Ling 3.0 Flash Fin (free) is free for input tokens while LFM2.5-24B-A2B costs $0.05 per 1M tokens.
API cost decision in 10 seconds
NewLFM2.5-24B-A2B vs Ling 3.0 Flash Fin (free)
Pick Ling 3.0 Flash Fin (free) 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 Ling 3.0 Flash Fin (free) when budget and context both matter.
On the standard 1M input plus 500K output workload, Ling 3.0 Flash Fin (free) is estimated at $0 vs $0.4 for LFM2.5-24B-A2B, saving $0.4 (100% lower).
Cost-first pickLing 3.0 Flash Fin (free)
Context-first pickLing 3.0 Flash Fin (free)
Sample savings$0.4100%
10x traffic gap$4
Ling 3.0 Flash Fin (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $4. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Ling 3.0 Flash Fin (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | LFM2.5-24B-A2B | Ling 3.0 Flash Fin (free) |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Ling 3.0 Flash Fin (free) | $0.6 | $0 |
| Balanced workload | 1M input + 1M output | Ling 3.0 Flash Fin (free) | $0.75 | $0 |
| Output-heavy chatbot | 1M input + 5M output | Ling 3.0 Flash Fin (free) | $3.55 | $0 |
Ling 3.0 Flash Fin (free) is free for output tokens while LFM2.5-24B-A2B costs $0.7 per 1M tokens.
Ling 3.0 Flash Fin (free) has 134.14K more context (2.05x larger).
Ling 3.0 Flash Fin (free) is free for the standard workload while the other model is estimated at $0.4.
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
Ling 3.0 Flash Fin (free) has the lower input price; Ling 3.0 Flash Fin (free) has the lower output price; Ling 3.0 Flash Fin (free) offers the larger context window. For the 1M input plus 500K output sample, Ling 3.0 Flash Fin (free) 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 for Ling 3.0 Flash Fin (free).
Choose LFM2.5-24B-A2B when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose Ling 3.0 Flash Fin (free) when you care most about lower input-token price, lower output-token price, and larger context window.
- On the standard 1M input plus 500K output workload, Ling 3.0 Flash Fin (free) is estimated at $0 vs $0.4 for LFM2.5-24B-A2B, saving $0.4 (100% lower).
- Ling 3.0 Flash Fin (free) is free for the standard workload while the other model is estimated at $0.4.
- Ling 3.0 Flash Fin (free) is free for input tokens while LFM2.5-24B-A2B costs $0.05 per 1M tokens.
- Ling 3.0 Flash Fin (free) is free for output tokens while LFM2.5-24B-A2B costs $0.7 per 1M tokens.
- Ling 3.0 Flash Fin (free) has 134.14K more context (2.05x larger).
| Feature | NewLFM2.5-24B-A2B (LiquidAI) | Ling 3.0 Flash Fin (free) (inclusionAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.05 | $0 |
| Completion Price per 1M tokens | $0.7 | $0 |
| Sample Workload Cost 1M input + 500K output | $0.4 | $0 |
| Context Window | 128K | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Ling 3.0 Flash Fin (free) | On the standard 1M input plus 500K output workload, Ling 3.0 Flash Fin (free) is estimated at $0 vs $0.4 for LFM2.5-24B-A2B, saving $0.4 (100% lower). |
| High-volume input processing | Ling 3.0 Flash Fin (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Ling 3.0 Flash Fin (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Ling 3.0 Flash Fin (free) | 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
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Open inclusionAI 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...
Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment...