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docs: upgrade MiniMax model references from M2.5 to M2.7

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Update all documentation to reference the latest MiniMax-M2.7 and
MiniMax-M2.7-highspeed models, replacing the previous M2.5 series.
Also updates the CLI backend section with the current API endpoint
(api.minimax.io) and platform URL.

Co-Authored-By: Octopus <liyuan851277048@icloud.com>
This commit is contained in:
Octopus
2026-03-18 07:57:16 -05:00
committed by PR Bot
parent fc096759fb
commit 7ce6f4fd40
5 changed files with 17 additions and 17 deletions
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docs/en/stage-1/1.1-introduction-to-ai-ide/index.md
+1 -1
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@@ -624,7 +624,7 @@ You can do this:
|------|-----------------|
| Doubao-Seed Series | ✅ Supported |
| GLM-4.7 / 4.6 | ❌ Not Supported |
| MiniMax-M2.1 / M2 | ❌ Not Supported |
| MiniMax-M2.7 / M2.5 | ❌ Not Supported |
| DeepSeek-V3.1 | ❌ Not Supported |
| Kimi-K2.5 | ✅ Supported |
| Kimi-K2-0905 | ❌ Not Supported |
docs/en/stage-1/1.3-integrating-ai-capabilities/index.md
+7 -7
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@@ -169,16 +169,16 @@ In addition to DeepSeek, you can also try other large language models. Since mos
::: details Learn More: What is MiniMax?
**MiniMax** is a Chinese AI company dedicated to general artificial intelligence research. MiniMax has developed its own MiniMax-M2.5 series of large language models, which perform well in multiple benchmarks with excellent cost-effectiveness.
**MiniMax** is a Chinese AI company dedicated to general artificial intelligence research. MiniMax has developed its own MiniMax-M2.7 series of large language models, which perform well in multiple benchmarks with excellent cost-effectiveness.
**Key Features of MiniMax-M2.5 Series:**
**Key Features of MiniMax-M2.7 Series:**
- **Ultra-long context**: Supports a 204,800-token context window, suitable for processing long documents and multi-turn conversations
- **Cost-effective**: Input $0.3/M tokens, Output $1.2/M tokens, extremely competitive pricing
- **Cost-effective**: Extremely competitive pricing
- **OpenAI-compatible API**: Can be called directly using the OpenAI SDK, no need to learn a new API format
- **Two available models**:
- `MiniMax-M2.5`: Flagship model for complex tasks
- `MiniMax-M2.5-highspeed`: High-speed version with same performance but faster response
- `MiniMax-M2.7`: Flagship model for complex tasks
- `MiniMax-M2.7-highspeed`: High-speed version with same performance but faster response
:::
The integration process is the same as DeepSeek, just three steps:
@@ -194,7 +194,7 @@ curl https://api.minimax.io/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${MINIMAX_API_KEY}" \
-d '{
"model": "MiniMax-M2.5",
"model": "MiniMax-M2.7",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
@@ -207,7 +207,7 @@ curl https://api.minimax.io/v1/chat/completions \
MiniMax's API format is almost identical to DeepSeek (both are OpenAI-compatible), so if you've already successfully integrated DeepSeek, switching to MiniMax only requires changing three things:
1. **Base URL**: Change to `https://api.minimax.io/v1`
2. **API Key**: Use your MiniMax API Key
3. **Model name**: Change to `MiniMax-M2.5` or `MiniMax-M2.5-highspeed`
3. **Model name**: Change to `MiniMax-M2.7` or `MiniMax-M2.7-highspeed`
For more details, refer to the [MiniMax OpenAI Compatible API Documentation](https://platform.minimax.io/docs/api-reference/text-openai-api).
:::