Should Small Teams Replace Sonnet 4.5 With MiniMax-M2 in Claude Code？
By
Novita AI
/ November 14, 2025 / LLM / 7 minutes of reading
Many developers are comparing MiniMax-M2 and Claude Sonnet 4.5, unsure whether M2’s claim of “8 % of the price and 2× the speed” really holds in coding and agentic workflows. The core confusion lies in balancing speed, cost, and reasoning power.
This article examines both models across benchmarks, architectural design, and real-world tasks—helping users decide which is more suitable for their coding, automation, or small-team workflows.
Can MiniMax-M2 Really Deliver “8% of the Price, 2× the Speed” Compared to Claude?
The answer is Yes！According to MiniMax’s official blog, the company highlights this improvement directly.
We have set the API price for the model at $0.30/¥2.1 RMB per million input tokens and $1.20/¥8.4 RMB per million output tokens, while providing an online inference service with a TPS (tokens per second) of around 100 (and rapidly improving). This price is 8% of Claude 3.5 Sonnet’s, with nearly double the inference speed.
However, our focus will be on the performance aspects they gave less attention to.
Benchmark
MiniMax-M2
Claude Sonnet 4.5
SWE-bench Verified
69.4
77.2
Multi-SWE-Bench
36.2
44.3
Terminal-Bench
46.3
50.0
ArtifactsBench
66.8
61.5
T²-Bench
77.2
84.7
GAIA (text only)
75.7
71.2
BrowseComp
44.0
19.6
FinSearchComp-global
65.5
60.8
Across coding-oriented benchmarks, Claude Sonnet 4.5 consistently outperforms MiniMax-M2 by ~10–20% on SWE and logic-heavy tasks, reflecting stronger long-context coherence and agent planning. Its architecture favors reasoning depth and tool integration over raw inference speed.
MiniMax-M2 shows surprising efficiency in retrieval and web-agent tasks, outperforming Claude on BrowseComp and FinSearchComp despite smaller parameter activation.
Activated parameters (per inference/token): around 10 billion.
Context window: reported up to ~200 000 tokens
Why Activation Size Matters
Because only about 10 billion parameters are active at a time, M2 runs faster and costs less to use. This smaller workload means each request needs less memory, so more tasks can run at once on the same hardware. In long or multi-file coding projects, that design keeps responses quick and stable, making the model smoother for interactive use.
When Is M2 the Right Choice—and When Should You Stick with Claude?
Projects requiring tool use, multi-step reasoning, and stateful agent planning
Complex bug fixing, code refactoring, and cross-module integration
MiniMax-M2 is better suited for:
Retrieval-augmented and web-connected coding agents
Lightweight automation and script generation
Financial data querying and information-driven coding workflows
Fast, low-cost iterative coding within simple or templated structures
#There is a test!
You are an advanced coding assistant. Evaluate and optimize the following function for speed, reliability, and scalability:
---
import requests
def fetch_prices(symbols):
data = {}
for s in symbols:
resp = requests.get(f"https://api.example.com/{s}")
data[s] = resp.json()["price"]
return data
---
Instructions:
1. Identify all performance and reliability issues in the original implementation.
2. Rewrite the function to support **concurrent execution**, **error handling**, **timeout and retry logic**, and **graceful degradation**.
3. Measure or estimate performance gain (e.g., x times faster for N symbols) and summarize key improvements.
4. Return only:
- The optimized code
- A short benchmark summary comparing sequential vs concurrent performance
- Example output for ['AAPL', 'GOOG', 'MSFT']
More systematic, includes rate-limiting, connection pooling, and structured output
Stability
Basic error handling, continues on failures
Fine-grained exception capture, retries, and rate-limit protection
Performance Estimate
2–4× speed-up
Up to 8× speed-up (ideal conditions)
Runtime Cost
Lower cost, faster response
Heavier computation, longer inference time
Best-Fit Tasks
Quick prototypes and small-scale scripts
Large-scale, high-reliability concurrent services
Conclusion Both models completed the same task but from different angles:
M2 focuses on speed and resource efficiency, producing a directly runnable concurrent version.
Claude 4.5 aims for completeness and engineering rigor, delivering a truly asynchronous, production-ready design.
How Can M2 Be Integrated into Claude Code?
Novita AI provides APIs with 200K context, and costs of $0.3/input and $1.2/output, supporting structured output and function calling, which delivers strong support for maximizing Minimax M2″s code agent potential.
The First: Get API Key
Step 1: Log in to your account and click on the Model Library button.
Browse through the available options and select the model that suits your needs.
Step 3: Start Your Free Trial
Begin your free trial to explore the capabilities of the selected model.
Step 4: Get Your API Key
To authenticate with the API, we will provide you with a new API key. Entering the “Settings“ page, you can copy the API key as indicated in the image.
Step 5: Install the API
Install API using the package manager specific to your programming language.
After installation, import the necessary libraries into your development environment. Initialize the API with your API key to start interacting with Novita AI LLM. This is an example of using chat completions API for python users.
from openai import OpenAI
client = OpenAI(
api_key="<Your API Key>",
base_url="https://api.novita.ai/openai"
)
response = client.chat.completions.create(
model="minimax/minimax-m2",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello, how are you?"}
],
max_tokens=131072,
temperature=0.7
)
print(response.choices[0].message.content)
Before installing Claude Code, ensure your system meets the minimum requirements. Node.js 18 or higher must be installed on your local environment. You can verify your Node.js version by running node --version in your terminal.
For Windows
Open Command Prompt and execute the following commands:
The global installation ensures Claude Code is accessible from any directory on your system. The npx win-claude-code@latest command downloads and runs the latest Windows-specific version.
For Mac and Linux
Open Terminal and run:
npm install -g @anthropic-ai/claude-code
Mac users can proceed directly with the global installation without requiring additional platform-specific commands. The installation process automatically configures the necessary dependencies and PATH variables.
Step 2 :Setting Up Environment Variables
Environment variables configure Claude Code to use Kimi-K2 through Novita AI’s API endpoints. These variables tell Claude Code where to send requests and how to authenticate.
For Windows
Open Command Prompt and set the following environment variables:
set ANTHROPIC_BASE_URL=https://api.novita.ai/anthropic
set ANTHROPIC_AUTH_TOKEN=<Novita API Key>
set ANTHROPIC_MODEL="qminimax/minimax-m2"
set ANTHROPIC_SMALL_FAST_MODEL="minimax/minimax-m2"
Replace<Novita API Key>with your actual API key obtained from the Novita AI platform. These variables remain active for the current session and must be reset if you close the Command Prompt.
For Mac and Linux
Open Terminal and export the following environment variables:
export ANTHROPIC_BASE_URL="https://api.novita.ai/anthropic"
export ANTHROPIC_AUTH_TOKEN="<Novita API Key>"
export ANTHROPIC_MODEL="minimax/minimax-m2"
export ANTHROPIC_SMALL_FAST_MODEL="inimax/minimax-m2"
Step 3: Starting Claude Code
With installation and configuration complete, you can now start Claude Code in your project directory. Navigate to your desired project location using the cd command:
cd <your-project-directory>
claude .
The dot (.) parameter instructs Claude Code to operate in the current directory. Upon startup, you’ll see the Claude Code prompt appear in an interactive session.
This indicates the tool is ready to receive your instructions. The interface provides a clean, intuitive environment for natural language programming interactions.
Step 4: Using Claude Code in VSCode or Cursor
Claude Code integrates seamlessly with popular development environments. It enhances your existing workflow rather than replacing it.
You can use Claude Code directly in the terminal within VSCode or Cursor. This maintains access to your familiar development tools while leveraging AI assistance.
Additionally, Claude Code plugins are available for both VSCode and Curs
For Individual Developers or Small Teams: Is It Worth Switching or Mixing M2 Now?
Short answer: Not yet for full migration — but yes for selective use.
Reasoning: MiniMax-M2 offers faster response times and lower operating costs, which make it appealing for small teams building lightweight coding agents or running high-frequency prototype loops. However, Claude Sonnet 4.5 still leads in reasoning depth, multi-module reliability, and tool orchestration.
Best practice: Use M2 for quick iterations, script generation, and cost-sensitive batch jobs. Keep Claude 4.5 for production-level development, debugging, and long-context tasks. A mixed workflow — M2 handling draft or repetitive workloads, Claude verifying and refining outputs — yields the best efficiency-to-quality balance.
MiniMax-M2 achieves low-latency, low-cost efficiency through a 10 B active-parameter design and a 200 K context window, excelling in retrieval and lightweight automation. Claude Sonnet 4.5, with stronger reasoning and tool integration, remains better for complex, multi-module software engineering. Together, they show that practical deployment is not about one replacing the other but about matching task complexity with the right model.
Frequently Asked Questions
What makes MiniMax-M2 faster than Claude Sonnet 4.5?
MiniMax-M2 activates only ≈10 B parameters per request, reducing memory load and improving concurrency—hence faster inference and lower cost.
Does Claude Sonnet 4.5 still perform better in coding?
Yes. Claude Sonnet 4.5 outperforms MiniMax-M2 by 10–20 % in SWE-Bench and logic-intensive tasks due to stronger long-context reasoning and agent planning.
When should I use MiniMax-M2 instead of Claude Sonnet 4.5?
Use MiniMax-M2 for quick prototyping, batch scripting, or cost-sensitive automation. Use Claude Sonnet 4.5 for multi-language, multi-file projects requiring tool orchestration and debugging.
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