Qwen3.8 Max (0902) Open vs 
Muse Spark 1.1 Paid
Qwen3.8 Max (0902) vs Muse Spark 1.1 compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Muse Spark 1.1 — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$6 /M outputNo per-token fees if you self-host
$4.25 /M outputManaged API (no infra to run)
Qwen3.8 Max (0902) vs Muse Spark 1.1 specs
| Spec | Qwen3.8 Max (0902) | Muse Spark 1.1 | Winner |
|---|---|---|---|
| Maker | Alibaba | Meta | – |
| Type | Open-weight | Proprietary | |
| Context window | 1M tokens | 1M tokens | |
| Input price | $2/M · free self-host | $1.25/M | |
| Output price | $6/M · free self-host | $4.25/M | |
| Vision / multimodal | Yes | Yes | = Tie |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | Apache 2.0 | Proprietary |
Price gap & when to choose each
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You need the longer 1M context window
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Qwen3.8 Max (0902) | Muse Spark 1.1 |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✓ |
Benchmarks: Qwen3.8 Max (0902) vs Muse Spark 1.1
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Qwen3.8 Max (0902) and Muse Spark 1.1 score
| Criterion | Qwen3.8 Max (0902) | Muse Spark 1.1 |
|---|---|---|
| Cost-efficiency | 4.0 | 4.0 |
| Context window | 5.0 | 5.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 5.0 | 5.0 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
What each model is
Qwen3.8 Max (0902) Open
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...
Muse Spark 1.1 Paid
Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context...
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Is Qwen3.8 Max (0902) as good as Muse Spark 1.1?
Qwen3.8 Max (0902) is open-weight and competitive on many tasks, but Muse Spark 1.1 may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Can I run Qwen3.8 Max (0902) locally?
Yes. Qwen3.8 Max (0902) has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Muse Spark 1.1 is API-only and cannot be self-hosted.
Qwen3.8 Max (0902) vs Muse Spark 1.1 — which should I pick in 2026?
Choose Qwen3.8 Max (0902) if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Muse Spark 1.1 if you want frontier capability through a managed API with zero infrastructure to run.
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