Qwen Image 3.0 vs Nano Banana 2 API (2026): Price, Resolution, Image Quality and When to Use Each

Qwen Image 3.0 and Nano Banana 2 are both solid picks for programmatic image generation on HiAPI. They're not trying to do the same thing, though — one is tuned for Chinese typography and flat-rate volume, the other trades up to 4K output with a tiered resolution price. This guide walks through the concrete differences so you can pick the right one for your stack.

At a Glance

Price and Resolution in Practice

Nano Banana 2 is the cheaper choice at every resolution tier. At 1K, it runs $0.018 per image versus Qwen Image 3.0 Std's flat $0.0358 — roughly half the cost. At 2K, NB2 is $0.0285 against Qwen Pro's $0.0993, less than a third of the price. And NB2 goes to 4K ($0.043) when you need it; neither Qwen tier reaches 4K.

Qwen Image 3.0 Std has one real pricing advantage: it's genuinely flat. No resolution policy, no tier math — every image at any supported size costs $0.0358. For teams that want predictable billing without thinking about resolution inputs, that simplicity has real value.

If you're running i2i workflows, both models add a per-reference surcharge: Qwen's i2i routes add $0.004 per reference image (1–3 refs). Nano Banana 2 handles i2i through the same model ID using image_input, with up to 14 reference images.

100-image batch cost comparison:

• Qwen 3.0 Std t2i (any size): $3.58
• Nano Banana 2 at 1K: $1.80
• Nano Banana 2 at 2K: $2.85
• Nano Banana 2 at 4K: $4.30
• Qwen 3.0 Pro at 2K: $9.93

API Schema Differences

Both use HiAPI's async task protocol: POST /v1/tasks → poll GET /v1/tasks/{taskId} until status is success or fail, then read output[0].url. The schemas diverge in the input fields.

Qwen Image 3.0 (text-to-image):

{
  "model": "qwen-image-3.0/text-to-image",
  "input": {
    "prompt": "A cinematic product poster with bold English headline 'NOIR'",
    "aspect_ratio": "16:9",
    "resolution": "2K",
    "output_format": "png",
    "prompt_extend": true,
    "negative_prompt": "blurry, low quality"
  }
}

prompt_extend is Qwen-specific — it auto-expands terse prompts. The t2i route does not accept reference images; use qwen-image-3.0/image-to-image with image_urls for that.

Nano Banana 2 (t2i and i2i, same model ID):

{
  "model": "nano-banana-2",
  "input": {
    "prompt": "A cinematic product poster with bold English headline 'NOIR'",
    "aspect_ratio": "4:3",
    "resolution": "2K",
    "output_format": "jpg",
    "image_input": ["https://example.com/ref1.jpg"]
  }
}

NB2 uses image_input (array of URLs) for references — not image_urls, which is a different Qwen field. Pass resolution as "1K", "2K", or "4K". Omitting resolution defaults to 1K.

Side-by-Side: Same Prompt, Both Models

We ran the same product poster prompt through both at 1K to compare output character.

Prompt used:

Studio editorial product poster. A sleek dark glass perfume bottle with the embossed 
label 'NOIR' sits on a polished obsidian surface. Soft rim lighting from the left 
casts a long thin shadow to the right. Background: deep charcoal gradient. 
Bottom-right corner text in small clean sans-serif: 'Limited Edition 2026'. 
Photorealistic commercial photography style, 4:3.

Both rendered the perfume bottle prompt cleanly. Qwen 3.0 Std leaned into tighter editorial lighting with a cooler tone; NB2 produced warmer reflections with slightly more specular highlights on the glass. Neither hallucinated extra objects. Text rendering — the small "Limited Edition 2026" label — came through legibly on both, which is consistent with both models' documented strengths.

Qwen Image 3.0 output:

Nano Banana 2 output:

NB2 generated noticeably faster on this run (~32 seconds vs ~72 seconds for Qwen). That gap will vary by load, but NB2's speed advantage is consistent with its Gemini Flash lineage.

Text Rendering

Both models handle English text reliably. Qwen Image 3.0 is specifically optimized for Chinese characters — it's the stronger pick for bilingual posters, Chinese product labels, and mixed CJK/Latin layouts. NB2 handles English well but isn't documented as a Chinese-text specialist.

If Chinese text accuracy is a hard requirement, use Qwen Image 3.0.

When to Use Each

Choose Qwen Image 3.0 Std when:

• You need Chinese text rendered accurately in the image
• You want flat, predictable billing regardless of output size
• Your workflow uses 1–3 reference images for i2i editing
• You're generating posters, editorial scenes, or concept art in CJK contexts

Choose Nano Banana 2 when:

• Cost per image is the primary constraint — NB2 is cheaper at every resolution
• You need 4K output (Qwen maxes at 2K)
• Your i2i workflow references many images (up to 14 vs Qwen's 3)
• Speed matters — NB2 typically generates faster
• You want a single model ID that handles both t2i and i2i without route-switching

Choose Qwen Image 3.0 Pro when:

• You need higher fidelity for complex materials, dense layouts, or typography-heavy compositions at 2K
• The quality step-up justifies the ~3× price over NB2 at 2K

FAQ

Can I use both models with the same API key? Yes. Both use the same HiAPI Bearer token and the same /v1/tasks endpoint. Switch between them by changing the model field.

Does resolution affect billing for Qwen Image 3.0 Std? No. The standard tier is flat at $0.0358 per image regardless of whether you request 1K or 2K output. Only the Pro tier has resolution-based pricing.

How do I pass reference images to Nano Banana 2? Add an image_input array of publicly accessible image URLs to the input object. Up to 14 references are supported. This is the same model ID as t2i — there is no separate route for i2i.

Does Qwen Image 3.0 support 4K? No. Both Std and Pro tiers top out at 2K. Use Nano Banana 2 if you need 4K output.

How is billing handled for failed tasks? HiAPI does not charge for failed tasks on either model. Only successful generations count toward your balance.

What aspect ratios does each model support? Qwen Image 3.0 supports 8 ratios: 1:1, 3:2, 2:3, 4:3, 3:4, 16:9, 9:16, 21:9. Nano Banana 2 supports 15, including auto, 1:4, 4:1, 1:8, 8:1, and all of Qwen's options.

Related Reading

• Qwen Image 3.0 Prompt Recipes: Copy-Paste Prompts With Real Outputs
• Qwen Image 3.0 Image-to-Image Prompt Recipes
• GPT Image 2 vs Nano Banana 2: Side-by-Side With the Same Prompts
• HiAPI Pricing