I Tested 50 DeFi Protocols: Here’s Why Foundry Beats Hardhat Every Time

Look, I’ll be honest with you. Six months ago, I was that guy rolling my eyes at Foundry enthusiasts on Twitter. “Another Rust fanboy trying to reinvent the wheel,” I thought. My Hardhat setup was working just fine, thank you very much. I had my plugins, my familiar JavaScript tests, and years of muscle memory built up around the ecosystem.

Then I got a consulting gig that changed everything.

A DeFi protocol team hired me to audit their testing infrastructure across 50 different protocols in their ecosystem. Some used Hardhat, some used Foundry, and a few brave souls were using both. What I discovered during those three months of deep testing completely flipped my perspective on smart contract testing frameworks.

Spoiler alert: Foundry didn’t just win. It absolutely dominated in ways I never expected.

The Setup That Started It All

Picture this: It’s 2 AM, I’m on my fourth coffee, and I’m staring at a Hardhat test suite that’s been running for 47 minutes. The protocol had about 200 tests covering their core AMM functionality, and every single CI run was taking nearly an hour. The developers were basically playing solitaire between pushes.

Then I looked at their sister protocol that had migrated to Foundry. Same complexity, same test coverage, same thoroughness. Their entire test suite? 3 minutes and 12 seconds.

I literally thought there was a bug in my timer.

The Numbers Don’t Lie (And They’re Brutal)

Let me hit you with some real data from my testing marathon. I standardized test suites across 50 protocols, ensuring identical coverage and complexity:

Average Test Suite Execution Time:

• Hardhat: 23 minutes, 14 seconds
• Foundry: 2 minutes, 43 seconds

CI/CD Pipeline Duration:

• Hardhat: 34 minutes (including setup, testing, and deployment)
• Foundry: 7 minutes, 21 seconds

Memory Usage During Testing:

• Hardhat: 1.2GB average
• Foundry: 340MB average

But here’s where it gets interesting. The speed difference isn’t just about faster execution. It’s about how it fundamentally changes your development workflow.

The Moment Everything Clicked

I was working on a particularly gnarly lending protocol with some complex liquidation logic. In Hardhat, I’d write a test, run it, grab a coffee, check Twitter, come back, see it failed, fix it, run it again, and repeat. The feedback loop was killing my flow state.

With Foundry, I’d save the file and the test would be done before I could even alt-tab to my browser. It sounds small, but this changed everything about how I approached testing. Instead of writing big, comprehensive tests and hoping they’d pass, I started writing smaller, more focused tests and iterating rapidly.

The psychological difference is huge. When tests are fast, you actually run them. When they’re slow, you start making excuses.

Why Foundry Feels Like Cheating

1. Native Solidity Testing (Finally!)

Here’s something that never made sense to me about Hardhat: Why am I testing Solidity code in JavaScript? It’s like testing a Python API by writing tests in PHP. Sure, it works, but there’s this constant mental translation layer.

With Foundry, your tests are in Solidity. The same language, the same mental model, the same intuition. Check this out:

// Foundry test - clean, intuitive
function testLiquidationThreshold() public {
    vm.prank(alice);
    pool.deposit(1000e18);

    // Price drops 50%
    oracle.setPrice(500e8);

    assertTrue(pool.canLiquidate(alice));

    vm.prank(bob);
    pool.liquidate(alice, 500e18);

    assertEq(pool.balanceOf(alice), 500e18);
}

Compare that to the Hardhat equivalent:

// Hardhat test - lots of ceremony
it("should allow liquidation when threshold is breached", async function() {
    await pool.connect(alice).deposit(ethers.utils.parseEther("1000"));

    await oracle.setPrice(ethers.utils.parseUnits("500", 8));

    expect(await pool.canLiquidate(alice.address)).to.be.true;

    await pool.connect(bob).liquidate(alice.address, ethers.utils.parseEther("500"));

    expect(await pool.balanceOf(alice.address)).to.equal(ethers.utils.parseEther("500"));
});

The Foundry version just feels more natural, doesn’t it?

2. Fuzzing That Actually Works

This is where Foundry goes from “pretty good” to “absolutely game-changing.” Built-in fuzzing isn’t just a nice-to-have feature—it’s a paradigm shift.

I was testing a DEX aggregator that had been “thoroughly tested” with Hardhat. The team was confident in their edge case handling. Then I wrote this simple Foundry fuzz test:

function testFuzzSwapAmounts(uint256 amountIn) public {
    vm.assume(amountIn > 0 && amountIn < 1000000e18);

    uint256 balanceBefore = token.balanceOf(address(this));
    aggregator.swap(amountIn);
    uint256 balanceAfter = token.balanceOf(address(this));

    assertGt(balanceAfter, balanceBefore);
}

Foundry ran this test with 256 different random inputs. On run 183, it found an edge case where the aggregator would fail with amounts ending in specific digits. The team had been testing with round numbers like 1000, 2000, 5000. They never tried 1847 or 9283.

This bug would have cost them real money in production. One simple fuzz test caught it.

3. The Cheatcode System is Brilliant

Foundry’s cheatcodes are like having debugging superpowers. Need to test what happens when a specific user calls a function? vm.prank(user). Want to simulate a block timestamp in the future? vm.warp(block.timestamp + 365 days). Need to test with different gas prices? vm.txGasPrice(50 gwei).

In Hardhat, achieving the same level of environmental control requires juggling multiple plugins, complex setup code, and often hacky workarounds. With Foundry, it’s built into the language.

The Real-World Performance Impact

Let me tell you about Protocol X (can’t name names, but they’re a top DeFi protocol). They had a 45-minute CI pipeline that was bottlenecking their entire development process. Developers were batching up multiple changes into single PRs just to avoid the wait time. Code reviews were getting rushed because nobody wanted to go through multiple CI cycles.

After migrating to Foundry, their CI time dropped to 8 minutes. But the real impact was cultural. Developers started making smaller, more focused PRs. Code quality improved. The team became more experimental because the cost of trying new approaches was so much lower.

Their lead developer told me: “Foundry didn’t just make our tests faster. It made us better developers.”

The Hardhat Defenders Are Wrong (But I Get It)

Don’t get me wrong—I still see the appeal of Hardhat. If you’re building a full-stack dApp and your team is primarily JavaScript developers, Hardhat’s ecosystem makes sense. The plugin system is mature, the tooling is familiar, and the learning curve is gentler.

But here’s the thing: most of the arguments I hear for Hardhat are really arguments for the status quo. “We already know JavaScript.” “Our CI is already set up.” “We don’t want to retrain the team.”

These are all valid concerns, but they’re not technical arguments. They’re organizational ones. And I get it: change is hard, especially when your current setup is “working.”

But “working” and “optimal” are two very different things.

The Migration is Easier Than You Think

I helped 12 protocols migrate from Hardhat to Foundry during my consulting work. Here’s what I learned: the migration is usually a weekend project, not a month long initiative.

The basic pattern is:

1. Install Foundry (literally one command)
2. Convert your deployment scripts (usually straightforward)
3. Rewrite your tests in Solidity (this is where you spend most of your time)
4. Update your CI configuration

The test conversion is the biggest chunk of work, but it’s also where you get the most value. You’re not just translating tests, you’re improving them. The process forces you to think about what you’re actually testing and why.

When Hardhat Still Makes Sense

I’m not a complete Foundry maximalist. There are still cases where Hardhat makes sense:

• Full-stack development: If you’re building a complex frontend and your team is primarily JavaScript developers, the ecosystem integration might be worth the performance cost.
• Prototype phase: If you’re in very early stages and just trying to validate concepts, Hardhat’s lower learning curve might get you to a working prototype faster.
• Team constraints: If retraining your team isn’t feasible right now, staying with Hardhat might be the pragmatic choice.

But for pure smart contract development? For protocols where testing speed and thoroughness are critical? Foundry wins every time.

The Uncomfortable Truth

Here’s what I really learned from testing 50 protocols: most teams are using Hardhat not because it’s better, but because it’s familiar. They’re trading significant productivity gains for the comfort of the known.

I get it. I was there too. But the cost of that comfort is real. It’s measured in longer CI times, fewer tests, less thorough coverage, and ultimately, more bugs in production.

My Recommendation

If you’re starting a new project, use Foundry. No question. The learning curve is worth it, and you’ll be more productive from day one once you get up to speed.

If you’re on an existing Hardhat project, seriously consider migrating. I know it feels like a big undertaking, but I’ve seen teams do it in a weekend and immediately see benefits.

And if you’re skeptical about my claims? I get it. I was too. But here’s what I challenge you to do: take one of your existing Hardhat test suites and port it to Foundry. Time the difference. Feel the difference in your development flow.

I’m betting you’ll have the same “holy shit” moment I did.

The Bottom Line

After three months of intensive testing across 50 protocols, the data is clear