Nano Banana 2.1 vs GLM 4.6V
GLM 4.6V costs 8.3x less per output token than Nano Banana 2.1 ($0.90 vs $7.50 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
- No data
- Output $/M
- $0.90
Nano Banana 2.1 or GLM 4.6V: 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 2.1 has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; GLM 4.6V on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and LMArena Text: coding. 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 GLM 4.6V has a AA Intelligence Index result, 11.2.
Directional only
Image generation
Design Arena: images
No call
Only Nano Banana 2.1 has a Design Arena: images result, 1291.
Directional only
Long documents
Listed context window
GLM 4.6V
GLM 4.6V takes 131K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.6V
Nano Banana 2.1 $0.0053, GLM 4.6V $0.0008 per turn.
List prices
At a glance
- Coding index
- Nano Banana 2.1 not benchmarked, GLM 4.6V 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 GLM 4.6V $0.90 per million output tokens, 8.3x apart.
- Context window
- Nano Banana 2.1 takes 66K tokens, GLM 4.6V 131K.
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 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 41.1% | Only GLM 4.6V measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 14.4% | Only GLM 4.6V measured |
| LMArena Text: coding | Not measured | 1389 | Only GLM 4.6V measured |
| LMArena Text: software and IT | Not measured | 1391 | Only GLM 4.6V measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.2 | Only GLM 4.6V measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 31.6% | Only GLM 4.6V measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Nano Banana 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 71.9% | Only GLM 4.6V measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 9.6% | Only GLM 4.6V measured |
| LMArena Text: hard prompts | Not measured | 1367 | Only GLM 4.6V measured |
| LMArena Text: expert | Not measured | 1371 | Only GLM 4.6V measured |
| LMArena Text: hard prompts in English | Not measured | 1391 | Only GLM 4.6V measured |
| LMArena Vision: diagrams | Not measured | 1182 | Only GLM 4.6V measured |
| LMArena Vision: homework | Not measured | 1155 | Only GLM 4.6V measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nano Banana 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 85.3 | Only GLM 4.6V measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 85.3% | Only GLM 4.6V measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Nano Banana 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 79.9% | Only GLM 4.6V measured |
| LMArena Text: science | Not measured | 1389 | Only GLM 4.6V measured |
| LMArena Text: medicine and healthcare | Not measured | 1389 | Only GLM 4.6V measured |
| LMArena Text: legal and government | Not measured | 1393 | Only GLM 4.6V measured |
| LMArena Text: business and finance | Not measured | 1359 | Only GLM 4.6V measured |
| Neither model has a result on the other 15 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index18 boards measured
| Benchmark | Nano Banana 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| IFBench | Not measured | 30.1% | Only GLM 4.6V measured |
| Long context reasoning (AA-LCR) | Not measured | 48.7% | Only GLM 4.6V measured |
| LMArena Text | Not measured | 1376 | Only GLM 4.6V measured |
| LMArena Text: instruction following | Not measured | 1350 | Only GLM 4.6V measured |
| LMArena Text: creative writing | Not measured | 1347 | Only GLM 4.6V measured |
| LMArena Vision | Not measured | 1164 | Only GLM 4.6V measured |
| LMArena Text: English | Not measured | 1395 | Only GLM 4.6V measured |
| LMArena Text: non-English | Not measured | 1358 | Only GLM 4.6V measured |
| LMArena Text: Chinese | Not measured | 1425 | Only GLM 4.6V measured |
| LMArena Text: Russian | Not measured | 1339 | Only GLM 4.6V measured |
| LMArena Text: multi-turn | Not measured | 1359 | Only GLM 4.6V measured |
| LMArena Text: longer queries | Not measured | 1357 | Only GLM 4.6V measured |
| LMArena Text: writing and language | Not measured | 1347 | Only GLM 4.6V measured |
| LMArena Text: entertainment and media | Not measured | 1343 | Only GLM 4.6V measured |
| LMArena Vision: English | Not measured | 1179 | Only GLM 4.6V measured |
| LMArena Vision: Chinese | Not measured | 1217 | Only GLM 4.6V measured |
| LMArena Vision: reading text | Not measured | 1171 | Only GLM 4.6V measured |
| LMArena Vision: creative writing | Not measured | 1113 | Only GLM 4.6V measured |
| Neither model has a result on the other 30 boards here | |||
Image generationDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Nano Banana 2.1 | GLM 4.6V | Leader |
|---|---|---|---|
| Design Arena: images | 1291 | 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
GLM 4.6V costs less
Repository review
50K input + 3K output tokens
GLM 4.6V costs less
Agent loop
200K input + 10K output tokens
GLM 4.6V 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 | Z.ai GLM 4.6V |
|---|---|---|
| Maker | Z.ai | |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | December 8, 2025 |
| Context window | 66K | 131K |
| Input $/Mtok | $1.50 | $0.30 |
| Output $/Mtok | $7.50 | $0.90 |
| 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 2.1 better than GLM 4.6V 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 2.1 or GLM 4.6V?
Nano Banana 2.1 costs $1.50 per million input tokens and $7.50 per million output tokens; GLM 4.6V costs $0.30 and $0.90. Cost per solved task is known for neither of them.
Which has the bigger context window, Nano Banana 2.1 or GLM 4.6V?
GLM 4.6V, with 131K tokens against 66K.
Has any benchmark tested both Nano Banana 2.1 and GLM 4.6V?
No benchmark has tested both yet. Nano Banana 2.1 has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; GLM 4.6V on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and LMArena Text: coding. Compare them on price and context instead. Data as of October 22, 2026.