Not as a general rule. gRPC commonly sends binary Protocol Buffers over HTTP/2, while REST-style APIs often use JSON—but REST does not require text payloads, and JSON APIs can also use HTTP/2. Binary encoding and HTTP/2 features can improve performance in some workloads. A 2016 gRPC benchmark reported several different advantages, not one universal sevenfold speedup.
REST and gRPC are different things from JSON and Protobuf
REST describes an architectural style for APIs; it does not dictate a particular data format or HTTP version. JSON is a common choice for REST-style APIs because people and ordinary web tools can readily inspect it. Those APIs can use HTTP/2 too. As Microsoft Learn puts it, “HTTP/2 is not exclusive to gRPC.”
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gRPC is an RPC framework designed for HTTP/2 and commonly uses Protocol Buffers (Protobuf) to define and encode messages. Protobuf’s wire format is binary, so it is not meant to be read directly as text. These are bundled design choices, not a clean test of “text versus binary” alone: encoding, transport, implementation, and workload can all affect results.
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What the cited benchmark actually measured
In a gRPC project article dated July 26, 2016, David Cao of Google described Android client-side comparisons. The serialization tests compared Protobuf with JSON; a separate RPC test compared unary gRPC calls with a simple RESTful HTTP JSON service. The RPC test repeatedly sent the same message for 60 seconds. The reported results vary by metric:
| Measurement in the 2016 test | Reported result | What it does—and does not—show |
|---|---|---|
| Serialization | Protobuf was about 3× faster than JSON in the tested setup. | A serialization result, not an end-to-end request speedup for every API. |
| Deserialization of messages below 1 KB | JSON was about 1.5× faster. | Small-message decoding did not favor Protobuf in this test. |
| Deserialization of messages above 15 KB | Protobuf was about 2× faster. | The result differed with message size. |
| Protobuf serialization versus gzipped JSON | Protobuf was well over 5× faster. | This is a particular serialization comparison, not a universal API-latency ratio. |
| Unary-call latency | gRPC was reported as 5×–10× faster through the 95th percentile, with averages around 2 ms. | This was the test’s specific Android client comparison; it does not establish a stable 7× result for other systems. |
| Bandwidth for 100–1,000-byte payloads | About 3× better for Protobuf. | A result for the stated small-payload range. |
| Bandwidth for 10–100 KB payloads | About 2× better for Protobuf. | A different result for larger payloads. |
The same article reported that streaming calls were more than 2× faster than unary calls, but it did not compare streaming gRPC against an equivalent HTTP streaming setup. That result therefore cannot establish a streaming advantage over a like-for-like HTTP API.
The benchmark is useful evidence that design choices can matter, but it is old and specific to its test setup. It does not show that every present-day gRPC service is seven times faster than every REST API.
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Why gRPC can be faster—and what else affects speed
Binary serialization can reduce work
Protobuf encodes data in a compact binary format. Depending on the schema, message, and implementation, encoding or transmitting a message may require less work or fewer bytes than using JSON. The benchmark’s differing results by operation and size illustrate why a single ratio cannot describe all cases.
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HTTP/2 can manage concurrent calls efficiently
gRPC is designed for HTTP/2, which supports multiplexing multiple streams on a connection. That can help when a service handles concurrent calls. But an HTTP API can also use HTTP/2, so this capability is not exclusive to gRPC.
The application and test conditions still count
Serialization may be only a small part of a request’s total time. Network conditions, compression, concurrency, server and client languages, runtime versions, application work, and database calls can change the outcome. A meaningful comparison needs equivalent functionality and clearly stated conditions, including latency percentiles rather than averages alone.
When gRPC or a JSON HTTP API is a better fit
| Consideration | gRPC with Protobuf | HTTP API with JSON |
|---|---|---|
| Payload and inspection | Compact binary messages; inspecting them requires the schema and suitable tools. | Human-readable payloads that are straightforward to inspect and compose by hand. |
| Transport | Designed for HTTP/2. | Can also use HTTP/2; the API style does not require HTTP/1.x. |
| Browser clients | Ordinary browser support is limited. Supported stacks can use gRPC-Web or JSON transcoding. | Broad native browser and general HTTP-tool support. |
| Development workflow | Requires .proto contracts, generated code, and client/server build tooling. | Often easier to call with general-purpose HTTP tools and simple clients. |
| Common fit | Internal services, streaming, polyglot services, and constrained networks. | Public or browser-facing APIs, interoperability, and cases where human inspection is useful. |
These are selection criteria, not fixed rules. A system can expose both a gRPC interface and a JSON HTTP interface for different clients.
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- Contracts and generated code: gRPC adds .proto definitions and generated client/server code to the development and build workflow.
- Debugging: Protobuf data is not human-readable on the wire; inspection depends on having the schema and appropriate tooling.
- Browser access: Standard browsers cannot directly call ordinary gRPC services. gRPC-Web or JSON transcoding are options only in supported setups.
- Streaming complexity: Long-lived or bidirectional streams can avoid repeated request overhead when the interaction suits them, but they introduce reconnect and concurrency concerns.
- Large messages: gRPC messages are loaded into memory before sending and deserialized into memory on receipt. For large binary payloads, streaming or a direct HTTP streaming endpoint may suit the application better.
- No fixed payload ratio: Protobuf is not guaranteed to produce a particular size or speed advantage for every schema and message.
How to evaluate a “7× faster” claim
Before using a ratio to choose a protocol, identify exactly what was measured. Serialization throughput, request latency, throughput, bandwidth, and payload size are different metrics and should not be treated as interchangeable.
- Specify client and server languages, runtime versions, message schema, and payload sizes.
- State compression, HTTP version, concurrency, network conditions, and whether database or application work is included.
- Compare equivalent functionality and report latency percentiles as well as averages.
- Use a workload that reflects the system’s actual clients and traffic, rather than assuming a published result transfers unchanged.
The gRPC project maintains performance testing infrastructure, but its benchmarking guide describes that infrastructure; it is not a current universal gRPC-versus-REST verdict.
Quick Recap
Sources
- Mobile Benchmarks — gRPC (David Cao, Google, July 26, 2016).
- Compare gRPC services with HTTP APIs — Microsoft Learn.
- gRPC vs REST: Understanding gRPC, OpenAPI and REST and when to use them in API design — Google Cloud.
- Benchmarking — gRPC.
- Performance best practices with gRPC — Microsoft Learn.
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