LFM2.5-24B-A2B is $2.45 cheaper per 1M input tokens (98% lower; 50x difference).
API cost decision in 10 seconds
NewPareto 26.9 vs NewLFM2.5-24B-A2B
Pick LFM2.5-24B-A2B for lower cost; pick Pareto 26.9 only if the larger context window matters more.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick LFM2.5-24B-A2B for lower cost; pick Pareto 26.9 only if the larger context window matters more.
On the standard 1M input plus 500K output workload, LFM2.5-24B-A2B is estimated at $0.4 vs $6.25 for Pareto 26.9, saving $5.85 (93.6% lower).
Cost-first pickLFM2.5-24B-A2B
Context-first pickPareto 26.9
Sample savings$5.8593.6%
10x traffic gap$58.5
Pareto 26.9 has more context, but LFM2.5-24B-A2B saves $5.85 on the standard workload. At 10x that traffic, the same price gap is about $58.5. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
LFM2.5-24B-A2B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Pareto 26.9 | LFM2.5-24B-A2B |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | LFM2.5-24B-A2B | $16.25 | $0.6 |
| Balanced workload | 1M input + 1M output | LFM2.5-24B-A2B | $10 | $0.75 |
| Output-heavy chatbot | 1M input + 5M output | LFM2.5-24B-A2B | $40 | $3.55 |
LFM2.5-24B-A2B is $6.8 cheaper per 1M output tokens (90.7% lower; 10.7x difference).
Pareto 26.9 has 134.14K more context (2.05x larger).
LFM2.5-24B-A2B is $5.85 cheaper on the standard workload (93.6% 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
LFM2.5-24B-A2B has the lower input price; LFM2.5-24B-A2B has the lower output price; Pareto 26.9 offers the larger context window. For the 1M input plus 500K output sample, LFM2.5-24B-A2B is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $6.25 for Pareto 26.9 and $0.4 for LFM2.5-24B-A2B.
Choose Pareto 26.9 when you care most about larger context window.
Choose LFM2.5-24B-A2B when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, LFM2.5-24B-A2B is estimated at $0.4 vs $6.25 for Pareto 26.9, saving $5.85 (93.6% lower).
- LFM2.5-24B-A2B is $5.85 cheaper on the standard workload (93.6% lower).
- LFM2.5-24B-A2B is $2.45 cheaper per 1M input tokens (98% lower; 50x difference).
- LFM2.5-24B-A2B is $6.8 cheaper per 1M output tokens (90.7% lower; 10.7x difference).
- Pareto 26.9 has 134.14K more context (2.05x larger).
| Feature | NewPareto 26.9 (unbiased) | NewLFM2.5-24B-A2B (LiquidAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $2.5 | $0.05 |
| Completion Price per 1M tokens | $7.5 | $0.7 |
| Sample Workload Cost 1M input + 500K output | $6.25 | $0.4 |
| Context Window | 262.14K | 128K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | LFM2.5-24B-A2B | On the standard 1M input plus 500K output workload, LFM2.5-24B-A2B is estimated at $0.4 vs $6.25 for Pareto 26.9, saving $5.85 (93.6% lower). |
| High-volume input processing | LFM2.5-24B-A2B | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | LFM2.5-24B-A2B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Pareto 26.9 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Pareto 26.10 Preview can replace Pareto 26.9 when lower sample workload cost matters most: $2.4.
- LFM2.5-2.6B (free) can replace LFM2.5-24B-A2B when lower sample workload cost matters most: $0.
- LFM2.5-1.2B-Thinking (free) can replace LFM2.5-24B-A2B when lower sample workload cost matters most: $0.
- LFM2.5-1.2B-Instruct (free) can replace LFM2.5-24B-A2B 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 $0.47 sample workload cost.
- MiMo-V2.6-Flash offers 1.05M context with $0.28 sample workload cost.
- DeepSeek V4.1 Flash · DeepSeek · #1
- Step 5 Preview · StepFun · #2
- GLM 5.3 Flash · Z.ai · #3
- MiMo-V2.6-Flash · Xiaomi · #4
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Open LiquidAI modelsPareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.
LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid...