Nano Banana Pro (Gemini 3 Pro Image) vs Qwen3.5-9B
Qwen3.5-9B costs 80.0x less per output token than Nano Banana Pro (Gemini 3 Pro Image) ($0.15 vs $12.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $12.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
Nano Banana Pro (Gemini 3 Pro Image) or Qwen3.5-9B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Nano Banana Pro (Gemini 3 Pro Image) has results on LMArena Image Edit; Qwen3.5-9B on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.5-9B has a AA Intelligence Index result, 13.3.
Directional only
Long documents
Listed context window
Qwen3.5-9B
Qwen3.5-9B takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-9B
Nano Banana Pro (Gemini 3 Pro Image) $0.0080, Qwen3.5-9B $0.0002 per turn.
List prices
At a glance
- Coding index
- Nano Banana Pro (Gemini 3 Pro Image) not benchmarked, Qwen3.5-9B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Nano Banana Pro (Gemini 3 Pro Image) $12.00 against Qwen3.5-9B $0.15 per million output tokens, 80.0x apart.
- Context window
- Nano Banana Pro (Gemini 3 Pro Image) takes 131K tokens, Qwen3.5-9B 262K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 23.5 | Only Qwen3.5-9B measured |
| SciCode | Not measured | 29.5% | Only Qwen3.5-9B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 24.2% | Only Qwen3.5-9B measured |
| Terminal-Bench | Not measured | 9.2% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 13.3 | Only Qwen3.5-9B measured |
| Epoch Capabilities Index | Not measured | 139.3 | Only Qwen3.5-9B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 86.8% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.6% | Only Qwen3.5-9B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 14.9% | Only Qwen3.5-9B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 79.0% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 61.7% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 12 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B | Leader |
|---|---|---|---|
| IFBench | Not measured | 66.7% | Only Qwen3.5-9B measured |
| Long context reasoning (AA-LCR) | Not measured | 70.0% | Only Qwen3.5-9B measured |
| DTBench | Not measured | 71.2% | Only Qwen3.5-9B measured |
| LMCA | Not measured | 24.5% | Only Qwen3.5-9B measured |
| Neither model has a result on the other 42 boards here | |||
Image generationDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B | Leader |
|---|---|---|---|
| LMArena Image Edit | 1390 | Not measured | Only Nano Banana Pro (Gemini 3 Pro Image) measured |
| Neither model has a result on the other 4 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen3.5-9B costs less
Repository review
50K input + 3K output tokens
Qwen3.5-9B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-9B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Google Nano Banana Pro (Gemini 3 Pro Image) | Qwen3.5-9B |
|---|---|---|
| Maker | Qwen | |
| Weights | No public weights listed | Open weights |
| Released | June 18, 2026 | March 10, 2026 |
| Context window | 131K | 262K |
| Input $/Mtok | $2.00 | $0.10 |
| Output $/Mtok | $12.00 | $0.15 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nano Banana Pro (Gemini 3 Pro Image) better than Qwen3.5-9B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Nano Banana Pro (Gemini 3 Pro Image) or Qwen3.5-9B?
Nano Banana Pro (Gemini 3 Pro Image) costs $2.00 per million input tokens and $12.00 per million output tokens; Qwen3.5-9B costs $0.10 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Nano Banana Pro (Gemini 3 Pro Image) or Qwen3.5-9B?
Qwen3.5-9B, with 262K tokens against 131K.
Has any benchmark tested both Nano Banana Pro (Gemini 3 Pro Image) and Qwen3.5-9B?
No benchmark has tested both yet. Nano Banana Pro (Gemini 3 Pro Image) has results on LMArena Image Edit; Qwen3.5-9B on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead. Data as of October 21, 2026.