API cost decision in 10 seconds

Nano Banana Pro (Gemini 3 Pro Image) vs Laguna M.1 (free)

Pick Laguna M.1 (free) when budget and context both matter.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Laguna M.1 (free) when budget and context both matter.

On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $8 for Nano Banana Pro (Gemini 3 Pro Image), saving $8 (100% lower).

Cost-first pickLaguna M.1 (free)
Context-first pickLaguna M.1 (free)
Sample savings$8100%
10x traffic gap$80

Laguna M.1 (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $80. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Laguna M.1 (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickNano Banana Pro (Gemini 3 Pro Image)Laguna M.1 (free)
Input-heavy / RAG5M input + 500K outputLaguna M.1 (free)$16$0
Balanced workload1M input + 1M outputLaguna M.1 (free)$14$0
Output-heavy chatbot1M input + 5M outputLaguna M.1 (free)$62$0
Cheaper input Laguna M.1 (free) $2 vs $0 / 1M

Laguna M.1 (free) is free for input tokens while Nano Banana Pro (Gemini 3 Pro Image) costs $2 per 1M tokens.

Cheaper output Laguna M.1 (free) $12 vs $0 / 1M

Laguna M.1 (free) is free for output tokens while Nano Banana Pro (Gemini 3 Pro Image) costs $12 per 1M tokens.

Larger context Laguna M.1 (free) 131.07K vs 262.14K

Laguna M.1 (free) has 131.07K more context (2x larger).

Sample workload Laguna M.1 (free) $8 vs $0

Laguna M.1 (free) is free for the standard workload while the other model is estimated at $8.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Nano Banana Pro (Gemini 3 Pro Image) Calculating… Estimated API cost
Laguna M.1 (free) Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Laguna M.1 (free) has the lower input price; Laguna M.1 (free) has the lower output price; Laguna M.1 (free) offers the larger context window. For the 1M input plus 500K output sample, Laguna M.1 (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $8 for Nano Banana Pro (Gemini 3 Pro Image) and $0 for Laguna M.1 (free).

Best Fit

Choose Nano Banana Pro (Gemini 3 Pro Image) when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Laguna M.1 (free) when you care most about lower input-token price, lower output-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $8 for Nano Banana Pro (Gemini 3 Pro Image), saving $8 (100% lower).
  • Laguna M.1 (free) is free for the standard workload while the other model is estimated at $8.
  • Laguna M.1 (free) is free for input tokens while Nano Banana Pro (Gemini 3 Pro Image) costs $2 per 1M tokens.
  • Laguna M.1 (free) is free for output tokens while Nano Banana Pro (Gemini 3 Pro Image) costs $12 per 1M tokens.
  • Laguna M.1 (free) has 131.07K more context (2x larger).
Head-to-Head Specs
FeatureNano Banana Pro (Gemini 3 Pro Image)
(Google)
Laguna M.1 (free)
(Poolside)
Input Price
prompt tokens per 1M
$2$0
Completion Price
per 1M tokens
$12$0
Sample Workload Cost
1M input + 500K output
$8$0
Context Window131.07K262.14K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLaguna M.1 (free)On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $8 for Nano Banana Pro (Gemini 3 Pro Image), saving $8 (100% lower).
High-volume input processingLaguna M.1 (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLaguna M.1 (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workLaguna M.1 (free)A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • Gemma 4 26B A4B (free) can replace Nano Banana Pro (Gemini 3 Pro Image) when lower sample workload cost matters most: $0.
  • Gemma 4 31B (free) can replace Nano Banana Pro (Gemini 3 Pro Image) when lower sample workload cost matters most: $0.
  • Lyria 3 Pro Preview can replace Nano Banana Pro (Gemini 3 Pro Image) when lower sample workload cost matters most: $0.
  • Lyria 3 Clip Preview can replace Nano Banana Pro (Gemini 3 Pro Image) when lower sample workload cost matters most: $0.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

Google catalog

Review all tracked Google models before deciding whether this matchup is the right shortlist.

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Poolside catalog

Check other Poolside models with comparable pricing, context, or release timing.

Open Poolside models
Nano Banana Pro (Gemini 3 Pro Image)

Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...

Laguna M.1 (free)

Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai/), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 256K...