Nano Banana Pro (Gemini 3 Pro Image) vs Saba
Saba costs 20.0x less per output token than Nano Banana Pro (Gemini 3 Pro Image) ($0.60 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
- $0.60
Nano Banana Pro (Gemini 3 Pro Image) or Saba: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nano Banana Pro (Gemini 3 Pro Image) for a larger context window (131K against 33K tokens).
No benchmark has tested both yet. Nano Banana Pro (Gemini 3 Pro Image) has results on LMArena Image Edit; Saba on AA Intelligence Index, GPQA Diamond (Artificial Analysis run) and Humanity's Last Exam (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 Saba has a AA Intelligence Index result, 6.5.
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 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Saba
Nano Banana Pro (Gemini 3 Pro Image) $0.0080, Saba $0.0005 per turn.
List prices
At a glance
- Coding index
- Nano Banana Pro (Gemini 3 Pro Image) not benchmarked, Saba 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 Saba $0.60 per million output tokens, 20.0x apart.
- Context window
- Nano Banana Pro (Gemini 3 Pro Image) takes 131K tokens, Saba 33K.
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.
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Saba | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 6.5 | Only Saba measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Saba | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 42.4% | Only Saba measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 4.3% | Only Saba measured |
| Neither model has a result on the other 20 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Saba | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 61.1% | Only Saba measured |
| Neither model has a result on the other 17 boards here | |||
Image generationDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Nano Banana Pro (Gemini 3 Pro Image) | Saba | 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
Saba costs less
Repository review
50K input + 3K output tokens
Saba costs less
Agent loop
200K input + 10K output tokens
Saba 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) | Mistral Saba |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 18, 2026 | February 17, 2025 |
| Context window | 131K | 33K |
| Input $/Mtok | $2.00 | $0.20 |
| Output $/Mtok | $12.00 | $0.60 |
| 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 Saba for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nano Banana Pro (Gemini 3 Pro Image) for a larger context window (131K against 33K tokens).
Which is cheaper, Nano Banana Pro (Gemini 3 Pro Image) or Saba?
Nano Banana Pro (Gemini 3 Pro Image) costs $2.00 per million input tokens and $12.00 per million output tokens; Saba costs $0.20 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Nano Banana Pro (Gemini 3 Pro Image) or Saba?
Nano Banana Pro (Gemini 3 Pro Image), with 131K tokens against 33K.
Has any benchmark tested both Nano Banana Pro (Gemini 3 Pro Image) and Saba?
No benchmark has tested both yet. Nano Banana Pro (Gemini 3 Pro Image) has results on LMArena Image Edit; Saba on AA Intelligence Index, GPQA Diamond (Artificial Analysis run) and Humanity's Last Exam (Artificial Analysis run). Compare them on price and context instead. Data as of October 21, 2026.