LFM2.5-24B-A2B is $0.04 cheaper per 1M input tokens (44.4% lower; 1.8x difference).
API cost decision in 10 seconds
NewLFM2.5-24B-A2B vs Solar Pro 4
Pick Solar Pro 4 when budget and context both matter.
Budget verdict
Pick Solar Pro 4 when budget and context both matter.
On the standard 1M input plus 500K output workload, Solar Pro 4 is estimated at $0.27 vs $0.4 for LFM2.5-24B-A2B, saving $0.13 (32.5% lower).
Solar Pro 4 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $1.3. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Cost winner changes by workload shape: input-heavy / RAG favors LFM2.5-24B-A2B, balanced workload favors Solar Pro 4, and output-heavy chatbot favors Solar Pro 4.
| Workload shape | Token mix | Better pick | LFM2.5-24B-A2B | Solar Pro 4 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | LFM2.5-24B-A2B | $0.6 | $0.63 |
| Balanced workload | 1M input + 1M output | Solar Pro 4 | $0.75 | $0.45 |
| Output-heavy chatbot | 1M input + 5M output | Solar Pro 4 | $3.55 | $1.89 |
Solar Pro 4 is $0.34 cheaper per 1M output tokens (48.6% lower; 1.94x difference).
Solar Pro 4 has 396.29K more context (4.1x larger).
Solar Pro 4 is $0.13 cheaper on the standard workload (32.5% 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; Solar Pro 4 has the lower output price; Solar Pro 4 offers the larger context window. For the 1M input plus 500K output sample, Solar Pro 4 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.4 for LFM2.5-24B-A2B and $0.27 for Solar Pro 4.
Choose LFM2.5-24B-A2B when you care most about lower input-token price.
Choose Solar Pro 4 when you care most about lower output-token price, and larger context window.
- On the standard 1M input plus 500K output workload, Solar Pro 4 is estimated at $0.27 vs $0.4 for LFM2.5-24B-A2B, saving $0.13 (32.5% lower).
- Solar Pro 4 is $0.13 cheaper on the standard workload (32.5% lower).
- LFM2.5-24B-A2B is $0.04 cheaper per 1M input tokens (44.4% lower; 1.8x difference).
- Solar Pro 4 is $0.34 cheaper per 1M output tokens (48.6% lower; 1.94x difference).
- Solar Pro 4 has 396.29K more context (4.1x larger).
| Feature | NewLFM2.5-24B-A2B (LiquidAI) | Solar Pro 4 (Upstage) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.05 | $0.09 |
| Completion Price per 1M tokens | $0.7 | $0.36 |
| Sample Workload Cost 1M input + 500K output | $0.4 | $0.27 |
| Context Window | 128K | 524.29K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Solar Pro 4 | On the standard 1M input plus 500K output workload, Solar Pro 4 is estimated at $0.27 vs $0.4 for LFM2.5-24B-A2B, saving $0.13 (32.5% 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 | Solar Pro 4 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Solar Pro 4 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- 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.
- LFM2-24B-A2B can replace LFM2.5-24B-A2B when lower sample workload cost matters most: $0.09.
- 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.
- GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
- GPT-6 Luna Pro offers 1.05M context with $0.35 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
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
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Open Upstage modelsLFM2.5-24B-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...
Solar Pro 4 is Upstage's cost-efficient large language model, featuring a 524K context window. It is built for long-horizon tasks and agentic workflows, with strong capabilities in office productivity, document-intensive...