6 ms·
Show HN: Smart model routing directly in Claude, Codex and Cursor
We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: https://www.youtube.com/watch?v=isKhAyivtfM https://www.youtube.com/watch?v=isKhAyivtfM.
At Weave, we write most of our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for everything but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided to build a model router to handle this for us.
The Weave Router acts as an Anthropic/OpenAI endpoint specifically for coding agents. It looks at every inference request and intelligently (more on that in a sec) decides what model to send it to, handling all the translations required along the way. So it can use faster/cheaper models (e.g. DeepSeek v4, GLM 5.2, Kimi K2.6) when possible, and frontier models (Opus 4.8 & GPT 5.5 (& Fable whenever it's back)) when necessary.
How do we know what model to route to? We trained an RL model on tens of thousands (so far!) of agent traces. We reward the routing model when it selects an LLM that successfully completes the given task.
Here's an example: if you ask the router to plan a complex change, it will (probably) route that request to Opus 4.8. Subagents exploring the codebase to gather context will be routed to more suitable models (e.g. DeepSeek V4 Flash). Then when you have the plan ready to implement, it will be (most likely) be handed to a quicker model (e.g. GLM 5.2) to carry it out.
We've been using this internally for the last month or so. We've saved 40% on tokens vs. what we otherwise would have paid, with no noticeable differences in quality or velocity.
The router is source-available under Elastic License 2.0, so you can self-host it. Or if you prefer, you can also use our hosted version: weaverouter.com.
I'll be here to answer any questions you may have!
- stpedgwdgfhgdd 3mo agoThe thing I do not get with these routers is that you will have more cache misses (5min ttl). And if there is one thing i’ve learned; using the cache is crucial. How does this router translate to $$$ when developing?
- adchurch 3mo agoYou're right and that's why we built the router to be cache aware! Once it starts using one model, the threshold to switch to another model will be higher because the additional cost of the cache miss needs to be worth the cost savings or quality increase. This is the key thing that other routers we've seen miss: they're stateless so for a coding agent use case you end up spending more money due to all the cache misses.
- alansaber 3mo agoThat is interesting, sounds like in practice you only end up routing between 2 models
- adchurch 3mo agoI'd say that a typical main agent loop has 1-3 models (obviously very situationally dependent), but when you have subagents those can get routed independently since they have a fresh context window, so there are a lot more degrees of freedom there.
- echelon 3mo agoOr not routing at all. In practice you just pick one and stick with it until the API stops or you hit performance issues.
- adchurch 3mo agoThe choice on the first turn is super important for this reason! But if a user prompt sends the convo in a very different direction then often it does make sense to reroute at that point.
- mthoms 3mo agoThis is a key point. I don't know if you can still edit your submission, but I think this would be helpful to mention up front. I'm looking forward to testing this.
- deleted 3mo ago
- _pdp_ 3mo agoCool.. but I still don't get how this is going to save money. It seems to me that it might actually burn more money just because the whole system now seems to be coming from different LLMs. Also, small LLMs are prone to stop before completion, throw errors and produce loops. Is this factored in the design of the tool? I am not sure. edit: spellcheck
- adchurch 3mo agoIt saves money because some agent sessions can be entirely handled by a smaller model (also relevant: subagents use fresh context windows so a subagent with a simple task can be routed to a smaller model even if the main agent needs a frontier model). Totally right about small LLMs btw, that's why we trained this on real agent sessions where we forced it to use different models. If the routing model sees small models can't handle a certain type of task then they won't be assigned. (Also as a fallback we have some guardrails that will have a bigger model come in to "rescue" a smaller model if it gets stuck)
- arendtio 3mo agoWhat is the difference from Cursors 'auto' mode?
- adchurch 3mo agoFun fact: Cursor's "auto" mode is just Composer (or at least it was last time I checked). So it's different in the sense that it actually does route to more than 1 model
- arendtio 3mo agoHow did you check? Like looking at the results or at the actual implementation? I mean, I know that it mostly chooses Composer, but I wonder if it is hard-wired or if they have a logic that just selects Composer most of the time?
- gmziven 3mo ago[flagged]
- ai_slop_hater 3mo agoIsn't this more expensive than always using the same model, since, as I understand, by routing to different models you give up on cache?
- adchurch 3mo agoIf you statelessly route each new request: yes it does end up being more expensive! So our routing is cache-aware. It will have a much higher threshold to switch from one model to another if there's already some cache for the first model. Experimentally this solves the problem (like I said we've saved 40% ourselves vs. what we would have otherwise paid).
- debarshri 3mo agoIt is funny. We are building something similar.
- adchurch 3mo agoOh cool, feel free to reach out to me at andrew@workweave.ai if you ever want to share notes! We've learned a lot in the process of building this so far :)
- spqw 3mo agoThis + making sure common requests are saved as reusable skills and scripts would probably save a large part of my token usage As prices increase we will see more of these tools to optimise and make the best use of token budget
- adchurch 3mo ago100%, from what we've seen, for a lot of big companies that 1. don't have subsidized usage and 2. are pushing AI adoption hard, figuring out token costs is P0 or P1 for their eng leadership
- SoftTalker 3mo agoSo you're saying that since adopting AI/LLM tech many companies have their top engineering priority being optimizing the costs of that rather than ... addressing actual business needs?
- adchurch 3mo agoI guess delivering business value is always #1, I just meant it's the biggest problem they're trying to solve. Here's a recent example that was public: https://fortune.com/2026/05/26/uber-coo-ai-spending-tokens-claude-code/ https://fortune.com/2026/05/26/uber-coo-ai-spending-tokens-c...
- g00k 3mo agoMan, I'm not so sure if I'd use something like this because the way I prompt already changes based upon what model I am using. I'm not convinced it would route to the right model based on my diction or whatever.
- alansaber 3mo agoYep this was always the reason to avoid "auto" mode in cursor.
- adchurch 3mo agoYeah that's a really interesting point, tbh I think the more relevant variable here is the harness you're using rather than the specific model? i.e. GPT 5.5 in the Claude harness behaves a lot more like Claude than Codex if that makes sense. Hard to quantify this ofc but that's what I've felt vibes wise from using this for the last month.
- devmor 3mo agoI have the same general feeling as well. Like you, I can’t prove it’s not just personal feeling - but e.x. Opus via Copilot CLI behaves entirely different than Opus via Claude Code, which behaves differently than Opus via OpenCode or Pi.
- ValentineC 3mo agoI have the same feeling. I've been trying Claude Code directly ever since Copilot nerfed their request-based system, and Opus just seems to perform "better" in Claude Code. It's also possible that it's the 1m context versus the 200k context (Copilot's limit) doing some of the work here.
- stronglikedan 3mo ago> Man, I'm not so sure if I'd use something like this because the way I prompt already changes based upon what model I am using. Perhaps you're just not the best use case. It may work better when Average Joe is the one prompting.
- emilio_srg2 3mo agobut this means you work with API pricing rather than subscription pricing. Isn’t it better to use claude or codex CLI etc directly in terms of cost?
- adchurch 3mo agoIf you have a Claude/Codex subscription then we use that (and account for the subsidized price accordingly when making routing decisions) instead of API billing. So you get the best of both worlds: subsidized usage for frontier models + save by using open/smaller models when it's genuinely better. In practice, lots of ppl are using this to make their Claude sub limits go further!
- emilio_srg2 3mo agoI see but didn’t they severely limited the usage allowed with `claude -p`
- adchurch 3mo agoBut we're not routing via `claude -p`, if you have sub usage available + it's the right choice to route to a Claude model, then the router is approximately a transparent passthrough. So it gets billed like normal `claude` usage rather than `claude -p`.
- alansaber 3mo ago"We reward the routing model when it selects an LLM that achieves the task successfully" sounds pretty oversimplified
- adchurch 3mo agoIndeed it is :) I skipped over talking about all the RL machinery, network design, reward function design, state representations, etc. because really the intuition is that we tell the model when it accomplishes its goal, and then it learns over time how to get better at making the right decisions in order to accomplish its goal. Happy to talk about this in some more depth if there's anything specific you're curious about!
- gautam_io 3mo agoThis is cool! Will this use my Claude Pro/Max subscription? Or will it always use the API billing "pay as you go"?
- adchurch 3mo agoYep it uses the Claude sub if possible and falls back to API billing only if you don't have a Claude sub or it's out of usage! Same deal for Codex
- slopinthebag 3mo ago> At Weave, we write ~all our code with AI This is probably not a very effective way of marketing imo. At least, it turns me completely off.
- adchurch 3mo agoFair enough, not meant to be marketing just a statement of fact. Would have turned me off too 18 months ago but times change...
- suyash 3mo agoI would rather just use OpenCode - leverage AI models, even can host locally or paid ones with ease.
- adchurch 3mo agoWe integrate with OpenCode too! OpenCode provides the harness, then the router selects the right model for the task. We haven't yet set up local model routing though, that's really interesting - have you had any success using local models for coding tasks? Tbh I haven't heard many success stories from using local models yet
- k9294 3mo agoWhat about request caching? If you swap to a cheaper model mid execution it might cost more that to make multiple requests to the already cached provider?
- adchurch 3mo agoYep 100%, mentioned this in another thread (https://news.ycombinator.com/item?id=48689448 https://news.ycombinator.com/item?id=48689448) but tl;dr we build the router to be cache aware
- mkagenius 3mo agoWe have created Murmur[1] which kind of works with your existing subscription (having API key is not mandatory). You can just tag @copilot @codex from claude code to delegate work to them. (it can also do it on its own too btw) 1. https://github.com/instavm/murmur https://github.com/instavm/murmur - Murmur
- adchurch 3mo agoVery interesting - curious how you've used it yourself so far? I can imagine one use case would be having e.g. GPT 5.5 review Opus 4.8's work?
- mkagenius 3mo agoUseful in splitting a big task - some parts are easy so give it to say Gemini. Some are harder so give it to gpt 5.5 and so on. Also the throughput kind of increases since providers are different.
- iluvcommunism 3mo agoThis is basically what I need, a router. I’m tired of changing intelligence & speed levels manually.
- adchurch 3mo agoNice, let me know any feedback you have from trying it out!
- peterbell_nyc 3mo agoI auto tune my prompts to a locked model version based on production data used as evals with holdback data. I think the use case for this would be one off interactive prompts? For now I just run those all against an Opus 4.8 MAX and I'm sure I could downtune, although for interactive my opening prompt isn't always reflective of my overall goals for the multi turn session. I'm just trying to figure out why on the fly routing would beat testing and tuning and locking models and versions for each class of call, with evals and auto tunes running to explore more possible models for commonly run classes of prompt over time . . .
- adchurch 3mo ago[dead]
- gopher_space 3mo ago"Based on your subscription tier and local hardware here's a list of models that fit and process definitions your biggest brain will comfortably handle." I guess that sounds a lot like moving your evals and auto tunes to a third-party, but I don't have the time, budget, or inclination to create a system like this out of whole cloth and then keep it relevant. I could see something that provides on-the-fly routing information being useful, but actual decision-making is too dependent on context.
- bijowo1676 3mo agoHow come data privacy and confidentiality is not an issue with services like these? Do people voluntarily use these proxies/routers, knowing their prompts, outputs and code will be seen by other people ? I get it might be ok for personal projects, but for anything that makes money and is a part of business... this must be big no-no ?
- victorbjorklund 3mo agoIt is a router that runs locally.
- adchurch 3mo agoIt's a real concern! We take this stuff super seriously (https://trust.mycroft.io/weave https://trust.mycroft.io/weave) and tbh most of our customers opt for the hosted version because it's much simpler on their end + they're already trusting us with a bunch of sensitive data. But of course since the source is available you can also run it locally or self host
- jakozaur 3mo agoIt's rather hard to do at the proxy level with agentic coding, such as Claude Code or similar. These are long-chained sessions of tool use that heavily rely on prompt caching. Changing mid-flight is costly. It looks like much more context is required to decide on the best model (e.g., summarizing logs might use a cheap model, whereas you likely want Opus/Mythos/GPT 5.6 to debug multithreading logic). In an agentic system, a decision about the model may be embedded in the decision to orchestrate the model.
- adchurch 3mo agoYep cache awareness is super important, mentioned this in another thread here: (https://news.ycombinator.com/item?id=48689448 https://news.ycombinator.com/item?id=48689448) But intuitively I think it makes sense that a model can learn what model to route things to if it has all the relevant info, and experimentally it works pretty well in our experience
- randomuser558 3mo ago[flagged]
- GodelNumbering 3mo agoThis would not work in the way that shows any significant genuine benefit IMO. Caching and optimum routing of a single request are at odds with each other. Higher the distinct model count in a conversation, more cache misses you accept. Based on what OP said elsewhere in the discussion "threshold to switch to another model will be higher" means that essentially you reduce the workflow into two models at most. The two model primitive, one planner and one executor, is already sufficient for such a use case. For lower than 2 models, it's just a simple single model cache-preserving conversation which arguably doesn't need another layer. For larger than 2 models, you are likely paying a large aggregate cache penalty that negates most of the gains
- adchurch 3mo agoWhen we started building this we did it as an experiment and we thought the same thing might be true (cache misses would make the whole thing pointless). This turned out not to be true! I think there are 3 reasons intuitively: 1. Small models can carry out a good number of requests e2e 2. Small model for part of a request + cache miss < big model for entire request in many cases 3. Subagents For our own usage we've saved 40% so far (that is of course including costs of uncached requests when switching models)
- GodelNumbering 3mo agoThis assumes a perfect problem routing though. Determining the complexity class of an arbitrary problem is generally undecidable or extremely hard (Rice's theorem implication). So, in real use cases, you need to amortize all cases where the problem got routed to the wrong model and recovery had to be performed) For example, if my task was "refactor this component to decouple all messy nesting", the problem router can't possibly know what is being referred to. This works for clear cut and dry problems but not for ambiguous problems. Most of the real world problems carry a lot of ambiguity.
- gopher_space 3mo agoIn my mind one of the problems is that I'm using the term 'router' to describe something more akin to a train schedule. A list of abilities, cost, and timeframe to be used by a model capable of deconstructing its own process.
- reliablereason 3mo agoWont this kill the kv cache? Also i am pretty sure neither open ai or anthropic leets you seed the agents own tokens.
- adchurch 3mo agoVery important consideration, addressed it in another thread (https://news.ycombinator.com/item?id=48689448 https://news.ycombinator.com/item?id=48689448). tl;dr we built this to be cache aware for exactly this reason
- treexs 3mo agoAhh been working on the same thing for a while now but haven't launched yet
- gopher_space 3mo agoA lot of people are working on the same thing because nobody's come up with a definition of "thing" that people agree on yet. Your project would be valuable just for adding another point of view to the conversaion.
- adchurch 3mo agoCool, interested to see your approach when you do launch! I think it's a really interesting problem
- jmalicki 3mo ago> with no noticeable differences in quality or velocity. Have you done any A/B tests on this with evidence? (That's one thing I'd be very interested to see for claims like this - I'm not necessarily doubting you, it just seems like it could be useful to understand claims of quality/efficiency)
- adchurch 3mo agoGreat question! Our main product quantifies engineering productivity & quality so I think we're uniquely qualified to answer this - our velocity has only gone up and our quality (bugs introduced, code turnover) has not budged per our own analysis.
- jmalicki 3mo ago> our velocity has only gone up That is super curious - using more low quality cheaper models increased your velocity? My prior would have been slightly reduced velocity but massive reduction in token costs made it worthwhile. Is that due to the faster inference time?
- jarodrh 3mo ago[flagged]
- nikcub 3mo agoI'm glad there are more attempts at solving model routing, as costs (at API rates) has really become an issue. Some feedback: 1. Reiterate the cache issue from other comments already here. there is a lot of optimisation in harnesses around caching and a proxy model blows that up 2. Coding agents are model aware - they already route code discovery to mini / flash models, planning to heavy models, workflow design to ultra, implementation to mid / high etc. They know when they're exploring, planning, implementing, reviewing etc. and which model class to select and when it fails. With a proxy you're breaking this control loop and feedback. It doesn't know, for ex. that it just attempted with deepseek v4 and it failed, lets try Opus? 3. How are you going to RL improvements and prevent the router becoming stale? You only have access to your own internal prompts and ~thousands of samples. This is RL'd on one orgs codebase. There are going to be a lot of prompts you haven't seen before and have no insight to on how to route correctly, and you have no insight into users HF to improve your own model. Orgs aren't going to share their traces with you, so you need other sources to train on and improve There are also new model releases every week that you need to keep up with - whats the story going to be here 4. Publish evals by running terminalbench / deepswe bench. Show us the performance / cost / time chart vs the other agent and model sets. If you can show gains there, you have a very simple value prop to sell where you can charge for a % of the saved costs
- adchurch 3mo agoReally appreciate the thoughtful feedback! 1. Agree it's important, fwiw the proxy model doesn't blow this up though - only incurs a 1 time cost when switching models and we're aware of that when making routing decisions 2. The agents are model aware yes but they are not incentivized to optimize too heavily here (in particular they don't use OS models even when they would be better). I think that's where this router comes in and brings genuine improvement. 3. Two parts here: 1 is continuing to grow our golden dataset over time, 2 is using reward signals from production traffic (on a per-customer basis or, if allowed, across all users) 4. Yes we have these internally, great callout that we should publish! Will do + will link from the repo soon. (Fwiw I think these benchmarks are useful but don't fully capture vibes - you should try it out yourself for that!)
- Reuben_Santoso 3mo agothis is impressive. genuinely better than most people appraoches with using LLM as another judge to help route. which just uses more tokens than saves
- adchurch 3mo agoAppreciate the kind words! Lmk if you have any feedback on it from using!
- lubujackson 3mo agoI notice Cursor already does something similar. Even if I have Opus 4.8 selected, it will trigger subagents using Composer 2.5. I like using Auto personally because it is pretty effective and deeply discounted, but at work I YOLO Opus high. I imagine a solution like this will eventually be an enterprise-forced solution because there is no reason right now for individual developers to be selective about model pricing. Even more important is non-tech users who do stuff through MCPs like "give me a full overview of all analytics" and let it chug for half an hour.
- adchurch 3mo agoOh interesting, didn't know Cursor did that! Totally makes sense though, routing subagents is def the easiest win, no need to have any cache awareness.
- kumiko_studio 3mo ago[dead]
- asdev 3mo agoLarge model companies will likely build this and make it better. It'll also be cheaper overall since they'll be subsidizing token cost if you use them directly vs third party router paying API costs
- adchurch 3mo agoI would argue they do not have a good incentive to build this and make it better. Why would Anthropic route Claude Code traffic to DeepSeek (at 20% of the cost)?
- zcw100 3mo agoCan't really win can ya? Scarce? They're driving up prices! Plentiful? It's all a big bubble!
- pradeep1177 3mo agoSo, how are you handling read/write caching? I mean, if I keep routing the next prompt based on the task weights? How about if I'm sending every 5th query to opus, which do expensive write cache?
- adchurch 3mo agoWe consider the cost of missing the cache when making each routing decision after the initial one. Discussed in a bit more depth here: https://news.ycombinator.com/item?id=48689448 https://news.ycombinator.com/item?id=48689448
- matt_d 3mo agoLooks interesting! Out of curiosity, how does it compare with vLLM Semantic Router? For reference: https://vllm-semantic-router.com/ https://vllm-semantic-router.com/ https://github.com/vllm-project/semantic-router https://github.com/vllm-project/semantic-router vLLM Semantic Router: Signal Driven Decision Routing for Mixture-of-Modality Models, https://arxiv.org/abs/2603.04444 https://arxiv.org/abs/2603.04444 https://github.com/vllm-project/semantic-router https://github.com/vllm-project/semantic-router For instance, does it offer similar algorithms: - vllm-sr/auto: efficient, fast, balanced routing, similar in spirit to Fugu // Sakana Fugu — Multi-Agent System as a Model: https://sakana.ai/fugu/ https://sakana.ai/fugu/ - vllm-sr/fusion: panel-style multi-model reasoning and synthesis. - vllm-sr/flow: router-native workflow orchestration - vllm-sr/remom: multi-round reasoning over one or multiple models. FWIW, it does look good on https://routeworks.github.io/leaderboard https://routeworks.github.io/leaderboard Ref. RouterArena: An Open Platform for Comprehensive Comparison of LLM Routers, https://arxiv.org/abs/2510.00202 https://arxiv.org/abs/2510.00202, https://github.com/RouteWorks/RouterArena https://github.com/RouteWorks/RouterArena
- adchurch 3mo agoGood questions. From what I can tell, vLLM semantic router is more optimized for one-off prompt/response workflows rather than agentic coding (I don't think it's cache aware). As another commenter (https://news.ycombinator.com/item?id=48689994 https://news.ycombinator.com/item?id=48689994) pointed out, for one-off requests, I think it makes more sense to lock to one model whose behavior you understand very well. For dynamic requests like the ones going to a coding agent I think dynamic routing makes more sense but it does need to be cache aware.
- matt_d 3mo ago[flagged]
- hmokiguess 3mo agoI tried Sakana Fugu, boy is it hungry ... it blows up tokens like nothing I have ever seen. Not that impressed with the results I got from it however if I'm being honest. Now I'm bought into their buy 1 get 2nd month free so will keep trying it but may cancel after.
- notatoad 3mo agoIs this talking to claude code, or to claude api (and paying api rates)? programatically routing requests through claude code sounds like a good way to get banned, just like the opencode and openclaw users.
- adchurch 3mo agoIf you have a Claude sub with subsidized usage we use that. If not you pay API prices.
- ValentineC 3mo agoIs that because you start by running it inside Claude Code? I don't see how Claude would allow any other harness to call them for their subscription, after all that OpenClaw hullabaloo.
- adchurch 3mo agoYep exactly
- thandv 3mo agoThis might be a stupid question, but can a extra added local llm help with the caching problem?
- adchurch 3mo agoWe haven't experimented with routing to local LLMs much. Technically they benefit from the cache too although it's more a question of latency than cost. But tbh I haven't seen great results in the wild from working with local LLMs for coding - curious if you've had any success with them?
- thandv 3mo agoI generally used them for token saving purposes, just using them for repetitive tasks, gated and supervised by claude. So its planned and verified by better models, but implementation falls on local ones. It has been pretty effective for me, as long as I spend a bit more initially on splitting complex tasks further down
- barmazoid 3mo ago[flagged]
- nativeit 3mo agoThis would have been neat back when I could afford enough tokens to even set it up properly. Now I’ve had to increase my GH Copilot subscription just to cover the bare minimum updates to a few websites every month, and I no longer do any test driving, or even recreational coding projects. I don’t have hundreds of dollars a month to plow into these products, so I’m rationing use, looking for better local options, and being much more discerning about where these tools actually save time. Precarious time to be alive…
- newaccountman2 3mo agotry OpenCode
- ValentineC 3mo ago> Now I’ve had to increase my GH Copilot subscription Maybe you should move away from a subscription that started charging by the token instead of by the request?
- dools 3mo agoI've been building a reasonably complicated project over the past week using deepseek v4 pro almost exclusively (a couple of k2.7 and 1 session with gpt5.5 to re-assess some architectural questions). Deepseek is super capable though if you're a coder. I don't even write "code" but I can tell when it's doing something dumb and tell it how to do it better, but other than that I'm not micro managing it or using it "just for auto complete" or whatever. And it is SO fucking cheap.
- adchurch 3mo agoYes the open source models are very good, that’s a big part of what makes this router save so much money in practice! There definitely are some things they still don’t handle well though where you do want a frontier model
- jpease 3mo agoIs this noticeably different than having your implementation planning phase break a larger task into sub-tasks, and recording the ideal model to use based on scope as part of the task definition?
- adchurch 3mo agoYes because it's a model explicitly trained to make model selections! Opus probably doesn't have a great idea of when to send a task to DeepSeek vs. to Sonnet, for example.
- james-mxtech 3mo ago[dead]
- jawon 3mo agoI got Opus to knock out an MCP server that implements subagents running in pi and tell Opus to send work to DeepSeek. Or I tell it to ask GPT-5.5 for critiques. It's manual but saves a lot of tokens.
- elgertam 3mo agoI ran into a problem at work recently: we are given access to a bunch of models up to a full Claude Opus 4.8, but a monthly budget of 100k tokens. We are also given access to Gemini 3.5 Flash & 3.1 Pro with a daily budget of 50M tokens, but no tool calling. I'd love to hook Claude Code (or Pi) into the Gemini model, but the lack of tool-calling makes it quite difficult. I've been planning out how an intelligent router might be able to use a token-efficient tool-calling model (including a small local open-weights model) to handle the basic tools like reading from the file system or interfacing with MCP servers such that context is gathered, but then send the built up context to the Gemini model where I have a nearly unlimited (for my use cases) token budget. Could your router handle this?
- thombles 3mo agoI’m curious how a workplace ends up with a model policy like this. It seems like you’d spend more time trying to work out how to use a tiny number of Opus tokens than doing it yourself.
- elgertam 3mo agoLet's just say this organization is very, very large and doesn't necessarily have the budget for everyone to have all of the tokens.
- Jaxkr 3mo agoMonthly budget of 100k Opus tokens? So $2.50 worth?
- adchurch 3mo agoYes we can route to Gemini models too and we handle all the translation complexity there!
- yiyingzhang 3mo agoCurious what's the typical switching frequency in your experiments and experience. How do you control the tradeoff of cache matching and model efficiency?
- forgeshiptoday 3mo agoJust curious how the router decides on which model to use. When I use Claude Code, I often ask Claude Code to decide itself if it should spawn a sub-agent to downgrade or upgrade the model. Claude Code is smart to know how much context and cache it has and will decide if it should use sub-agent with a lesser model (sometimes it costs more to re-fetch tokens with a Sonnet sub-agent if the parent agent already has the context).
- adchurch 3mo agoWe trained a model to select which LLM to call at any given turn, based on lots of agent traces
- threerouter 3mo ago[dead]
- Lerc 3mo agoThere are so many of these projects to wrangle AIs I think we might need an AI to go through, analysing each and amalgamating the good bits. It makes me think of MakeFiles. Make is sufficiently bad that everyone who has used it has considered writing a better way to do it. A good percentage of those people have done so. On the other hand, make is also not so sufficiently bad that it cannot do its job. The choice becomes picking the thing that everyone has or one of the many many alternatives that proclaim their strengths and leave their weaknesses lurking to bite when they are least expected. No single replacement to make dominates, and make lives on. I wonder if AI management is on a similar path.
- guripong 3mo ago[dead]
- pradeep1177 3mo agoI generally believe the proxy route is best to understand any harness. I been building some thing similar.
- implexa_founder 3mo agoI see a great tension in the market today. On one hand you want agents to work reliably and that needs a lot of harness, computer use, model routine, tasks running longer etc. And on other hand you simply want to reduce your dependencies and costs. Agent building is very nascent and all the frontier companies are trying to build the best harnesses possible. As basic prompting, researching, coding gets mature, more and more of such tasks will be optimal for model routing open source etc etc but there is a chance that by that time frontier models again make costs and routing, low and effortless. Basically I believe everyone has started jumping to the. -- REAL PROBLEM IS COST v. REAL PROBLEM IS EFFICIENT, RELIABLE AGENTS/WORKFLOWS. It's going to be very interesting to see how this plays out.
- latchkey 3mo agoWhat I want is a router that can also provision compute on demand and shut it down when it is done.
- Bishop81 3mo ago[flagged]
- Bnjoroge 3mo agoLooks cool, but I couldnt find any benchmarks for how well this does. Any links?
- nawi 3mo ago[dead]
- virangjhaveri 3mo agoDo you reward the RL model based on the token consumption when multiple LLMs complete the task ?
- adchurch 3mo agoEffectively yes (based on cost though, not raw token count)
- TaylorGood 3mo agoYour employees need to stop baiting on X.. "I'll hire cracked devs who score above a certain number, just scan your GitHub, get a score, send me a screenshot" meanwhile getting the actual score is a premium feature. This is one of the most grotesque metric and funnels for data input I've seen. And, to delete your Weave account? Email them, they don't respond.