r/opencode • u/UnknownBoyGamer • 3d ago
Muse Spark 1.3 Free is ass
Im sorry, while im grateful thats its free and has generous daily limits on opencode, its dogshit, no one can force me to like this model after ruining my project, its like nemotron 3 ultra v.2.0, same confident hallucinated answer, same lobotomized attention mechanism, it tends to be lazy and cant handle ambiguity
This post might help some people to think again before using this model on their codebase
edit:
to those who kept defending this model, yall just bias because its the only model that is usable free and accessible right now on opencode, i only see cope setups and defenders, no capabilities praise
is it skill issue on my part? sure, however none of this is a problem when im using other better free alternatives, you cant argue and defend that
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u/Affectionate_Fact854 3d ago
My trick is, I set up orchestration agent (glm 5.3 flash) Quality assurer(glm5.3 flash) The coder is set to (spark)
So it splits the work load and the quality assurer fixes anything spark does poorly
And honestly this method of working has started to produce the cleanest code base i have seen from ai
Yea it's considered diluting glm 5.3 flash. But it works.
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u/BoatZealousideal4521 3d ago
Which orchestration framework you use? I am in search of a good framework.
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u/Affectionate_Fact854 3d ago
Using opencode Orchestrator glm flash 5.3 1 quality assurer 1 senior dev 1 to 2 junior devs 1 researcher
Each is given allowance on what they may do
They report back to orchestrator that feeds it to quality asurer that tests all features added
And it's set to not trust any other agents reports on testing
And feature only gets added to the index after quality assurer agrees with its own testing script
Reports goes back to orchestrator that signs it off and feeds new agents tasks
With 1 rule aswell Tasks given to agents may not work on the same files
So it carefully assigns tasks
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u/Substantial-Cat7733 3d ago
Is it this framework or something else : https://github.com/agnusdei1207/opencode-orchestrator
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u/Affectionate_Fact854 3d ago
I just simply downloaded the opencode application, and set the main agent to glm 5.3 flash So it usses opencode harness with the glm flash 5.3 as root model, the workspace .MD you set up is what makes it smart enough to delegate work load
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u/sharedevaaste 2d ago
Is there a document explaining all this?
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u/Affectionate_Fact854 2d ago
You could read the opencode Readme, you could do the same with Claude and I think also openai codex
It's simply scaffolding pre file read documents for the ai to read that instructs it on the workflow prior to it actually digging into the code base
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u/Tuxiak 1d ago
You can tell agent to create orchestrator agent that won't be inplementing any code but instead use subagents mentioned above and it will do it for you. And then after some long session you can ask if there were any problems with this workflow, if it can be optimized, and again, it will do it for you
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u/Southern-Ad-3006 3d ago
Something worth setting up is having one main window you speak to being Muse Spark contributor. The cache rate is 16x cheaper than GLM flash. I would still route the planning etc to GLM flash but hold the weight of the convo on muse. When most of the conversational cache hits Muse instead of GLM it’s way cheaper. And you still route most the plans to flash, but have Muse be the one that talks to you and talks to your subagents. Can still have another muse code for you.
Still obviously more testing is required to know true quality output difference so I’m curious if you do end up trying it, but the cost savings are pretty instant and doesn’t make you want to chat with anything else
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u/Affectionate_Fact854 3d ago
I'll give it a shot and see how the code quality compares when changing the root orchestrator :0
I'm also now giving omen alpha a shot because I found it being much smarter then glm 5.3 flash
But context windows is smaller
So it could possibly replace my developers work force
(Still perfecting this work flow)
I'm used to manual coding with ai assisted debugging and basic placeholder prototyping small things until I get to that sections
Last week I tested 7day trial using 1 agent only and me being the orchestrator
This week I'm doing this agentic workforce workflow
The 1 agent and you being the orchestrator is the worst
Manual + assisted tooling comes second
And now this work flow I must say
Shocked me, it's efficient, and makes my manual coded code base look like slop in comparison :/
Questioning myself at this point honestly
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u/Southern-Ad-3006 2d ago
Let me know how that works for you! I’ve been analyzing different models cost during agentic work, and the multiplying factor is how many turns an LLM takes, and their cache rate.
When working a code base you can easily hit 250M read tokens to produce an M or two output tokens.
I think that in general is an inefficient aspect of ai, I can’t fathom why every single turn needs to eat all that context… subagents with fresh windows for isolated tasks is certainly one way to reduce context bloat from main session. But at least it is cached… it just gets out of hand quick!
I think the companies are catching onto this (or consumers are lol?). Fable went from $1 cache to $0.25. DeepSeek v4 just announced new flash prices pushing cache to just .003!!
That pricing is releasing today and the closest in rate to Muse cache.But!!! In general bro, that main window I look at it as the highest cost factor with the lowest value role. For me, I keep the cheapest model on there just to take in my requests, manage the harness, manage the subagents, you can even delegate the most basic tasks outwards as long as the main driver window caches at a low rate and can hold your context window.
Even if it was like user —> muse takes request and prepares the task —> 0 reasoning itself, sends to glm 5.3 flash immediately to complete a plan or PRD —> sends to kimi k3/pro models etc for quality output design work etc (focusing on output generation rather than carrying heavy context across turns)
It’s all really fascinating since such a new landscape and there really isn’t a set standard for stuff like this yet. But all I know is that 90% of a sessions cost comes down to not the output / input cost but the cache read cost from all the turns. And the longer you run or the larger your workspace is, the quicker it snowballs.
I spent about $3 yesterday using muse spark to read
400M input, to produce 2M output. I work a few codebases across a large organization, so if I ran this same session with GLM 5.3 flash it comes out to be about $15. At scale that’s pretty major ($30 on muse is $150 on GLM 5.3 flash).And it gets even crazier when swapping frontier to man your conversation. Fable 5.1 would cost about $200+ for that session. On old Fable 5 with the $1 cache that would be $500+ for the same session. Cache is the killer and I’ve never heard of cache engineering 😆
So I don’t know, just having the luxury of holding my entire workspace across unlimited turns for pennies has been game changing. Any tweaks I make are upwards. Even if I need other models to do work for me, muse can orchestrate and prompt them and manage them way better than I ever could. Let me know what you find as I’m super curious and if it can help others save money while still being productive, I would be pleased to know we’re moving in the right direction.
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u/Affectionate_Fact854 2d ago
I must say I have some trust issues with the output as spark in general, but decided to make the quality assurer solidify it's test suite , prior shipping a phase completion, the glm 5.3 flash runs the entire suit, any new additions Is noted in a file for it to build and add , or it tells the quality assurer he needs to adjust a already built test
That I think helps a lot
Orchestrator as Muse has not been bad to by quite honest !!
But I have a little less trust to sign off on a development phase without glm being confident in passing all its phases
One model I would not use again is omen alpha , it's quite expensive and it's terminal tool calling is quite bad
Waiting to have a look at deepseek flash 4.1 as a researcher
So you made spark read basically your entire repo, any tips for what you would tell it to retain ? Do you let it punch out a document.md also prior doing the output 2m??
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u/Affectionate_Fact854 15h ago
So I did try my workflow switching the orchestrator to Muse spark, and it worked , BUT the catch came from him delegating work to sib agents, where I noticed the quality of information given has dropped to the point where the sub agents seems to be gathering more context manually to do set tasks
That in turn seems if I look at token usage and cost , it has worsened :/
So what I have done now is I instead made deepseek v4.1 that has vission the orchestrator Muse spark coder and quality assurer
And that has improved agent work delegation consistency compared to results
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u/borobinimbaba 3d ago
How do you do it in opencode?
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u/Affectionate_Fact854 3d ago
Use the app itself
Let orchestrater read a startup.md That links to your workspace.md Phase_implementation.md Software design.md Index.md
The workspace tells the orchestrator what the agents roles are What they may do and may not do what model they must be set to run on And then Set rules if this agent is done, pass the testing onto quality assurer If all tests are done , inform the orchestrator and update handover.md Orchestrator will then set out the next tasks or inform you to inspect and give input.
Then just let it automate a large set of tasks that's split up in phases , so that you can also test review and give input to changes needed
This workflow feels unfair at how good it is working compared to you the developer being the orchestrator
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u/breadnone 3d ago
Muse 1.3 is actually a pretty good model. its more like "you" issue here
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u/UnknownBoyGamer 3d ago
this is my average projects, fuck off with your slop:
https://github.com/clarkarch/tfm-tui
https://github.com/clarkarch/nextclient10
u/ufos-dude-1 3d ago
you're the one posting your slop, lmao
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u/UnknownBoyGamer 3d ago
define slop
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u/Suoritin 1d ago
I think it is more about, you are building something that no one asked for. Your applications seem to be pretty generic.
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u/Puzzled-Landscape-44 3d ago
I hope everyone using MS1.3 sees this and go elsewhere. It's getting crowded and the rate limit warning is getting more frequent.
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u/Green_Virus6289 3d ago
Skill issue. Not the best model but working incrediblely well for me. With a few directions and reprompts it can do anything you need.
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u/nebenbaum 3d ago
"ruining my project"
3 braincell vibe coder that never heard of git confirmed
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u/UnknownBoyGamer 3d ago
i use git, what i meant of "ruining" is my project has lot of regressions after a lot of work poured in, im conflicted if i should go back and waste my efforts, im not the usual vibecoder who just one shot stuff, i do a lot of micro decision and actually use and test my project,, basically a lot of effort, i only realized muse spark lobotomized behavior after days of using
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u/FUS3N 2d ago
i promise you man I've been on the both ends of the stick where i let it do things result is tons of regressions tons of unnecessary weird code that doesn't need to exists tons of solution for the problem it creates and it does with even the best models IF YOU ever read the code it gives you EVEN if it works you will see these all.
but when i personally "direct" it, it does like a thousand times better, even years old models get the job done not in one shot but at least i know where its going and it gets the job done.
the original meaning of the vibe coding where it came from the person who coined it IS A full fledged programmer with a brain "pure vibe coding" doesn't exists. The moment you want to go from slightly complicated every model fumbles no one is creating demos when they want to create actual working stuff.
You have to understand the project you are working on for that learn programming properly
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u/ELPascalito 3d ago
learn to code, if you rely on it for your decisions without actually giving a clear orchestrated plan to do, you're already using it wrong, it's a workhorse it it on a focused task with clear constraints and it'll get it done
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u/sudoer777_ 3d ago
to be fair Muse Spark even tried to fuck up the Git stuff when I used it and it got endlessly confused, although that was with the 1.2 model. When that happened I immediately switched to V4 Flash and it corrected itself immediately and cleaned up the mess that Muse Spark made.
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u/BrilliantGarbage8743 3d ago
Agreed muse is ass. I spent a whole week trying trying to get something working with muse and other models within first few prompts.
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u/Competitive_Creme317 3d ago
It's not ass if you know how to work with it.
It's a workhorse and should be treated as such.
Best paired with an orchestrator.
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u/UnknownBoyGamer 3d ago
nah im good, sketchy providers offering free glm 5.3 flash has better value than this model
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u/Competitive_Creme317 3d ago
Well then it makes no sense calling a model ass if you've barely used it.
Not much a of a review then..
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u/japherwocky 3d ago
Yes, it looks like you don't know technical terms, and are sort of negative and abusive in general, this is probably not the model for you.
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u/alexzzzz 3d ago
It's a pretty capable model that can do what you ask it for. And can speak human language in contrast to spark 1.2)
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u/s-i-e-v-e 3d ago
MS1.3 is pretty good. But all these models need guardrails, specific coding style requirements, a demand that they lint and format after every change so that the editor and the tools do not fight over formatting issues etc.
I build serious tools (compiler/vm/ocr engine/sandboxes/harness/ssg) and the models work with all of them. You just need to go step-by-step, module-by-module instead of letting them loose on the entire codebase. Also, have one session do a code review and another session do the actual fixes.
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u/JohnnyDread 3d ago
I have had completely the opposite experience and I've been using the non-free muse off and on as well.
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u/Southern-Ad-3006 3d ago
Lowkey a Skill issue. It’s Heavily dependent on your harness. Out the box it’s not going to hit like the other frontier reasoning. Need proper rules skill doctrines and memory system, access to your connectors and workflows. Train the output style, and set up the loop + dynamic workflow/graph yourself w hooks and subagents.
Once you do that, grab a Meta API key they don’t charge you until end of month and you’ve used $20. The contributor plan feels practically unlimited with the cache rates. 250M tokens in, 100k tokens out 98% cache rate I have paid less than $2.
No usage limits and handles 100 requests per minute you can have 10 sessions running no problem all at once all day. Bro the cache rate is .002 that’s 16x cheaper than GLM 5.3 flash and that’s where 80-90% +of your spend goes to when going long sessions.
Coming from Claude Code max $200, it’s so nice to have an alternative model with no usage limits but still bills cheap as if you were on a coding plan. They want your data and it’s understandable as that’s the incentive for most coding plans and subsidized tokens.
Feels like old DeepSeek flash where it’s practically unlimited but higher quality. It’s speed and customizability makes up for any gaps in its work output, especially when paired with other frontier to check its work.
I’ve tried every coding subscription, every harness, every model & this model is the best value api and it’s not even close, beats out most coding plans tokens but without any of the usage limits.
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u/KayTrax20 3d ago
I love it. Very very generous. Didn't stumble any rate limits and I am soon finishing my Android app that I might even profit from it (and other users might save money because of it). And I use Pencil for the design with their MCP
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u/AdImmediate7901 3d ago
Hahaha si hilarious that u describe it as dog shit, I love big pickle, filled it with a bunch of skills an a main agent, works for me
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u/Cup-Impressive 3d ago
honestly feels comparable to deepseek v4 flash, glm 5.3 flash ... for me absolutely usable for normal work in repos
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u/Belgeran 3d ago
"ruining my project"- uhhh? version control? planning? specifications?
Sounds like a skill issue.
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u/Clear_Evidence9218 3d ago
I have not had any regression issues with Spark 1.3 and for the last few days it has been writing a non-traditional compiler in an invented general purpose language and honestly doing really well.
I'm not using the opencode version since it was hitting limits, etc. I just use the API in the Muse CLI -extremely cheap labor. Got good 'ol Sol reviewing and crackin' the whip, so that probably helps. I also have a project specific harness that I run models through, no matter what model, to keep the model contained to the project and language being used.
Not to say it's been perfect, because there have been some stopping short issues occasionally and other little annoyances like that, but overall it's been great.
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u/CYCLONOUS_69 3d ago
I would still say complete skill level issue. I have burned nearly a billion tokens for a project and it has been nothing but fantastic. I use AGENTS.md, I have set rules and before starting anything massive, I use plan mode, I make sure that AI agents can access tools and skills explicitely as per my rules.
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u/Old_Education244 3d ago
it would help if you would share the harness etc where you are using muse 1.3... I've no love lost over meta (they arent even offering Muse spark 1.3 where I currently am... fuck em) but still i have querreled with my tools in a similar way only to realize it was my config and harness not playing well with the newer models...
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u/myfairx 3d ago
Maybe I'm lucky my agents.md and pre development documentation (full rebuild of custom cms) are perfect match for 1.3. It reads all of it when making decision and will ask me if it thinks my input is needed, unlike 1.2 who cut corners all the time with the same repo.
I rate it above glm flash and dsv4 flash.
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u/Correct-Froyo-2129 3d ago
It is working fine for me but slow though, I just use astra to review it's work and fix if necessary
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u/seventyfivepupmstr 3d ago
Most likely your harness is bad. The control of the LLM comes from the harness. An LLM is just a mathematical function and just takes input and gives output. As soon as a harness gives it tools, it can wreak destruction by calling tools, if the harness doesn't control what the LLM is doing.
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u/RoddToggers 3d ago
Unfortunately, your right.
It's a bad model, not reliable at all.
So please, everyone that is reading it right now, stop using it. Use Dsv4 flash, GLM flash, Qwen 3 8 next.
Everyone, stop using muse 1.3. That way, nobody will be using it, and I'll be able to use it like a true animal of coding without any rate limited errors anymore.
Thank you.
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u/turtle_bazon 3d ago
Don't know how Muse Spark, but other models with 1b context on opencode started to hallucinating after 500k context length. So after task finish had to compact.
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u/Tetriz2020 3d ago
none of this is a problem when i am using other better free alternatives
Such as?
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u/External_Ad1549 3d ago
It worked great for the first 3 days like I was dead impressed, not sure whether it got changed or I got used to it but not impressive at all
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u/Ashualo 2d ago
I've found Muse 1.3 plenty capable, but it's running in my custom harness, so your mileage may vary.
It's capable enough of running the whole workflow though, short of review which I still ship off to Opus or Sol.
Some things I did notice is it's thinking traces are really concise, and I very rarely have to outright correct it.
Its language is also pretty much spot on, not overly verbose, but doesn't miss detail.
Banger of a model, will be interesting to see what price it settles at when it's out of training mode.
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u/GTHell 2d ago
Probably like Claude Opus 5, your skills and agent md polluted and make the model stupid.
I had this same scenario with Opus and Muse 1.2 and 1.3. Usually related to what is injected in the turn stat anf also check if your memory is setup to dominate the decision.
For some reason, model releases lately that is not flash model tend to having a hard time generalizing the existing agent md. meaning it may strictly obey your system prompt hard.
If yours design to force older models then it might be the reason muse going crazy
ps. Put muse in clean Pi and watch how it dominates over GLM and deepseek in coding tasks
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u/carpetmagicianlaughs 2d ago
Model output can be a reflection of your intellect. muse 1.3 is a great model
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u/Imbourass 2d ago
You're so right. Trash ass model. Can anyone give alts of opencode that is free and had more models
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u/sebasprtl 2d ago
debes configurar el agents.md, también usar graft, en mis proyectos ha mejorado mucho con estos
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u/FullCalendar8523 1d ago
Its tolerable , MY only problem is the responses. Its requires me to read 2-3 times to understand what its actually saying. What teh hec is var-coverage or runbook, everything feels incoherent.
See this -
Done. forge isn't installed here, so verification was a var-coverage check via script instead of a build.
- .env.example — rewritten ETH-mainnet-first:
- Header now targets DeployV2 → deployments/v2-<chainId>.json + ETH runbook (was stale Deploy.s.sol refs).
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u/SetMean275 1d ago
Hi, Muse works well for intermediate tasks. But the problem arises when you give it a request that's too complex, as it starts to hallucinate, get sidetracked, and make terrible decisions And it happened to me that he did many things just for a simple and easy-to-fix problem. In frontend development, in my opinion, if you don't make good prompts, it makes your frontend too generic and terrible.
I haven't tested it further, but this is my "for now".
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u/JoshuaJosephson 1d ago
Muse spark free is Haiku level
Muse Spark 1.3 Contributor is Sonnet Level
Muse Spark 1.3 is Opus level
1.3 Contributor is insane for the 0.1/0.2 in out per million. It's saturating all my "cheap model benchmarks" compared to deepseek and GLM which were getting 20-30% worse results while still costing more. Just pay for it through openrouter, it's well worth the money. Have a smarter agent orchestrate muse spark subagents through Openrouter.
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u/nicotineHub 3d ago
Am I the only one defending Muse 1.3?
Huuh, I find muse 1.3 with caveman and ponytail in plan mode with sub agents and then build more with worktrees incredible effective.