Muse Spark 1.3: Top-10 Across Text, Coding, Vision & Agents
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Overview
Muse Spark 1.3 from Meta delivers consistent top-10 performance across the HuaLinYuan leaderboards. It sits at #10 in Text & Chat (Index 1494), Coding (Index 1659), and Vision (Index 1290), while placing #17 in AI Agents (Index 3.26). This breadth makes it a versatile choice for teams that need a single model for writing, code generation, image understanding, and agent workflows.
The model is priced at $1.25 per million input tokens and $4.25 per million output tokens. It is not yet available on HuaLinYuan or LongHua AI, but comparable alternatives you can use today include Gemini 3.7 Flash, Gemini 3.8 Flash, and Kimi K3.
Strengths
- Top-10 in Text, Coding, Vision
- Strong agent-task performance
- Single model for multimodal needs
- Competitive per-token pricing
Best for
- General chat and writing assistance
- Code generation and debugging
- Image analysis and captioning
- Multi-step agent workflows
Things to know
- Not yet available on this platform
- Agent rank lower than core tasks
Muse Spark 1.3 vs other models
FAQ
What does Muse Spark 1.3 cost?
Official pricing is $1.25 per 1M input tokens and $4.25 per 1M output tokens. There is no free tier mentioned; you pay only for what you use through the provider's API.
What is Muse Spark 1.3 best at?
It excels across the board: #10 in Text & Chat, Coding, and Vision, plus #17 in AI Agents. This makes it strongest for teams needing one model that handles writing, code, images, and agent tasks reliably.
How do I choose between Muse Spark 1.3 and its peers?
If you want a single model covering text, code, vision, and agents with top-10 ranks, Muse Spark 1.3 fits. If you need immediate access on HuaLinYuan, Gemini 3.7/3.8 Flash and Kimi K3 are available now and offer similar breadth.
Can I use Muse Spark 1.3 on HuaLinYuan or LongHua AI?
Not yet. The model is not currently available on this site. For immediate use, try the comparable models listed: Gemini 3.7 Flash, Gemini 3.8 Flash, or Kimi K3.
Similar models you can use here
Tell LongHua Tree ASI what you want — it splits the task and assigns the strongest model to each part, then delivers the finished result.