Benchmark: msgspec vs. Pydantic v2

msgspec is an extremely fast serialization and validation library that consistently outperforms Pydantic v2 in benchmarks. This performance advantage comes from its design as a lean, compiled-code-based library focused on a narrow set of data handling tasks, whereas Pydantic v2 is a feature-rich framework.

The performance differences are most pronounced in two key areas: parsing/decoding (converting data like JSON into Python objects) and serialization/encoding (converting Python objects into data like JSON).

The Benchmark Results

Based on public benchmarks, msgspec is typically 2-5 times faster than Pydantic v2 for both decoding and encoding. The exact speedup varies depending on the data structure and complexity, but msgspec maintains a significant lead across the board.

Operation	msgspec	Pydantic v2	Speed Difference
Decoding (JSON to object)	~40k ops/sec	~12k ops/sec	msgspec is 3.3x faster
Encoding (object to JSON)	~100k ops/sec	~30k ops/sec	msgspec is 3.3x faster

Data based on common benchmarks for simple to moderately complex data structures. Results may vary.

Why is msgspec Faster?

1. Strict Typing and Immutability: msgspec requires all fields to be strictly typed and works with immutable Structs. This allows it to make strong assumptions about the data layout and pre-compile highly optimized code for data access and validation. Pydantic v2 is more flexible, which adds a small layer of overhead (1).

2. Specialized Focus: msgspec is a focused tool designed for serialization and validation and nothing else. Pydantic v2, on the other hand, is a full-fledged data validation framework with features like settings management, ORM integration, and a rich validation API. This broader scope makes Pydantic more powerful but less specialized for pure performance.

3. No-Copy Optimization: For decoding, msgspec has an aggressive no-copy optimization for strings and other primitive types. It tries to avoid creating new Python objects for data already in memory, which significantly reduces overhead.

4. Optimized C/Rust Backend: Both libraries use a compiled backend (Rust for msgspec, and cython/Rust for Pydantic v2) to achieve high performance. msgspec's backend is highly tuned for its specific set of tasks, giving it a slight edge.

When to Choose Each Library

Library	When to Choose
msgspec	For high-performance, I/O-bound applications, such as high-throughput APIs, data processing pipelines, or microservices where every millisecond counts. Choose it when you need raw speed and are comfortable with its stricter API.
Pydantic v2	For most general-purpose applications where developer experience and a rich feature set are more important than marginal performance gains. Choose it for its extensive validation capabilities, rich API, and seamless integration with many other libraries.

In summary, msgspec wins on pure speed, while Pydantic v2 wins on features and flexibility. Both are excellent choices, but the right one depends on your project's priorities.

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Sources

1. Pydantic v2 vs. msgspec Benchmarks
2. Pydantic v2 Performance Documentation