Solid 2 vs Octane

solid-2-versus-octane.md

NOTICE: I've summarized the perspectives of Octane's and Solid's creators here, for anyone short on time: https://gist.github.com/aleclarson/829c10aa7d287944ef75e1c2a90bef06

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I'm a React/Preact/Astro developer with an interest in other renderers. The two that have most caught my eye recently are Octane (from Dominic Gannaway of React Hooks / Svelte / Inferno fame) and Solid 2.

I asked ChatGPT to compare them with its own "Renderer DX Pillars", which I've shared below. This is its gut instinct, with very little hedging:

Pillar	Winner	Why
State architecture freedom	Solid 2	Reactivity is independent of components. Much less component gravity.
Reactive reasoning	Solid 2	The dependency graph is explicit and causal. Easier to answer “why did this update?”
Derived state & synchronization	Solid 2	Fine-grained derivation is the native model; less need to coordinate state manually.
Async/data flow	Solid 2	This is basically Solid 2's flagship idea. Async being part of reactivity feels deeper than improving Suspense/hooks ergonomics.
Component authoring	Octane	Normal values, normal functions, familiar TSX, fewer Solid-specific semantic gotchas.
Escape hatches	Solid 2, narrowly	Solid's primitives compose very directly with imperative JS without pretending everything is a component concern.
Ecosystem interoperability	Octane	If its React-ecosystem compatibility ambitions work, this could be a huge advantage.
Tooling & debuggability	Solid 2 today	More mature and battle-tested. Octane's compiler creates more invisible machinery that tooling has to explain well.
Architectural scaling	Solid 2	Its reactive model naturally lets domain/application architecture exist independently of rendering.

So my gut scoreboard is:

Solid 2: 7 Octane: 2

But the two Octane wins are meaningful ones.

Where Octane feels strongest

Its pitch seems particularly strong around:

“I want React's authoring experience without React's runtime/design baggage.”

You get something like:

function Counter() {
  const [count, setCount] = useState(0);
  const doubled = count * 2;

  return <button onClick={() => setCount(count + 1)}>
    {doubled}
  </button>;
}

That's extremely approachable.

Solid asks you to internalize:

const [count, setCount] = createSignal(0);
const doubled = () => count() * 2;

which isn't hard, but it is a different programming model.

So for day-one DX, I wouldn't be surprised if Octane feels better.

Where Solid feels fundamentally stronger

Solid's advantages seem to accumulate as the application becomes less like:

some components with state

and more like:

a complex reactive application that happens to have a UI.

That's where signals outside components, ownership, fine-grained derivation, async graph semantics, stores, and independent domain state all start reinforcing each other.

My gut says the trajectory looks something like:

small app

Octane  ██████████
Solid   █████████

         ↓ complexity

large/stateful app

Octane  ████████
Solid   ████████████

Not because Octane necessarily scales poorly, but because Solid's abstraction seems closer to the actual problem being modeled once state relationships get complicated.

The pillar I'd be least confident about

Escape hatches.

Octane could easily end up winning there if its compiler makes effects, refs, subscriptions and integration code extraordinarily pleasant.

And ecosystem interoperability could become an overwhelming Octane win if their compatibility layer is genuinely broad and reliable rather than “we have adapters for the popular demos.”

My strongest instincts

If I had to assign confidence rather than points:

• Solid strongly wins: state architecture, derived state, async, architectural scaling.
• Solid probably wins: reactive reasoning, escape hatches.
• Octane strongly wins: initial component authoring.
• Octane probably wins: ecosystem interoperability.
• Solid wins for now: tooling/maturity.

The biggest question I'd personally want answered before choosing between them is therefore not performance.

It's:

Does Octane's compiler actually eliminate the architectural drawbacks of component-centric reactivity, or does it mostly make that model much nicer to write?

If it's the latter, I'd expect Solid 2 to remain the stronger foundation for complex applications.

We agree about a lot of things. And the cross-pollination is real — but I'd correct the lineage on the specific design you're critiquing. The purely colorless model — pending reads throw, value types stay clean, no marker anywhere — landed in our signals repo in August 2023, before runes were announced (we folded that repo into the monorepo, but the commits are all still there). Resources in Solid 1 pointed the direction but were nullable, so I won't claim more than we shipped — the fully colorless contract is the 2.0 work. What the Svelte conversations actually convinced me of was removing transitions, not the coloring approach. And notably, Svelte still doesn't have the colorless model today: await in a $derived or a template is the color, written right there in the source. This design is ours and very deliberate — which is exactly why I want to defend it properly.

Coloring is painful when color is static and viral — async/await recolors every caller in the chain. We erased the color at the read site instead. Every reactive read has one contract: it may not be ready, pending-ness propagates through derivation, and boundaries or isPending/latest absorb it wherever you actually care. The payoff is that asyncness isn't load-bearing in your code's structure — swap a sync signal for an async one and zero downstream code changes. Put it in the type system and that refactor goes viral again. Readiness as a dynamic, queryable property is our answer to coloring. And I'd gently note the compiler only "knows" inside its horizon — your own doc ships a runtime guard for promise shapes that escape the analysis through props and foreign modules. Deterministic where it can see; runtime fallback where it can't. Same boundary we're both living with, we just put the contract on different sides of it.

I'll also take the garbage collector analogy, because I think it points the other way. GCs won general-purpose memory management because the runtime owns the live object graph — reachability is a runtime property that static analysis provably can't recover. Every attempt to replace that with inference under familiar syntax (escape analysis, region inference) ended up as an optimization layered on a runtime system, never a substitute for it. The one static approach that genuinely worked, Rust, required a new, stricter language — and even Rust concedes the unprovable shapes back to the runtime: Rc, RefCell, Arc are all runtime mechanisms for exactly the cases the borrow checker can't see through. Static analysis where it can prove, runtime knowledge for the general case — that's the stable equilibrium in memory management, and I'd bet it's the stable equilibrium here. Which is, as far as I can tell, exactly what "use strong" is walking toward: a genuinely stricter language. I think that's a coherent, even exciting bet — but notice what it spends: the moment the compiler hard-rejects React habits with no override, "your React knowledge transfers" stops being the pitch. At that point we're both asking people to learn a new model, and the comparison becomes: where do the semantics live — in a specified runtime graph you can interrogate while the app runs, or in a compiler's analysis you trust and read diagnostics from? Your own list of remaining work ("explain what the compiler decided and connect that explanation to what happened at runtime") is that exact gap, described from the other side.

On agents we mostly agree, but the argument cuts both ways. Yes, agents make stricter compile-time contracts practical — they'll happily refactor against a precise diagnostic. They also make day-one authoring familiarity matter much less, and when they're debugging a running application they ask runtime questions: why is this pending, what is this transition waiting on, why did this update twice. A diagnostic explains what the compiler couldn't prove; it doesn't explain what the app just did. I don't think compile-time and runtime knowledge are rivals — we compile too, obviously. The difference is only what gets discarded before the app runs.

No perfect async model, agreed — that's not the claim. The claim is narrower: when the model inevitably misses something, I want the miss to be inspectable in a specified, running graph rather than reconstructed from generated output. That's the property I think compounds.

Genuinely looking forward to watching "use strong" evolve. If the endgame is that both of us abandon "familiar" as a value and compete on which new model earns its constraints — that's a much better framing than the one this thread started with.

Yeah, fair correction on the timeline. I was referring to the async work and discussions around Svelte, not claiming Solid’s colourless design came from me. I worded that badly, but I think you know what I meant anyway – actually you definitely do, we spoke about this on our podcast or Discord etc.

I also understand what you mean about every reactive read having the same contract. Being able to replace a synchronous source with an async one without rewriting everything downstream is valuable. I’m not suggesting you should put Promise<T> everywhere and bring that problem back. TBH my design for Svelte was not this, Rich changed it around originally, I literally pitched the same idea you had with $derived or I think at the time when I was on Svelte team it was $async. It was like a year ago now, who knows.

The distinction I was trying to get at is slightly different though. In ordinary JS, const value = readValue() gives me a value from that execution. A getter or a tracked derivation preserves a different relationship. Moving a read, passing its result instead of the getter, or calling it outside the right tracking scope can change the behaviour. The runtime might know exactly what happened, but that doesn't mean the distinction is obvious from the code or its value types. Async adds another question about where a read can prevent execution from continuing. I still think theres a real trade-off there, even when the reactive graph handles it correctly.

In the React "shaped" component model, the default is that calculations inside render run again. const total = price * quantity stays ordinary code. You then remove unnecessary work through memoisation, whether written manually or performed by the compiler. That doesn't make React free of snapshots or stale closures, obviously. But it is a different starting contract, and one I think is worth keeping.

You're right that I was too loose with the point about the compiler knowing. I don't mean it can see through arbitrary JS or predict every runtime branch. I mean we can define a language with stronger rules, establish more from those rules, and keep runtime behaviour or reject a pattern where the analysis ends. I want those semantics to be specified, rather than depending on whatever an optimisation happened to manage.

The Rust comparison is actually quite close to what I meant with "use strong". Yes, it asks people to learn some new rules. I don't think that makes their React knowledge stop transferring, though. Components, props, state, composition, and a lot of existing application structure still make sense. Strong mode is opt-in today, and ordinary code and dependencies can keep their existing behaviour. Familiarity can be useful without being a promise to preserve every habit forever. TBH it doesn't really matter at all to agents, as asking them to adhere to new rules is hardly going to cause anyone to complain, and that goes back to my point in the prior comment.

You’re right about debugging, to some extent (unless I have got you wrong). If an agent is looking at a broken app, it needs evidence from what actually ran, a compiler error only gets you so far. Octane already exposes source-linked render causes, hook state, and transition/Suspense state, but it doesn’t yet give you the same view of causality as your graph. The missing part is connecting the compiler’s choices to what you can inspect at runtime. I think we can do that without making a fine-grained graph the model for everything. Plus we already have octane-doctor, devtools support is on the way. However, in real world practice, I think this area is going to be completely changed as agents become even more capable. I've already had a big issue debugged in realtime, in the compiled output of Octane debugged by an agent inserting console.log and it working, it fixed it. It didn't care for the compiled output being completely different from the user-code, it just worked great – thank you Codex and ChatGPT 5.6 Sol, which gets Octane so well in a very large codebase.

I suspect we agree on more than the earlier comments suggested. Agents make a new model easier to pick up, but they also make vague semantics easier to paper over, which isn’t good. Octane still has to prove that its extra constraints are worth it – which it will, I'm confident of that. The only useful answer to that is going to be in the implementation, not another round of analogies. Using tsrx has yielded so many benefits you wouldn't believe too, I can't really get into those details just yet, but believe me it's been transformative.

My push back is mostly – Solid 2.0 has been an exceptional launch, but don't use that as a reason to denounce Octane. I've got a strong hunch, a spider-sense almost that that I'm onto something equally as special Solid 2.0, except Octane might actually be the next big-thing (fucking finally). So that's why I never rained down on your celebration, because Solid is epic – you know me personally and I love your work Ryan. I never went on any of your threads on X, Reddit or whatever telling people to use Octane over Solid. So don't take what I say personally, we're just learning from one another, and that's healthy.

This time no AI.

If I came off dismissive of Octane that isn't my intention. Especially not from a technology standpoint. The current push of AI forks I find distasteful given the effort it takes to create those libraries in the first place, but I wasn't grouping Octane in with them.

It is more that Ive been pushing back against React for over a decade now. Not React the implementation, but React the model. React the implementation has been poked at for years. But the model has had people feel secure despite what empirically was in front of them. It has taken a long time to gain any ground against its inertia.

So to me this is like OOP vs FP, or maybe closer to home immediate mode vs retained mode. I didn't enter the ring because of adoption, developer experience, or even performance, but a belief in a fundamentally better model. Obviously I acknowledge it isn't something so cut and dry. But it is why I focus on education and trends that span more than a single framework.

I don't doubt Octane is capable of everything you are setting out to accomplish. I think language/compiler is an important part of the authoring story even more so with AI. Solid just approaches the problem the way I always have with the view a compiler is a last stage optimization. We need to know what we are building first. It can be argued that maybe Svelte switched gears too quickly, but it is a textbook example of what Im talking about. They had the compiler but then they realized they had an incomplete model.

Solids track record of not changing is very much grounded in our approach. We didn't chase DX. And in that I think we have a lot in common with React. The prevalence of agents doesn't change those foundations of truth to me. Which is to say if you ask me what we should be building it isn't Reacts model. That foundation has had its chance and for the betterment of the ecosystem we need to explore different paths.

The compiler can come later. We're still catching up to the deficit of not having nearly as many people building on this model the past decade. The fact that we are still discovering concrete wins at runtime without a compiler I view as evidence this has more legs. Far from solved.

So if you hear me being critical here it is just rebelling against the calcification of Reacts core model. It has enough legacy as it is. I refuse to accept it and I will undermine it at every junction. Not out of malice or disrespect of the engineering that goes into solutions built on top of it, but because that is the foundation on which my work stands.

Thanks for clarifying Ryan. Like I said, it's all good.

I know you only have good intentions with your thinking and comments. I'm not trying to rain on your endeavours or your critical thinking into why React's model isn't the right one. We all know it's not right, I already tried and largely failed with trying to change that with Ripple. The community just have no appetite to adopt new frameworks anymore. I was having a chat with a very well known software engineer that used to work at Google the other month and he said that he was excited by Ripple but has no reason to move from React, because the migration path simply isn't worth it anymore. He can get an agent to fix the performance issue in React and it largely just works eventually.

I'm just a builder and tinkerer. Octane is an attempt for me to delve further down the path I first started on with Inferno all those years back. I feel like I left unfinished business on the table when I was working on the OG React Compiler – Prepack whilst at Facebook and this has been a nice change of scenery for me. If the migration story from moving from React to something a lot better is watertight, then just maybe it will move the needle, or at least their agent will tell them they should.

It's also crucial to point out here that signals play a major role in Octane too – just not as a first-class citizen just yet – they might though, but we first wanted to let people decide what to use and our recommendation has been to use Alien Signals or Jotai/Zustland if people are already using that in their React apps. useState is a good local state mechanic, but again, with "use strong" we can detect people using it in problematic ways and push people to use better state mechanics, such as signals, state machines or context.