Nemotron 3.5 Super VL Open vs 
Muse Spark 1.3 Contributor Paid
Nemotron 3.5 Super VL vs Muse Spark 1.3 Contributor 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 1.3 Contributor — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$0.5 /M outputNo per-token fees if you self-host
$0.2 /M outputManaged API (no infra to run)
Nemotron 3.5 Super VL vs Muse Spark 1.3 Contributor specs
| Spec | Nemotron 3.5 Super VL | Muse Spark 1.3 Contributor | Winner |
|---|---|---|---|
| Maker | NVIDIA | Meta | – |
| Type | Open-weight | Proprietary | |
| Context window | 1M tokens | 1M tokens | = Tie |
| Input price | $0.15/M · free self-host | $0.1/M | |
| Output price | $0.5/M · free self-host | $0.2/M | |
| Vision / multimodal | Yes | Yes | = Tie |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | NVIDIA Open Model | Proprietary |
Price gap & when to choose each
Muse Spark 1.3 Contributor is ~2.5× cheaper than Nemotron 3.5 Super VL on output tokens ($0.2 vs $0.5 per M tokens).
- 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 want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Nemotron 3.5 Super VL | Muse Spark 1.3 Contributor |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✓ |
Benchmarks: Nemotron 3.5 Super VL vs Muse Spark 1.3 Contributor
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Nemotron 3.5 Super VL and Muse Spark 1.3 Contributor score
| Criterion | Nemotron 3.5 Super VL | Muse Spark 1.3 Contributor |
|---|---|---|
| Cost-efficiency | 5.0 | 5.0 |
| 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
Nemotron 3.5 Super VL Open
NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video...
Muse Spark 1.3 Contributor Paid
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...
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 Nemotron 3.5 Super VL as good as Muse Spark 1.3 Contributor?
Nemotron 3.5 Super VL is open-weight and competitive on many tasks, but Muse Spark 1.3 Contributor 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 Nemotron 3.5 Super VL locally?
Yes. Nemotron 3.5 Super VL has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Muse Spark 1.3 Contributor is API-only and cannot be self-hosted.
Nemotron 3.5 Super VL vs Muse Spark 1.3 Contributor — which should I pick in 2026?
Choose Nemotron 3.5 Super VL 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 1.3 Contributor if you want frontier capability through a managed API with zero infrastructure to run.
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