MiniMax M2-her with Jev
MiniMax M2-her is a model from MiniMax, released 2026-01-23. It costs $0.300 per million input tokens and $1.20 per million output tokens, reads up to 66K tokens of context, and writes up to 2,048 tokens in one reply. Through llm11, set model to minimax/minimax-m2-her.
- Input price
- $0.300 / 1M
- Output price
- $1.20 / 1M
- Context window
- 66K tokens
- Max output
- 2K tokens
- Cached input
- $0.030 / 1M
- Released
- 2026-01-23
- Accepts
- text
Read from the provider's prompt cache
Read from the live catalogue and refreshed daily. At blended list price, 58% of the 332 priced models we can call cost more.
Using MiniMax M2-her with Jev
Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. MiniMax M2-her does the answering when Jev sends it work, or when you name it yourself. At list price MiniMax M2-her falls in the llm11-balanced band, but no pack routes to it because it does not advertise structured output, which the verification checks rely on. You can still pin it: pass minimax/minimax-m2-her as model and routing steps aside while verification still runs.
Jev is new, so we have not published results for MiniMax M2-her with and without it, and this page does not invent any. Every response comes with a receipt that names the model that answered and what it cost against your most expensive model, so you can measure the pairing on your own traffic.
What a request costs
List price arithmetic, the same sum a receipt does. llm11 adds nothing per request; the only fee is on buying credits.
| Request | Tokens in / out | One | A thousand |
|---|---|---|---|
| Short chat turn | 500 / 200 | $0.00039 | $0.390 |
| Question over retrieved documents | 4,000 / 500 | $0.00180 | $1.80 |
| Long document summary | 30,000 / 1,000 | $0.010 | $10.20 |
Cheaper models to try
The catalogue has no benchmark score for MiniMax M2-her, so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| DeepSeek DeepSeek V3 0324 | $0.290 | $1.14 | 164K | |
| DeepSeek DeepSeek V3.1 Terminus | $0.300 | $1.00 | 164K | |
| Qwen Qwen3 Coder 480B A35B | $0.300 | $1.00 | 262K | |
| OpenAI GPT-5.4 Nano | $0.200 | $1.25 | 400K |
Call it
Same OpenAI request shape. Naming the model pins it, so nothing is routed, and the answer is still checked.
python
from openai import OpenAI
client = OpenAI(base_url="https://www.llm11.com/v1", api_key="llm11_live_...")
res = client.chat.completions.create(
model="minimax/minimax-m2-her",
messages=[{"role": "user", "content": "Hello"}],
)More from MiniMax
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| MiniMax M3 | $0.300 | $1.20 | 1.05M | |
| MiniMax M2.7 | $0.210 | $0.840 | 205K | |
| MiniMax M2.5 | $0.270 | $1.08 | 205K | |
| MiniMax M2.1Retires 2026-10-08 | $0.300 | $1.20 | 205K | |
| MiniMax M2 | $0.300 | $1.20 | 205K | |
| MiniMax M1 | $0.400 | $2.20 | 1M |
Questions
- What is MiniMax M2-her with Jev?
- Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. MiniMax M2-her does the answering when Jev sends it work, or when you name it yourself. At list price MiniMax M2-her falls in the llm11-balanced band, but no pack routes to it because it does not advertise structured output, which the verification checks rely on. You can still pin it: pass minimax/minimax-m2-her as model and routing steps aside while verification still runs. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is MiniMax M2-her a System One model?
- No. MiniMax M2-her answers requests. The System One model is Jev, which decides which model answers each one, so the two do different jobs and llm11 uses both.
- How much does MiniMax M2-her cost?
- $0.300 per million input tokens and $1.20 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00180, so a thousand of them is about $1.80. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the MiniMax M2-her context window?
- 65,536 tokens, with up to 2,048 tokens in a single reply.
- Does MiniMax M2-her support tool calling and structured output?
- The catalogue does not list tool calling, structured output and reasoning controls.
- Can I use MiniMax M2-her through llm11?
- Yes. Set model to minimax/minimax-m2-her on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to MiniMax M2-her?
- Routing decisions are made by Jev, TypeSafe AI's System One model. At list price MiniMax M2-her falls in the llm11-balanced band, but no pack routes to it because it does not advertise structured output, which the verification checks rely on. You can still pin it: pass minimax/minimax-m2-her as model and routing steps aside while verification still runs.
- What is a cheaper alternative to MiniMax M2-her?
- Nearest in price and below it: DeepSeek DeepSeek V3 0324 at $0.290 in and $1.14 out, DeepSeek DeepSeek V3.1 Terminus at $0.300 in and $1.00 out and Qwen Qwen3 Coder 480B A35B at $0.300 in and $1.00 out. The catalogue has no benchmark score for MiniMax M2-her, so this is a price ordering. It does not claim these answer as well.