Nano Banana Pro (Gemini 3 Pro Image) vs GPT-4
Updated October 21, 2026. No benchmark has tested both models yet. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- No data
- Output $/M
- $12.00
- Coding
- No data
- Overall
- 6.7
- Output $/M
- $60.00
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Nano Banana Pro (Gemini 3 Pro Image) has the edge where output tokens cost 5.0x less, and where the context window is larger, 131K against 8K tokens.
No benchmark has tested both yet. Nano Banana Pro (Gemini 3 Pro Image) has results on LMArena Image Edit; GPT-4 on SWE-bench Verified, SWE-bench Lite and SWE-bench (full test set). 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 GPT-4 has a AA Intelligence Index result, 6.7.
Directional only
Long documents
Listed context window
Nano Banana Pro (Gemini 3 Pro Image)
Nano Banana Pro (Gemini 3 Pro Image) takes 131K tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nano Banana Pro (Gemini 3 Pro Image)
Nano Banana Pro (Gemini 3 Pro Image) $0.0080, GPT-4 $0.060 per turn.
List prices
At a glance
- Coding index
- Nano Banana Pro (Gemini 3 Pro Image) not benchmarked, GPT-4 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 GPT-4 $60.00 per million output tokens, 5.0x apart.
- Context window
- Nano Banana Pro (Gemini 3 Pro Image) takes 131K tokens, GPT-4 8K.
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 Index6 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | GPT-4 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 22.4% | Only GPT-4 measured |
| SWE-bench Lite | Not measured | 39.7% | Only GPT-4 measured |
| SWE-bench (full test set) | Not measured | 12.5% | Only GPT-4 measured |
| AA Coding Index | Not measured | 13.1 | Only GPT-4 measured |
| LMArena Text: coding | Not measured | 1209 | Only GPT-4 measured |
| LMArena Text: software and IT | Not measured | 1195 | Only GPT-4 measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | GPT-4 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 6.7 | Only GPT-4 measured |
| Epoch Capabilities Index | Not measured | 125.7 | Only GPT-4 measured |
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | GPT-4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 34.9% | Only GPT-4 measured |
| BIG-Bench Hard | Not measured | 75.1% | Only GPT-4 measured |
| LMArena Text: hard prompts | Not measured | 1200 | Only GPT-4 measured |
| LMArena Text: expert | Not measured | 1149 | Only GPT-4 measured |
| LMArena Text: hard prompts in English | Not measured | 1209 | Only GPT-4 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | GPT-4 | Leader |
|---|---|---|---|
| GSM8K | Not measured | 92.0% | Only GPT-4 measured |
| LMArena Text: math | Not measured | 1230 | Only GPT-4 measured |
| LMArena Text: mathematical work | Not measured | 1228 | Only GPT-4 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | GPT-4 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 56.2% | Only GPT-4 measured |
| MMLU | Not measured | 86.4% | Only GPT-4 measured |
| AI2 Reasoning Challenge | Not measured | 96.3% | Only GPT-4 measured |
| LMArena Text: science | Not measured | 1177 | Only GPT-4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1145 | Only GPT-4 measured |
| LMArena Text: legal and government | Not measured | 1191 | Only GPT-4 measured |
| LMArena Text: business and finance | Not measured | 1145 | Only GPT-4 measured |
| Neither model has a result on the other 10 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | GPT-4 | Leader |
|---|---|---|---|
| IFBench | Not measured | 33.2% | Only GPT-4 measured |
| DTBench | Not measured | 62.7% | Only GPT-4 measured |
| LMCA | Not measured | 17.1% | Only GPT-4 measured |
| HellaSwag | Not measured | 95.3% | Only GPT-4 measured |
| WinoGrande | Not measured | 87.5% | Only GPT-4 measured |
| LMArena Text | Not measured | 1206 | Only GPT-4 measured |
| LMArena Text: instruction following | Not measured | 1201 | Only GPT-4 measured |
| LMArena Text: creative writing | Not measured | 1191 | Only GPT-4 measured |
| LMArena Text: English | Not measured | 1220 | Only GPT-4 measured |
| LMArena Text: non-English | Not measured | 1194 | Only GPT-4 measured |
| LMArena Text: Chinese | Not measured | 1184 | Only GPT-4 measured |
| LMArena Text: German | Not measured | 1198 | Only GPT-4 measured |
| LMArena Text: Japanese | Not measured | 1137 | Only GPT-4 measured |
| LMArena Text: Korean | Not measured | 1087 | Only GPT-4 measured |
| LMArena Text: French | Not measured | 1220 | Only GPT-4 measured |
| LMArena Text: Spanish | Not measured | 1197 | Only GPT-4 measured |
| LMArena Text: Russian | Not measured | 1195 | Only GPT-4 measured |
| LMArena Text: Polish | Not measured | 1265 | Only GPT-4 measured |
| LMArena Text: multi-turn | Not measured | 1206 | Only GPT-4 measured |
| LMArena Text: longer queries | Not measured | 1190 | Only GPT-4 measured |
| LMArena Text: writing and language | Not measured | 1219 | Only GPT-4 measured |
| LMArena Text: entertainment and media | Not measured | 1184 | Only GPT-4 measured |
| Neither model has a result on the other 24 boards here | |||
Image generationDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | GPT-4 | 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
Nano Banana Pro (Gemini 3 Pro Image) costs less
Repository review
50K input + 3K output tokens
Nano Banana Pro (Gemini 3 Pro Image) costs less
Agent loop
200K input + 10K output tokens
Nano Banana Pro (Gemini 3 Pro Image) 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) | OpenAI GPT-4 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 18, 2026 | May 28, 2023 |
| Context window | 131K | 8K |
| Input $/Mtok | $2.00 | $30.00 |
| Output $/Mtok | $12.00 | $60.00 |
| 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 GPT-4 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Nano Banana Pro (Gemini 3 Pro Image) has the edge where output tokens cost 5.0x less, and where the context window is larger, 131K against 8K tokens.
Which is cheaper, Nano Banana Pro (Gemini 3 Pro Image) or GPT-4?
Nano Banana Pro (Gemini 3 Pro Image) costs $2.00 per million input tokens and $12.00 per million output tokens; GPT-4 costs $30.00 and $60.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Nano Banana Pro (Gemini 3 Pro Image) or GPT-4?
Nano Banana Pro (Gemini 3 Pro Image), with 131K tokens against 8K.
Has any benchmark tested both Nano Banana Pro (Gemini 3 Pro Image) and GPT-4?
No benchmark has tested both yet. Nano Banana Pro (Gemini 3 Pro Image) has results on LMArena Image Edit; GPT-4 on SWE-bench Verified, SWE-bench Lite and SWE-bench (full test set). Compare them on price and context instead. Data as of October 21, 2026.