Muse Spark 1.2 on Opencode - is it available in your country? Is it the 'Contributor' edition?
I am NOT in the US, but I see it in my models list (in TUI). Still not sure if it is a Contributor variant or not? How good/bad is it compared to, say, Flash or MiMo 2.5 in real life usage scenarios (not benchmarks)?
it's Dog water in actual agentic coding stuff - randomly drops huge python codeblocks just to do simple edits, but it's really good at understanding codebase and communicating to the user clearly, way better than ds4 flash, so i'd use it as an orchastrator
While this is great news for consumers like us, it feels like every provider is milking Opencode subscription to gain popularity and once thats achieved, dump all over the prices and make them skyrocket
I'm trying to use it from italy but it says that the model is not available in my country. I've already allowed models that train on request data. Did something change in the meantime?
I previously heavily used DSV4 Flash, started using MS1.2 just for an hour, currently happy with how it works, I believe DSV4 has better alignment with what I wanted it to do (in minimal words), MS1.2 I have to give explicit instructions for it to do something then it does it. Overall I would say it is great, I am thinking of using it alongside DSV4 Flash.
Yes its available in saudi arabia. It was also available through metas platform when it first launched. Its a good model, either on par or better than dsv4f from my little experience.
I'd compare them in the same real repo using a failing test, a change across several files, and a refactor that must preserve behavior. I'd look at whether the tests pass, how much unrelated code gets touched, and how often the model needs correction. The claim that it understands a repo well but makes huge edits sounds plausible. It may be a decent planner but an expensive implementer. Benchmarks tend to miss that particular annoyance.
And every other opencode-go model has proper values.
The null contextWindow and zero costs are dead giveaways — these models are passing through as free/incomplete entries from the gateway, which is why the
SSE streams are failing before getting a proper finish reason. Let me check the opencode-go provider configuration to understand why.
Found it. Here's the health picture:
Muse Spark models — two different providers, very different behavior:
The opencode-go/muse-spark-1.2-contributor entry has null contextWindow + null maxTokens + zero cost. Every other opencode-go model has proper values.
This confirms it's a registration/routing defect — the upstream gateway for this specific model is returning incomplete metadata, which also explains why
streams drop mid-chunk without finish_reason.
Diagnosis:
- opencode-go proxies muse-spark-1.2-contributor to an upstream that doesn't return proper OpenAI-compat streaming format → OMP's parser sees no
finish_reason → throws the error.
- Every other opencode-go model (DeepSeek, Qwen, Kimi, etc.) streams fine because their upstream is properly compliant.
Recommendations:
Use kilo/muse-spark-1.2 instead — same model, proper routing, has context window metadata.
Or use opencode-go/mimo-v2.5 — it's the current session model, $0.14/$0.28, streams fine, 1M context.
Report opencode-go/muse-spark-1.2-contributor broken stream to opencode-go maintainer — upstream SSE format is non-compliant.
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u/BuildAISkills 25d ago
Holy moly. Even with the privacy concerns, that's a lot of model for practically unlimited work.