LFM2.5-1.2B-Instruct (free) is free for input tokens while GLM 4.7 costs $0.4 per 1M tokens.
API cost decision in 10 seconds
LFM2.5-1.2B-Instruct (free) vs GLM 4.7
Pick LFM2.5-1.2B-Instruct (free) for lower cost; pick GLM 4.7 only if the larger context window matters more.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick LFM2.5-1.2B-Instruct (free) for lower cost; pick GLM 4.7 only if the larger context window matters more.
On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Instruct (free) is estimated at $0 vs $1.27 for GLM 4.7, saving $1.27 (100% lower).
Cost-first pickLFM2.5-1.2B-Instruct (free)
Context-first pickGLM 4.7
Sample savings$1.27100%
10x traffic gap$12.75
GLM 4.7 has more context, but LFM2.5-1.2B-Instruct (free) saves $1.27 on the standard workload. At 10x that traffic, the same price gap is about $12.75. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
LFM2.5-1.2B-Instruct (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | LFM2.5-1.2B-Instruct (free) | GLM 4.7 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | LFM2.5-1.2B-Instruct (free) | $0 | $2.88 |
| Balanced workload | 1M input + 1M output | LFM2.5-1.2B-Instruct (free) | $0 | $2.15 |
| Output-heavy chatbot | 1M input + 5M output | LFM2.5-1.2B-Instruct (free) | $0 | $9.15 |
LFM2.5-1.2B-Instruct (free) is free for output tokens while GLM 4.7 costs $1.75 per 1M tokens.
GLM 4.7 has 169.98K more context (6.19x larger).
LFM2.5-1.2B-Instruct (free) is free for the standard workload while the other model is estimated at $1.27.
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-Instruct (free) has the lower input price; LFM2.5-1.2B-Instruct (free) has the lower output price; GLM 4.7 offers the larger context window. For the 1M input plus 500K output sample, LFM2.5-1.2B-Instruct (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for LFM2.5-1.2B-Instruct (free) and $1.27 for GLM 4.7.
Choose LFM2.5-1.2B-Instruct (free) when you care most about lower input-token price, and lower output-token price.
Choose GLM 4.7 when you care most about larger context window.
- On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Instruct (free) is estimated at $0 vs $1.27 for GLM 4.7, saving $1.27 (100% lower).
- LFM2.5-1.2B-Instruct (free) is free for the standard workload while the other model is estimated at $1.27.
- LFM2.5-1.2B-Instruct (free) is free for input tokens while GLM 4.7 costs $0.4 per 1M tokens.
- LFM2.5-1.2B-Instruct (free) is free for output tokens while GLM 4.7 costs $1.75 per 1M tokens.
- GLM 4.7 has 169.98K more context (6.19x larger).
| Feature | LFM2.5-1.2B-Instruct (free) (LiquidAI) | GLM 4.7 (Z.ai) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $0.4 |
| Completion Price per 1M tokens | $0 | $1.75 |
| Sample Workload Cost 1M input + 500K output | $0 | $1.27 |
| Context Window | 32.77K | 202.75K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | LFM2.5-1.2B-Instruct (free) | On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Instruct (free) is estimated at $0 vs $1.27 for GLM 4.7, saving $1.27 (100% lower). |
| High-volume input processing | LFM2.5-1.2B-Instruct (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | LFM2.5-1.2B-Instruct (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GLM 4.7 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- GLM 4.5 Air (free) can replace GLM 4.7 when lower sample workload cost matters most: $0.
- GLM 4 32B can replace GLM 4.7 when lower sample workload cost matters most: $0.15.
- GLM 4.7 Flash can replace GLM 4.7 when lower sample workload cost matters most: $0.26.
- GLM 4.5 Air can replace GLM 4.7 when lower sample workload cost matters most: $0.55.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- Gemini 3.1 Flash Lite offers 1.05M context with $1 sample workload cost.
- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
- No popular competitor is currently available.
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 Z.ai modelsLFM2.5-1.2B-Instruct is a compact, high-performance instruction-tuned model built for fast on-device AI. It delivers strong chat quality in a 1.2B parameter footprint, with efficient edge inference and broad runtime support.
GLM-4.7 is Z.ai’s latest flagship model, featuring upgrades in two key areas: enhanced programming capabilities and more stable multi-step reasoning/execution. It demonstrates significant improvements in executing complex agent tasks while...