MiniMax M2-her API66K context
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations.
Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).
What is MiniMax M2-her?
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...
MiniMax M2-her on the release timeline
MiniMax M2-her pricing
Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):
| Model | Input / 1M | Output / 1M | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| MiniMax M2-her | $0.30 | $1.20 | $0.03 | — | 66K |
On output price, MiniMax M2-her is cheaper than 56% of the 309 models in the catalog.
What MiniMax M2-her costs per month
| Workload | Tokens in / out (monthly) | Est. cost |
|---|---|---|
| Support chatbot | 40M / 12M | $26.40 |
| RAG / knowledge base | 200M / 20M | $84.00 |
| Coding agent | 80M / 25M | $54.00 |
| Batch extraction | 150M / 8M | $54.60 |
| Content generation | 20M / 40M | $54.00 |
Estimate your own monthly cost
Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.
MiniMax M2-her vs alternatives
| Model | Input / 1M | Output / 1M | Context | Our test |
|---|---|---|---|---|
| MiniMax M2-her | $0.30 | $1.20 | 66K | — |
| MiniMax M2.1 | $0.30 | $1.20 | 205K | — |
| MiniMax M3 | $0.30 | $1.20 | 1M | 8/9 |
| MiniMax-01 | $0.20 | $1.10 | 1M | — |
| Virtuoso Large | $0.75 | $1.20 | 131K | — |
| KAT-Coder-Pro V2 | $0.30 | $1.20 | 256K | — |
When not to use MiniMax M2-her
- It is served by a single provider, so there is less failover headroom during an outage.
Specs
| Model ID | minimax/minimax-m2-her |
| Modality | text->text (input: text) |
| Context window | 65,536 tokens |
| Max output | 2,048 tokens |
| Tool / function calling | — |
| Structured output (JSON) | — |
| Released | 2026-01-23 |
| Open weights | — (hosted API only) |
How to call MiniMax M2-her
from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
model="minimax/minimax-m2-her",
messages=[{"role": "user", "content": "Hello"}],
)
print(resp.choices[0].message.content)curl https://api.datallmlab.com/v1/chat/completions \
-H "Authorization: Bearer YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"minimax/minimax-m2-her","messages":[{"role":"user","content":"Hello"}]}'import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
model: "minimax/minimax-m2-her",
messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);The same key routes MiniMax M2-her and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.
Prompting tips for MiniMax M2-her
- Be explicit and show the shape of the answer. Spell out format, tone and constraints up front, and include one short example of the output you want — MiniMax M2-her follows concrete instructions better than abstract ones.
Tips are derived from MiniMax M2-her's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.
Open-source tools for MiniMax M2-her
Popular open-source frameworks and agents to build with MiniMax M2-her over the API — star counts pulled from GitHub (July 2026).
Listed by GitHub stars; inclusion is by ecosystem relevance (agent frameworks, SDKs and gateways), not affiliation. Stars change — see each repo for current numbers.
Migrating to MiniMax M2-her
Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → minimax/minimax-m2-her. Messages, streaming and the rest of your code stay the same. Routing & failover guide.
Rate limits & reliability
Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.
Related reading
Call MiniMax M2-her with one key
300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.
Get an API keyCompare pricingFrequently asked questions
What is MiniMax M2-her?
MiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. It accepts text input with a 66K-token context window and was released on 2026-01-23. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.
How much does MiniMax M2-her cost?
On DataLLM Lab it is $0.30 per 1M input tokens and $1.20 per 1M output tokens, with cached input at $0.03/1M — cheaper than about 56% of the 309-model catalog on output price. Pay-as-you-go, no subscription.
What is the context window of MiniMax M2-her?
66K tokens, with up to 2K max output tokens.
Is MiniMax M2-her open source?
No open weights are published — it is available through hosted API access only.
How do I call the MiniMax M2-her API?
Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "minimax/minimax-m2-her". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.
What are good alternatives to MiniMax M2-her?
Close options by price and capability include MiniMax M2.1, MiniMax M3, MiniMax-01 — all callable with the same DataLLM Lab key.