LFM2-24B-A2B is $0.27 cheaper per 1M input tokens (90% lower; 10x difference).
API cost decision in 10 seconds
LFM2-24B-A2B vs MiniMax M2-her
Pick LFM2-24B-A2B when budget and context both matter.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick LFM2-24B-A2B when budget and context both matter.
On the standard 1M input plus 500K output workload, LFM2-24B-A2B is estimated at $0.09 vs $0.9 for MiniMax M2-her, saving $0.81 (90% lower).
Cost-first pickLFM2-24B-A2B
Context-first pickLFM2-24B-A2B
Sample savings$0.8190%
10x traffic gap$8.1
LFM2-24B-A2B is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $8.1. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
LFM2-24B-A2B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | LFM2-24B-A2B | MiniMax M2-her |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | LFM2-24B-A2B | $0.21 | $2.1 |
| Balanced workload | 1M input + 1M output | LFM2-24B-A2B | $0.15 | $1.5 |
| Output-heavy chatbot | 1M input + 5M output | LFM2-24B-A2B | $0.63 | $6.3 |
LFM2-24B-A2B is $1.08 cheaper per 1M output tokens (90% lower; 10x difference).
LFM2-24B-A2B has 62.46K more context (1.95x larger).
LFM2-24B-A2B is $0.81 cheaper on the standard workload (90% 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
LFM2-24B-A2B has the lower input price; LFM2-24B-A2B has the lower output price; LFM2-24B-A2B offers the larger context window. For the 1M input plus 500K output sample, LFM2-24B-A2B is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.09 for LFM2-24B-A2B and $0.9 for MiniMax M2-her.
Choose LFM2-24B-A2B when you care most about lower input-token price, lower output-token price, and larger context window.
Choose MiniMax M2-her when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
- On the standard 1M input plus 500K output workload, LFM2-24B-A2B is estimated at $0.09 vs $0.9 for MiniMax M2-her, saving $0.81 (90% lower).
- LFM2-24B-A2B is $0.81 cheaper on the standard workload (90% lower).
- LFM2-24B-A2B is $0.27 cheaper per 1M input tokens (90% lower; 10x difference).
- LFM2-24B-A2B is $1.08 cheaper per 1M output tokens (90% lower; 10x difference).
- LFM2-24B-A2B has 62.46K more context (1.95x larger).
| Feature | LFM2-24B-A2B (LiquidAI) | MiniMax M2-her (MiniMax) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.03 | $0.3 |
| Completion Price per 1M tokens | $0.12 | $1.2 |
| Sample Workload Cost 1M input + 500K output | $0.09 | $0.9 |
| Context Window | 128K | 65.54K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | LFM2-24B-A2B | On the standard 1M input plus 500K output workload, LFM2-24B-A2B is estimated at $0.09 vs $0.9 for MiniMax M2-her, saving $0.81 (90% lower). |
| High-volume input processing | LFM2-24B-A2B | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | LFM2-24B-A2B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | LFM2-24B-A2B | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- LFM2.5-1.2B-Thinking (free) can replace LFM2-24B-A2B when lower sample workload cost matters most: $0.
- LFM2.5-1.2B-Instruct (free) can replace LFM2-24B-A2B when lower sample workload cost matters most: $0.
- MiniMax M2.5 (free) can replace MiniMax M2-her when lower sample workload cost matters most: $0.
- MiniMax M2.5 can replace MiniMax M2-her when lower sample workload cost matters most: $0.72.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
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Open MiniMax modelsLFM2-24B-A2B is the largest model in the LFM2 family of hybrid architectures designed for efficient on-device deployment. Built as a 24B parameter Mixture-of-Experts model with only 2B active parameters per...
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message...