Schematron V2 Turbo is $0.02 cheaper per 1M input tokens (40% lower; 1.67x difference).
API cost decision in 10 seconds
NewLFM2.5-24B-A2B vs Schematron V2 Turbo
Pick Schematron V2 Turbo when budget is the priority.
Budget verdict
Pick Schematron V2 Turbo when budget is the priority.
On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $0.4 for LFM2.5-24B-A2B, saving $0.29 (73.8% lower).
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $2.95. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Schematron V2 Turbo stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | LFM2.5-24B-A2B | Schematron V2 Turbo |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Schematron V2 Turbo | $0.6 | $0.22 |
| Balanced workload | 1M input + 1M output | Schematron V2 Turbo | $0.75 | $0.18 |
| Output-heavy chatbot | 1M input + 5M output | Schematron V2 Turbo | $3.55 | $0.78 |
Schematron V2 Turbo is $0.55 cheaper per 1M output tokens (78.6% lower; 4.67x difference).
Both models report the same context window at 128K tokens.
Schematron V2 Turbo is $0.29 cheaper on the standard workload (73.8% 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
Schematron V2 Turbo has the lower input price; Schematron V2 Turbo has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Schematron V2 Turbo 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 $0.1 for Schematron V2 Turbo.
Choose LFM2.5-24B-A2B when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose Schematron V2 Turbo when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $0.4 for LFM2.5-24B-A2B, saving $0.29 (73.8% lower).
- Schematron V2 Turbo is $0.29 cheaper on the standard workload (73.8% lower).
- Schematron V2 Turbo is $0.02 cheaper per 1M input tokens (40% lower; 1.67x difference).
- Schematron V2 Turbo is $0.55 cheaper per 1M output tokens (78.6% lower; 4.67x difference).
- Both models report the same context window at 128K tokens.
| Feature | NewLFM2.5-24B-A2B (LiquidAI) | Schematron V2 Turbo (Inference.net) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.05 | $0.03 |
| Completion Price per 1M tokens | $0.7 | $0.15 |
| Sample Workload Cost 1M input + 500K output | $0.4 | $0.1 |
| Context Window | 128K | 128K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Schematron V2 Turbo | On the standard 1M input plus 500K output workload, Schematron V2 Turbo is estimated at $0.1 vs $0.4 for LFM2.5-24B-A2B, saving $0.29 (73.8% lower). |
| High-volume input processing | Schematron V2 Turbo | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Schematron V2 Turbo | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | 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 provider hubsLiquidAI catalog
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