons:
- Not built for programmatic, high-volume API use
- Image generation eats points fast — output image costs $60.61 / 1M tokens
Pricing
- 10,000 points/day: $4.17/month ($49.99/year)
- 1M points/month: $199.99/year
- 2.5M points/month: $499.99/year
- 5M points/month: $999.99/year
Best For
Writers, designers, marketers, and prompt engineers who want to use Nano Banana 2 in a chat workflow rather than wire it into their own code.
6. PiAPI
Introduction
PiAPI sits somewhere between an API host and a creator platform. You get straightforward Nano Banana 2 endpoints, but you also get a no-code workspace, async job queues, and commercial usage rights bundled into every plan. It’s particularly common among teams that need to hand off generation tasks to non-engineers — marketing, ops, design — without giving them an API key.
Features
- Async API with task IDs and webhook callbacks
- Browser-based workspace for non-technical users
- Up to 14 reference images per request
- Multiple resolution tiers with flat pricing
- Commercial licensing included
- Round-the-clock technical support
Pros & Cons
Pros:
- Async-first design fits batch generation pipelines well
- The no-code side reduces friction for cross-functional teams
- Flat per-resolution pricing makes cost projection easy
Cons:
- Per-image price isn’t the absolute lowest at higher resolutions
- The workspace overlaps with what you might already have internally
Pricing
- Nano Banana 2 — 1K: $0.06 / image
- Nano Banana 2 — 2K: $0.08 / image
- Nano Banana 2 — 4K: $0.12 / image
Best For
Agencies, content shops, and product teams where engineers and non-engineers need to share the same Nano Banana setup.
7. Fal.ai
Introduction
Fal.ai has carved out its niche as the platform developers reach for when they want generative AI to feel like part of the frontend, not a back-office job. The JavaScript SDK is genuinely first-class, streaming is built into the core protocol, and Nano Banana 2 inherits all of that infrastructure. It’s the kind of host that quietly makes a demo feel polished.
Features
- Realtime streaming for progressive image delivery
- JS/TS SDK with React hooks for client-side calls
- Queue API with status polling and cancellation
- Multiplier-based pricing across resolutions
- Optional add-ons for web search and high-thinking modes
Pros & Cons
Pros:
- The best front-end developer experience among the platforms here
- Streaming makes interactive UIs much more compelling
- Performance under load is consistent
Cons:
- 2K and 4K outputs scale at 1.5x and 2x, which can sting on large jobs
- Add-on charges stack up if you’re using multiple optional features
Pricing
- 1K image: $0.067 / image (~12 images per $1)
- 2K image: 1.5x base rate
- 4K image: 2x base rate
- 0.5K image: 0.75x base rate
- Web search: +$0.015 / request
- High thinking: +$0.002 / request
Best For
Frontend-heavy teams building interactive web apps where users expect images to appear in seconds, not minutes.
8. Evolink
Introduction
Evolink takes a more accountant-friendly approach to inference billing. Instead of one flat price per image, it breaks every request into parts — input image, output image at a given resolution, search calls, text tokens — and charges for each one as a separate credit line. It’s a bit more work to estimate upfront, but it pays off if you’re trying to squeeze every cent out of a production pipeline.
Features
- Credit-based billing with USD-equivalent rates visible per modality
- Separate line items for input, output, search, and text tokens
- Resolution tiers from 0.5K through 4K
- Rule-based pricing rules viewable per model
- Web search and image search as optional features
Pros & Cons
Pros:
- Easiest platform to do real cost modeling on
- Lower-than-average price at 1K ($0.063)
- Granular control over which features you pay to enable
Cons:
- The detailed pricing scheme has a learning curve
- Smaller ecosystem and fewer integrations than the big aggregators
Pricing
- Input image: $0.0005 / image
- Output image (0.5K): $0.042
- Output image (1K): $0.063
- Output image (2K): $0.094
- Output image (4K): $0.141
- Web/Image search: $0.013 / request
Best For
Engineering teams optimizing a high-volume pipeline who need to know exactly what each line of cost is and where to trim.
9. AI/ML API
Introduction
AI/ML API is one of the larger aggregator plays in the space, with a catalog north of 300 models served through a unified, OpenAI-style endpoint. Nano Banana 2 and Nano Banana Pro both show up here, and the platform is well-positioned for teams that want enterprise support and a deep model bench in one contract.
Features
- 300+ model catalog under a single API
- OpenAI-compatible REST surface
- Enterprise SLAs, billing terms, and support tiers
- Built-in monitoring and analytics
- Both Nano Banana 2 and Nano Banana Pro available
Pros & Cons
Pros:
- Deep catalog if your roadmap touches lots of model types
- Solid choice for procurement-driven enterprise buyers
- Documentation and SDKs are well-maintained
Cons:
- Per-image price runs a touch above the cheapest options
- Pricing details aren’t always visible without an account
Pricing
- Nano Banana 2: ~$0.07 / image (14 images per $1)
- Nano Banana Pro: ~$0.14 / image (7 images per $1)
Best For
Mid-market and enterprise teams that need a single AI vendor with broad model coverage and the contractual footing to back it up.
Conclusion
The Nano Banana API landscape has matured fast. ApiPass leads on price and multi-model convenience, WaveSpeed on raw speed, RunComfy on ComfyUI integration, Replicate on stability, Poe on consumer experience, PiAPI on hybrid no-code/API workflows, Fal.ai on frontend developer experience, Evolink on billing transparency, and AI/ML API on enterprise breadth. There isn’t a single winner — there’s just the one that fits your stack, your team, and your budget the best. With Nano Banana 2 now widely served across all nine of these platforms, that decision is yours to make.
