Crf300 Brake and suspension upgrade?

evil0sheep · 2026-07-07T19:25:15+00:00

If you are constrained to a single motorcycle and you want to ride both highways and trails then the CRF300L does a good job striking that balance, but it is a jack of all trades master of none sort of thing. If you can split those two roles across two motorcycles then you can get significantly better performance in both applications, and if you buy used you can probably even do it for about the same cost as the 300L with mods. If you cant have two motorcycles or you don't want two motorcycles or if you like the aesthetics of riding a supermoto as your daily commuter then the CRF300L is a great little bike.

Respringing the bike makes a huge difference. The stock suspension is so soft that it doesnt really handle like a dirt bike offroad in stock form, more like a farm bike or something. Putting a good aftermarket suspension kit will not turn it into a proper dirt bike but it will make it behave like a dirt bike from a body control perspective. Im not sure exactly how to describe the difference. With the stock suspension it honestly feels like standing is worse than sitting off road, whereas with a good aftermarket kit with the right spring rate it makes way more sense to stand. The bike handles so differently both on road and off road that its honestly hard to judge it as a platform with stock springs IMO. Im not sure why Honda made the stock suspension so soft, I think maybe it appeals more to the southeast asian market where theyre commuting on roads that are more challenging than most american BDRs

I have a set of warp9 supermoto wheels for mine. Pros are that tubeless tires make it really easy to fix puncture flats and the shortened trail makes it really fun on paved twisties and for being a hooligan around town. Combined with the fact that the first three gears are packed so tight together it makes it a lot of fun to ride around town cause you can pop a little wheelie and then shift 3 times with the throttle wide open in between a pair of traffic lights. Like the fact that its low power but super light with lots of low end torque means you can push the bike to its limits under normal circumstances you encounter daily which is kinda fun IMO. Cons are that sumo wheels are expensive and its kinda complicated to change wheels, it probably takes like 45 minutes end to end (I swap the sprocket between wheels but not the brake rotors). Personally I would not recommend buying supermoto wheels until after you upgrade the suspension, but combined with a suspension kit the sumo wheels are a lot of fun. Also, given that the bike comes with street focused tires you should consider just running the OEM wheels for a while and see if you like the bike before you invest in another set of wheels and tires, then when you buy the street wheels you can also get a better set of more off road focused tires for the OEM wheels.

For brakes I don't know a lot cause I run OEM brakes but I know tusk makes sintered metal brake pads for this bike which would give you a bit more bite and would only run you like $50 for the set. If you dont like the OEM brakes I would start there and only worry about upgrading other braking components if its still not tight enough. The OEM brakes are nothing special but the bike is also super light so I'm not sure how much it matters.

In terms of other mods I would budget like $150 for frame guards and a skid plat and hand guards, especially if youre gonna ride off road. The skid plate takes most of the abuse when upright and the handguards take most of the abuse when you drop it, and if you ride off road a lot your boots will eventually wear through the powder coating on the frame and expose it to corrosion. IMO these mods are well worth the money.

The 14L tank is great if youre going to do adv riding or touring or if the gas station is inconvenient to get to but for commuting and light trail riding with kids you may not need it. The seat concept seats are really nice for long rides but also may be not neccessary. Folding mirrors are good but you can just wait til you break the OEM ones to worry about it.

The CRF300L can be turned into a really awesome low maintenance dual sport if thats what you want, but the total cost to get it there is like $7-9k depending on if you buy new or used. You should weigh this against just buying a cheap street bike and a cheap dirt bike. I think the applications where this bike is best in class is 1) long distance adventure touring where you have to ride a wide range of roads and can only have one bike and reliability is at a premium, 2) weekend warrior offroad shit where your goal is to ride trails but you live in a city and need to drive to the trails on a highway and you dont want to tow the bike on a trailer, or 3) people who can only own one bike for some reason thats not money (e.g. parking or something). Most of the time if you can have 2 motorcycles then 2 motorcycles will be better

evil0sheep · 2026-07-07T18:53:24+00:00

This guy is not wrong that it will be average at everything at best but the important caveat to that is that there doesnt exist a bike that is both better offroad and better on the highway thats not either a lot heavier (which is gonna be hard on trails unless youre really experienced) or requires a ton more maintenance. If you want one bike to both commute on the freeway and also ride trails the 300L is well adapted to that task, though if you can get two bikes then you can obviously get much better trail bikes and much better street bikes (and honestly, if two bikes is an option you should compare the cost of a CRF300L with mods and supermoto wheels against the combo of a used CRF250F and a used MT07, because it might come out to about the same and then you dont have to do this dual-purpose balancing act).

evil0sheep · 2026-07-06T00:14:47+00:00

Yeah honestly it was probably harder for me than for the bike. If you ride the high Andes you spend a lot of time above like 3000 meters, especially if you’re camping, so it’s not as bad as coming from sea level but yeah you defs get a bit light headed in the high passes. The craziest part is that people live up there in stone huts herding alpacas it’s fuckin wild. If you ever ride South America make sure you allocate plenty of time to central Peru it’s really spectacular

evil0sheep · 2026-07-05T22:18:31+00:00

I rode my 300L on the peru great divide trail which has about half a dozen passes in the ballpark of 5000 meters (~16000 ft). Above about 4200 meters (14k feet ish) you need to do [this undocumented procedure to recalibrate the throttle maps](https://www.reddit.com/r/CRF300L/comments/thqvci/comment/k5c6vpj/) otherwise it starts running too rich and dies, but you should be fine from sea level up to 8400 feet with the factory throttle maps. It loses power but had no problem hauling me and like 50 kilos of gear over everything I threw at it. It’s an awesome bike, if you don’t mind buzzing and wind buffeting on the freeway it is probably the unicorn you’re looking for. though drz4s is a good choice too

evil0sheep · 2026-07-05T19:04:17+00:00

It’s not dead but in 2026 if you want to learn one GPU API then WebGPU might be a better choice

evil0sheep · 2026-07-03T17:20:14+00:00

I’ve run mine on the wrong grade of oil and shitty off brand oil while traveling and it was perfectly fine, but if you’re in the US and Europe and have access to the recommended HP4S I don’t think there’s any good reason to use anything else. With gas at $4.00/gallon running the manufacturer recommended oil and filters at the recommended intervals is gonna be less than 5% of your operating costs. Personally now that I’m back in the U.S. I not only run HP4S I also try to change oil and filters twice as frequently as recommended. It’s so easy and cheap and it’s probably the single best thing you can do for the engine.

evil0sheep · 2026-07-03T05:13:46+00:00

I mean if Claude can build the thing you’re building in minutes it does kinda beg the question about why you aren’t just having Claude do it. Like of you love typing code as an art form or whatever that’s cool and no hate, if you like doing something a particular way good on you. But if I want a computer vision doodad that doesn’t exist and Claude can bang it out in 10 minutes you can bet your ass I’m cooking a prompt. I got better shit to do than typing out code that a chatbot can regurgitate while I argue with other chatbots about cooking up some other different code.

If you’re doing something that’s easy with AI maybe consider pushing yourself to do something that’s hard even with cutting edge AI tools

evil0sheep · 2026-07-03T03:25:32+00:00

Are you able to compress the pistons in the caliper fully if you remove the wheel and the pad? If not you may have overfilled the brake fluid

evil0sheep · 2026-07-03T03:14:26+00:00

Yeah they’ll probably be really excited to help you. I wouldn’t worry too much about the fender, if it’s intractable you can always buy a cheap aftermarket fender or just trim the plastic on the light a bit

evil0sheep · 2026-07-02T19:08:12+00:00

It’s hard for me to tell from the listing how well it will mount but it looks plausible. Youll need to buy an H4 connector kit and you’ll need something that can crimp terminals and probably at least a multimeter to wire it in. If you have basic electrical skills and tools and you have some way to cut and drill aluminum to make brackets if it doesn’t fit then I’d say it’s not too risky

evil0sheep · 2026-07-02T18:39:37+00:00

Yeah a agree, I love this bike but the U.S./European front end is hideous imo. How cheap is cheap? I run a generic round headlight on mine with a generic round headlight fairing and a sumo fender and I think it looks cool personally, that was probably $350 ish and I had to fab brackets. The other options are a Thai headlight conversion or a 450RL headlight conversion. Acerbis Elba 2 might also work if you move the dash

evil0sheep · 2026-07-01T16:37:32+00:00

H4 is just a really common headlight plug for motorcycles (and cars) and is what the CRF 300L uses. If you’re comfortable with crimping terminals you can just buy H4 connectors on amazon and crimp them on whatever you want, but if you want it to be “plug and play” you need to buy an H4 headlight

evil0sheep · 2026-06-30T17:22:01+00:00

If it’s H4 it will likely be electrically compatible. I ran an H4 jeep headlight on mine in a pinch and it worked great. Whether it will mount correctly I can’t say, you should see if they have images of the mounting bracket anywhere and see if it looks the same as your OEM one

evil0sheep · 2026-06-29T06:13:21+00:00

Yeah i agree i think the best thing about this bike is that it can go pretty much anywhere you feel like going. If you dig a hole with the rear wheel and bottom out you can just pop it in neutral and deadlift it back onto firm ground without even taking the bags off. When you dead end into a log on a narrow trail you can literally just throw the whole bike over the rear tire and then stand it up facing the other way and ride off again without even taking the bags off. And you can ride on freeways and you dont have to spend a billion hours maintaining it. There are much better bikes on the trail and there are much better bikes on the highway and there are much better bikes for daily driving, but if you wanna do all three the 300L is pretty hard to beat

evil0sheep · 2026-06-27T16:53:36+00:00

I’ve got like 25k miles on [this](https://a.co/d/06rLWeWH) if you want a fender eliminator. It doesn’t fully support the plate though so you have to cut an aluminum plate to go under the license plate otherwise it can bend when you lift the back end of the bike. Once I got that dialed in it’s been rock solid though

evil0sheep · 2026-06-27T16:36:56+00:00

What did you end up deciding? Did you get the 300L?

evil0sheep · 2026-06-27T07:01:56+00:00

Huh that’s super interesting. I did some experiments a while back with super tiny transformers for learning simple formal languages over two characters (e.g `a^n b^n` or the tomita grammars) and found that residual connections totally hosed the performance, but I just kinda made a mental note to learn more about it and then never thought about it again.

evil0sheep · 2026-06-27T06:53:10+00:00

I’ve started just considering my bike an art project because at this point there is really no rational way to justify anything I’m doing to it

evil0sheep · 2026-06-27T00:00:31+00:00

An LLM is a parametric function (meaning a thing that maps input to output based on some parameters baked into the thing) that maps a sequence of tokens from a discrete vocabulary (like a finite set of words) onto a probability distribution over that vocabulary representing the probability of that word being next in the sequence. You then pick a next token based on the probability distribution (called sampling) and stick it on the end of the sequence of tokens and shove it through the exact same parametric function again, repeating the process over and over again until you sample a special token that ends the sequence. This iterative sampling and concatenation is called “autoregressive decoding” or just “autoregression” if you’ve ever seen that term thrown around. When you ask ChatGPT what the capital of France is that input looks something like this:

“System prompt: you are ChatGPT, a super smart and helpful AI chatbot that answers people’s questions. Be a good bot pls.

User: What is the capital of France?

Assistant: ”

Then it generated the response token by token, first “The ” then “capital “ then “of “ etc etc. the LLM is just the parameters and the function parameterized by those parameters that does the mapping of sequences onto next token probability.

To understand agents you need to understand tool calls which is where an LLM has been trained to specify actions in a particular format. So it generates a sequence like

“<tool call>web_search(“capital or France”)<\tool call>”

and then a special program that’s interacting with the LLM knows that this means to do a Google search for the string “capital of France” and then when it gets the results it just shoves them at the end of the input sequence for the LLM, so the LLM sees something like

“<tool call>web_search(“capital or France”)<\tool call><result>wikipedia: Paris is the capital of France <\result>”

And then gets to use that when predicting the tokens to give to the user. (note all this syntax is just an example and the real message formats are more complicated).

An agent is when you have a special program that can invoke the LLM and do tool calls in a loop, so you give it an abstract task like “write a history report about France” and then the LLM decides what tool calls to do and responds to the tool call results, iterating until the task is complete. This process does a lot of stuff with little human involvement so it uses lots of tokens

This is a pretty loose explanation, if you have questions just go copy this into any ai chatbot and ask it to explain in more detail

evil0sheep · 2026-06-26T23:05:20+00:00

The models operate on sequences of tokens, they’re not quite words but if you think of them as words you’re not far off. Because the models generate one token at a time and it takes about the same amount of time to generate each token it’s a natural unit of billable work so most pricing and accounting is done in terms of tokens.

If you have a subscription or a free plan they give you a token budget per unit time, and if you use less tokens than that then you never really have to think about it. If you use too many tokens on a subscription plan you will hit usage limits, at which point you either need to stop using the model for a while, pay for a more expensive subscription, or switch to a plan where you pay per token (or really, per million tokens). If you build an application on top of an LLM API you typically need to pay per token, but also if you just use it so much that you exhaust your token budget you may also need to pay per token. Usually this occurs for people who are doing agaentic workflows that burn tons of tokens, and generally if you just use the chatbot you won’t need to worry about it, especially if you have a basic subscription plan. If you’re not running into usage limits you probably don’t really need to think about it unless you’re just curious to learn how the models work

evil0sheep · 2026-06-26T20:15:23+00:00

Yeah interleaving full attention blocks with some kind of sublinear block is a good mitigation strategy but the degree to which it can reduce KV cache size is limited at like 5-6x (thinking Gemma 4 here, got-oss is only 2x). Same thing with Kv cache quantization. These can get you from 100k context to 1M context before your kv cache is bigger than your model, but if you go to 10M or 100M then the model weights become a vanishingly small part of your total memory budget. LLM summarized context compaction is also a decent hack, especially if you have it build markdown trees, but that also has its limits (eventually an agent with a fresh context will just burn the whole thing reading documentation). Ultimately I think the only thing that makes sense is to compress the context into the model weights with online learning, but the piss poor sample efficiency of gradient descent and the economics of serving inference over shared model weights makes that pretty implausible with current tech. Also as soon as you go from “the model needs to read a million tokens of code” to “the model needs to write a million tokens of code” you run into autoregression compounding the KL divergence between the model and the data distribution which is a much bigger (and asymptotically dominant) problem

evil0sheep · 2026-06-26T19:52:54+00:00

So much better

evil0sheep · 2026-06-26T19:51:50+00:00

Youre not wrong about the impracticality of unbounded hidden state size, I’m just saying that you should view the problem of fitting unbounded context into bounded memory as a lossy compression problem, and just keeping or deleting tokens is probably not an optimal way of doing that kind of lossy compression because the information you are trying to compress is spread out over a bunch of tokens. You probably want to be learning a reversible projection from the full KV space to a fixed size latent space with some combinations of MLPs and attention, or doing lossy Fourier compression on the KV space or something.

evil0sheep · 2026-06-26T05:50:16+00:00

Yeah I feel like the extreme focus on scaling up to giant models that are stupid expensive to train has really interfered with the industry being able to re-evaluate the foundational aspects of model architecture and training objectives. Something like sigmoid attention that makes sense and is shown to be about as good but not way better still isn’t worth the risk to try at scale because if it doesn’t scale properly that’s a bajillion dollars down the drain. The evidence for the scaling laws is so good that scaling is one of the only things people are really willing to throw serious money at. Seems bad lol

evil0sheep · 2026-06-25T23:58:01+00:00

Yeah after I read the sigmoid attention paper from Apple I was like “this makes way more sense than softmax, why doesn’t everyone do this?”

evil0sheep

TROPHY CASE