API cost decision in 10 seconds
LFM2.5-1.2B-Thinking (free) vs Granite 4.0 Micro
Pick LFM2.5-1.2B-Thinking (free) for lower cost; pick Granite 4.0 Micro only if the larger context window matters more.
Budget verdict
Pick LFM2.5-1.2B-Thinking (free) for lower cost; pick Granite 4.0 Micro only if the larger context window matters more.
On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Thinking (free) is estimated at $0 vs $0.07 for Granite 4.0 Micro, saving $0.07 (100% lower).
Granite 4.0 Micro has more context, but LFM2.5-1.2B-Thinking (free) saves $0.07 on the standard workload. At 10x that traffic, the same price gap is about $0.73. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
LFM2.5-1.2B-Thinking (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | LFM2.5-1.2B-Thinking (free) | Granite 4.0 Micro |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | LFM2.5-1.2B-Thinking (free) | $0 | $0.14 |
| Balanced workload | 1M input + 1M output | LFM2.5-1.2B-Thinking (free) | $0 | $0.13 |
| Output-heavy chatbot | 1M input + 5M output | LFM2.5-1.2B-Thinking (free) | $0 | $0.58 |
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
LFM2.5-1.2B-Thinking (free) has the lower input price, LFM2.5-1.2B-Thinking (free) has the lower output price, and Granite 4.0 Micro offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for LFM2.5-1.2B-Thinking (free) and $0.07 for Granite 4.0 Micro.
Choose LFM2.5-1.2B-Thinking (free) when you care most about lower input-token price, and lower output-token price.
Choose Granite 4.0 Micro when you care most about larger context window.
| Feature | LFM2.5-1.2B-Thinking (free) (LiquidAI) | Granite 4.0 Micro (IBM) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $0.02 |
| Completion Price per 1M tokens | $0 | $0.11 |
| Sample Workload Cost 1M input + 500K output | $0 | $0.07 |
| Context Window | 32.77K | 131K |
| Release Date | 2026-01-20 | 2025-10-20 |
LFM2.5-1.2B-Thinking is a lightweight reasoning-focused model optimized for agentic tasks, data extraction, and RAG—while still running comfortably on edge devices. It supports long context (up to 32K tokens) and is...
Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models released by IBM. They are fine-tuned for long...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | LFM2.5-1.2B-Thinking (free) | On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Thinking (free) is estimated at $0 vs $0.07 for Granite 4.0 Micro, saving $0.07 (100% lower). |
| High-volume input processing | LFM2.5-1.2B-Thinking (free) | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | LFM2.5-1.2B-Thinking (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Granite 4.0 Micro | A larger context window leaves more room for retrieved passages and source files. |