Nano Banana (Gemini 2.5 Flash Image) vs Qwen3-235B-A22B
Nano Banana (Gemini 2.5 Flash Image) (2025) and Qwen3-235B-A22B (2025) are compact production models from Google DeepMind and Alibaba. Nano Banana (Gemini 2.5 Flash Image) ships a 33K-token context window, while Qwen3-235B-A22B ships a 128K-token context window. On pricing, Nano Banana (Gemini 2.5 Flash Image) costs $0.3/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Qwen3-235B-A22B is safer overall; choose Nano Banana (Gemini 2.5 Flash Image) when provider fit matters.
Decision scorecard
Local evidence first| Signal | Nano Banana (Gemini 2.5 Flash Image) | Qwen3-235B-A22B |
|---|---|---|
| Decision fit | General | Coding, RAG, and Long context |
| Context window | 33K | 128K |
| Cheapest output | $30/1M tokens | $1.2/1M tokens |
| Provider routes | 3 tracked | 4 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Use Nano Banana (Gemini 2.5 Flash Image) when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Qwen3-235B-A22B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3-235B-A22B has the lower cheapest tracked output price at $1.2/1M tokens.
- Qwen3-235B-A22B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3-235B-A22B uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen3-235B-A22B for Coding, RAG, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Nano Banana (Gemini 2.5 Flash Image)
$7,740
Cheapest tracked route: Google AI Studio
Qwen3-235B-A22B
$620
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $7,120. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qwen3-235B-A22B is $28.80/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3-235B-A22B adds Structured outputs in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Nano Banana (Gemini 2.5 Flash Image) is $28.80/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-01 | 2025-04-29 |
| Context window | 33K | 128K |
| Parameters | — | 235B |
| Architecture | decoder only | decoder only |
| License | Unknown | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nano Banana (Gemini 2.5 Flash Image) | Qwen3-235B-A22B |
|---|---|---|
| Input price | $0.3/1M tokens | $0.4/1M tokens |
| Output price | $30/1M tokens | $1.2/1M tokens |
| Providers |
Capabilities
| Capability | Nano Banana (Gemini 2.5 Flash Image) | Qwen3-235B-A22B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Qwen3-235B-A22B. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Nano Banana (Gemini 2.5 Flash Image) lists $0.3/1M input and $30/1M output tokens, while Qwen3-235B-A22B lists $0.4/1M input and $1.2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-235B-A22B lower by about $8.57 per million blended tokens. Availability is 3 providers versus 4, so concentration risk also matters.
Choose Nano Banana (Gemini 2.5 Flash Image) when provider fit and lower input-token cost are central to the workload. Choose Qwen3-235B-A22B when long-context analysis, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Nano Banana (Gemini 2.5 Flash Image) or Qwen3-235B-A22B?
Qwen3-235B-A22B supports 128K tokens, while Nano Banana (Gemini 2.5 Flash Image) supports 33K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Nano Banana (Gemini 2.5 Flash Image) or Qwen3-235B-A22B?
Nano Banana (Gemini 2.5 Flash Image) is cheaper on tracked token pricing. Nano Banana (Gemini 2.5 Flash Image) costs $0.3/1M input and $30/1M output tokens. Qwen3-235B-A22B costs $0.4/1M input and $1.2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Nano Banana (Gemini 2.5 Flash Image) or Qwen3-235B-A22B open source?
Nano Banana (Gemini 2.5 Flash Image) is listed under Unknown. Qwen3-235B-A22B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Nano Banana (Gemini 2.5 Flash Image) or Qwen3-235B-A22B?
Qwen3-235B-A22B has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Nano Banana (Gemini 2.5 Flash Image) and Qwen3-235B-A22B?
Nano Banana (Gemini 2.5 Flash Image) is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, and Venice AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Nano Banana (Gemini 2.5 Flash Image) over Qwen3-235B-A22B?
Qwen3-235B-A22B is safer overall; choose Nano Banana (Gemini 2.5 Flash Image) when provider fit matters. If your workload also depends on provider fit, start with Nano Banana (Gemini 2.5 Flash Image); if it depends on long-context analysis, run the same evaluation with Qwen3-235B-A22B.
Continue comparing
Last reviewed: 2026-05-20. Data sourced from public model cards and provider documentation.