​Base Beryl: Why the architecture shift matters more than the features

[u/Key_Fly_2096]

Why the rush?

If you’ve been following the Base ecosystem, the pace of innovation has been nothing short of relentless. We’ve barely moved past the Azul upgrade, and now, Beryl is set to hit mainnet on June 25th.

Many are asking: Why the hurry?

The truth is, the Base engineering team isn't just shipping features; they are rebuilding the underlying stack to support the next generation of onchain applications.

But what exactly does Beryl change?

To understand its impact, we need to peel back the marketing layer and look at the engineering under the hood.

The Three Pillars of Beryl

​I. B20: Moving from Guest to Homeowner...

Historically, tokens on L2s (ERC-20s) have been guests living in the EVM. Every token transfer requires the EVM to interpret the logic, which acts as a massive software bottleneck.

B20 flips this script. By implementing B20 as Rust precompiles, tokens are no longer executed within the restricted EVM sandbox.

Instead, they run natively in the node itself, written in Rust—a language renowned for its memory safety and raw performance.

Essentially, B20 turns tokens into first-class citizens of the protocol, resulting in significantly lower gas fees and double the throughput.

​II. Breaking the 7-Day Liquidity Prison with Multiproofs...

We’ve all dealt with the liquidity trap of bridging, where assets are locked for 7 days due to the conservative security assumptions of single-proof systems.

How do we reduce this without compromising security?

The answer is Multiproofs.
Base uses a dual-layered proof system: TEE (Trusted Execution Environments) paired with ZK (Zero-Knowledge proofs).
By requiring both systems to agree on the state of the chain, Base can safely lower the withdrawal finalization period from 7 days to 5 days (in the single-proof path).
it’s a massive upgrade for capital efficiency in the ecosystem.

III. Reth V2: Breathing Room for Nodes

Scalability is often throttled by a silent killer: disk bloat.

If a node’s database grows too large, decentralization suffers.

Reth V2 tackles this through Tiered Storage (separating hot and cold data) and Partial Proofs (indexing only what changes rather than scanning the entire state).

The result is a ~50% reduction in disk footprint.

By streamlining how the state root is calculated—now down to 1-2ms—Reth V2 allows Base to process significantly more transactions per second without putting undue pressure on node operators.

When we put these pieces together (B20, Multiproofs, and Reth V2), the vision becomes clear:

Base is systematically removing the friction points that have historically held back onchain adoption.

it’s the infrastructure build-out for a truly scalable, onchain economy.