Nano Banana 2.1 vs o3
Nano Banana 2.1 and o3 cost about the same per output token ($7.50 vs $8.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $7.50
- Coding
- No data
- Overall
- 51.1
- Output $/M
- $8.00
Nano Banana 2.1 or o3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nano Banana 2.1 for output tokens 1.1x cheaper ($7.50 vs $8.00 per million).
No benchmark has tested both yet. Nano Banana 2.1 has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; o3 on Aider polyglot, SWE-bench Verified and SWE-bench Multimodal. 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 o3 has a AA Intelligence Index result, 20.2.
Directional only
Reasoning
GPQA Diamond
No call
Only o3 has a GPQA Diamond result, 84.1%.
Directional only
Math
AIME
No call
Only o3 has a AIME result, 85.3%.
Directional only
Knowledge
MMLU Pro
No call
Only o3 has a MMLU Pro result, 85.6%.
Directional only
Web design
Design Arena: websites
No call
Only o3 has a Design Arena: websites result, 1036.
Directional only
Image generation
Design Arena: images
No call
Only Nano Banana 2.1 has a Design Arena: images result, 1293.
Directional only
Long documents
Listed context window
o3
o3 takes 200K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nano Banana 2.1
Nano Banana 2.1 $0.0053, o3 $0.0060 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only o3 has the number, $0.571.
Directional only
At a glance
- Coding index
- Nano Banana 2.1 not benchmarked, o3 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 2.1 $7.50 against o3 $8.00 per million output tokens, 1.1x apart.
- Context window
- Nano Banana 2.1 takes 66K tokens, o3 200K.
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 Index12 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 81.3% | Only o3 measured |
| SWE-bench Verified | Not measured | 58.4% | Only o3 measured |
| SWE-bench Multimodal | Not measured | 36.0% | Only o3 measured |
| LiveCodeBench (Vals AI) | Not measured | 83.9% | Only o3 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 80.8% | Only o3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 37.1% | Only o3 measured |
| GSO-Bench | Not measured | 8.8% | Only o3 measured |
| WeirdML | Not measured | 52.4% | Only o3 measured |
| ALE-Bench | Not measured | 933.5 | Only o3 measured |
| LMArena Text: coding | Not measured | 1407 | Only o3 measured |
| LMArena Text: software and IT | Not measured | 1415 | Only o3 measured |
| SciCode | Not measured | 9.2% | Only o3 measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 20.2 | Only o3 measured |
| Epoch Capabilities Index | Not measured | 146.7 | Only o3 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 80.7% | Only o3 measured |
| METR time horizons | Not measured | 65.4% | Only o3 measured |
| GDPval | Not measured | 30.8% | Only o3 measured |
| DeepResearch Bench | Not measured | 45.2% | Only o3 measured |
| OSWorld | Not measured | 23.0% | Only o3 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 63.0% | Only o3 measured |
| BrowseComp-Plus | Not measured | 65.9% | Only o3 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index17 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.1% | Only o3 measured |
| MMMU Pro (Vals AI) | Not measured | 80.4% | Only o3 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 82.7% | Only o3 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 20.1% | Only o3 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 81.8% | Only o3 measured |
| ARC-AGI | Not measured | 60.8% | Only o3 measured |
| ARC-AGI-2 | Not measured | 6.5% | Only o3 measured |
| SimpleBench | Not measured | 53.1% | Only o3 measured |
| Chess puzzles | Not measured | 37.0% | Only o3 measured |
| Mystery game puzzles | Not measured | 29.0% | Only o3 measured |
| VPCT | Not measured | 52.0% | Only o3 measured |
| LMArena Text: hard prompts | Not measured | 1402 | Only o3 measured |
| LMArena Text: expert | Not measured | 1402 | Only o3 measured |
| LMArena Text: hard prompts in English | Not measured | 1411 | Only o3 measured |
| LMArena Vision: diagrams | Not measured | 1220 | Only o3 measured |
| LMArena Vision: homework | Not measured | 1234 | Only o3 measured |
| Kagi LLM Benchmark | Not measured | 67.6% | Only o3 measured |
| Neither model has a result on the other 5 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| AIME | Not measured | 85.3% | Only o3 measured |
| MATH 500 (Vals AI) | Not measured | 94.6% | Only o3 measured |
| MGSM (Vals AI) | Not measured | 91.8% | Only o3 measured |
| AA Math Index | Not measured | 88.3 | Only o3 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 88.3% | Only o3 measured |
| OTIS Mock AIME | Not measured | 84.4% | Only o3 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 33.3% | Only o3 measured |
| MATH level 5 | Not measured | 97.8% | Only o3 measured |
| LMArena Text: math | Not measured | 1426 | Only o3 measured |
| LMArena Text: mathematical work | Not measured | 1423 | Only o3 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index15 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 85.6% | Only o3 measured |
| LegalBench (Vals AI) | Not measured | 83.8% | Only o3 measured |
| CorpFin (Vals AI) | Not measured | 59.7% | Only o3 measured |
| TaxEval (Vals AI) | Not measured | 74.6% | Only o3 measured |
| MortgageTax (Vals AI) | Not measured | 65.7% | Only o3 measured |
| MedQA (Vals AI) | Not measured | 96.1% | Only o3 measured |
| MedCode (Vals AI) | Not measured | 47.3% | Only o3 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 85.3% | Only o3 measured |
| SimpleQA Verified | Not measured | 49.4% | Only o3 measured |
| GeoBench | Not measured | 74.0% | Only o3 measured |
| LMArena Text: science | Not measured | 1429 | Only o3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1448 | Only o3 measured |
| LMArena Text: legal and government | Not measured | 1428 | Only o3 measured |
| LMArena Text: business and finance | Not measured | 1393 | Only o3 measured |
| FACTS Benchmark Suite | Not measured | 44.4% | Only o3 measured |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1036 | Only o3 measured |
| Design Arena: UI components | Not measured | 1017 | Only o3 measured |
| Design Arena: game dev | Not measured | 1034 | Only o3 measured |
| Design Arena: data viz | Not measured | 1200 | Only o3 measured |
| Design Arena: all code categories | Not measured | 1020 | Only o3 measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index34 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 41.8% | Only o3 measured |
| MedScribe (Vals AI) | Not measured | 76.7% | Only o3 measured |
| IFBench | Not measured | 71.4% | Only o3 measured |
| Long context reasoning (AA-LCR) | Not measured | 74.7% | Only o3 measured |
| DTBench | Not measured | 84.8% | Only o3 measured |
| LMCA | Not measured | 39.7% | Only o3 measured |
| Fiction.LiveBench | Not measured | 88.9% | Only o3 measured |
| Creative writing (Lech Mazur) | Not measured | 83.9% | Only o3 measured |
| CL-bench | Not measured | 17.8% | Only o3 measured |
| LMArena Text | Not measured | 1410 | Only o3 measured |
| LMArena Text: instruction following | Not measured | 1368 | Only o3 measured |
| LMArena Text: creative writing | Not measured | 1359 | Only o3 measured |
| LMArena Vision | Not measured | 1214 | Only o3 measured |
| LMArena Text: English | Not measured | 1417 | Only o3 measured |
| LMArena Text: non-English | Not measured | 1401 | Only o3 measured |
| LMArena Text: Chinese | Not measured | 1437 | Only o3 measured |
| LMArena Text: German | Not measured | 1420 | Only o3 measured |
| LMArena Text: Japanese | Not measured | 1403 | Only o3 measured |
| LMArena Text: Korean | Not measured | 1370 | Only o3 measured |
| LMArena Text: French | Not measured | 1430 | Only o3 measured |
| LMArena Text: Spanish | Not measured | 1395 | Only o3 measured |
| LMArena Text: Russian | Not measured | 1406 | Only o3 measured |
| LMArena Text: Polish | Not measured | 1438 | Only o3 measured |
| LMArena Text: multi-turn | Not measured | 1405 | Only o3 measured |
| LMArena Text: longer queries | Not measured | 1372 | Only o3 measured |
| LMArena Text: writing and language | Not measured | 1372 | Only o3 measured |
| LMArena Text: entertainment and media | Not measured | 1373 | Only o3 measured |
| LMArena Vision: English | Not measured | 1221 | Only o3 measured |
| LMArena Vision: Chinese | Not measured | 1237 | Only o3 measured |
| LMArena Vision: reading text | Not measured | 1218 | Only o3 measured |
| LMArena Vision: humor | Not measured | 1222 | Only o3 measured |
| LMArena Vision: captioning | Not measured | 1210 | Only o3 measured |
| LMArena Vision: recognizing things | Not measured | 1234 | Only o3 measured |
| LMArena Vision: creative writing | Not measured | 1201 | Only o3 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Nano Banana 2.1 | o3 | Leader |
|---|---|---|---|
| Design Arena: images | 1293 | Not measured | Only Nano Banana 2.1 measured |
| Design Arena: graphic design | 1333 | Not measured | Only Nano Banana 2.1 measured |
| Design Arena: logos | 1277 | Not measured | Only Nano Banana 2.1 measured |
| LMArena Text to Image | 1328 | Not measured | Only Nano Banana 2.1 measured |
| LMArena Image Edit | 1426 | Not measured | Only Nano Banana 2.1 measured |
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 2.1 costs less
Repository review
50K input + 3K output tokens
Nano Banana 2.1 costs less
Agent loop
200K input + 10K output tokens
Nano Banana 2.1 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 2.1 | OpenAI o3 |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | No public weights listed |
| Released | October 6, 2026 | April 16, 2025 |
| Context window | 66K | 200K |
| Input $/Mtok | $1.50 | $2.00 |
| Output $/Mtok | $7.50 | $8.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | $0.571 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nano Banana 2.1 better than o3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nano Banana 2.1 for output tokens 1.1x cheaper ($7.50 vs $8.00 per million).
Which is cheaper, Nano Banana 2.1 or o3?
Nano Banana 2.1 costs $1.50 per million input tokens and $7.50 per million output tokens; o3 costs $2.00 and $8.00. Cost per solved task is known for o3 only.
Which has the bigger context window, Nano Banana 2.1 or o3?
o3, with 200K tokens against 66K.
Has any benchmark tested both Nano Banana 2.1 and o3?
No benchmark has tested both yet. Nano Banana 2.1 has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; o3 on Aider polyglot, SWE-bench Verified and SWE-bench Multimodal. Compare them on price and context instead. Data as of October 22, 2026.