LFM3-1.7B is $1.42 cheaper per 1M input tokens (94.7% lower; 18.8x difference).
API cost decision in 10 seconds
NewLFM3-1.7B vs Nano Banana 2.1
Pick LFM3-1.7B when budget and context both matter.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick LFM3-1.7B when budget and context both matter.
On the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $5.25 for Nano Banana 2.1, saving $5.07 (96.6% lower).
Cost-first pickLFM3-1.7B
Context-first pickLFM3-1.7B
Sample savings$5.0796.6%
10x traffic gap$50.7
LFM3-1.7B is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $50.7. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
LFM3-1.7B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | LFM3-1.7B | Nano Banana 2.1 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | LFM3-1.7B | $0.5 | $11.25 |
| Balanced workload | 1M input + 1M output | LFM3-1.7B | $0.28 | $9 |
| Output-heavy chatbot | 1M input + 5M output | LFM3-1.7B | $1.08 | $39 |
LFM3-1.7B is $7.3 cheaper per 1M output tokens (97.3% lower; 37.5x difference).
LFM3-1.7B has 196.61K more context (4x larger).
LFM3-1.7B is $5.07 cheaper on the standard workload (96.6% lower).
Estimate your workload cost
Your Workload Cost
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
LFM3-1.7B has the lower input price; LFM3-1.7B has the lower output price; LFM3-1.7B offers the larger context window. For the 1M input plus 500K output sample, LFM3-1.7B is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.18 for LFM3-1.7B and $5.25 for Nano Banana 2.1.
Choose LFM3-1.7B when you care most about lower input-token price, lower output-token price, and larger context window.
Choose Nano Banana 2.1 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
- On the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $5.25 for Nano Banana 2.1, saving $5.07 (96.6% lower).
- LFM3-1.7B is $5.07 cheaper on the standard workload (96.6% lower).
- LFM3-1.7B is $1.42 cheaper per 1M input tokens (94.7% lower; 18.8x difference).
- LFM3-1.7B is $7.3 cheaper per 1M output tokens (97.3% lower; 37.5x difference).
- LFM3-1.7B has 196.61K more context (4x larger).
| Feature | NewLFM3-1.7B (LiquidAI) | Nano Banana 2.1 (Google) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.08 | $1.5 |
| Completion Price per 1M tokens | $0.2 | $7.5 |
| Sample Workload Cost 1M input + 500K output | $0.18 | $5.25 |
| Context Window | 262.14K | 65.54K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | LFM3-1.7B | On the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $5.25 for Nano Banana 2.1, saving $5.07 (96.6% lower). |
| High-volume input processing | LFM3-1.7B | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | LFM3-1.7B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | LFM3-1.7B | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- LFM3-1.7B (free) can replace LFM3-1.7B when lower sample workload cost matters most: $0.
- LFM2.5-2.6B (free) can replace LFM3-1.7B when lower sample workload cost matters most: $0.
- LFM2.5-1.2B-Thinking (free) can replace LFM3-1.7B when lower sample workload cost matters most: $0.
- LFM2.5-1.2B-Instruct (free) can replace LFM3-1.7B when lower sample workload cost matters most: $0.
- Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- Llama 4 Scout offers 1.31M context with $0.25 sample workload cost.
- GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
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