Nemotron 3.5 Super VL Open vs 
Mistral Large Open
Nemotron 3.5 Super VL vs Mistral Large compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.
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
$6 /M outputNo per-token fees if you self-host
Nemotron 3.5 Super VL vs Mistral Large specs
| Spec | Nemotron 3.5 Super VL | Mistral Large | Winner |
|---|---|---|---|
| Maker | NVIDIA | Mistral AI | – |
| Type | Open-weight | Open-weight | – |
| Context window | 1M tokens | 128K tokens | |
| Input price | $0.15/M · free self-host | $2/M · free self-host | |
| Output price | $0.5/M · free self-host | $6/M · free self-host | |
| Vision / multimodal | Yes | No | |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | Yes | = Tie |
| License | NVIDIA Open Model | Apache 2.0 | – |
Price gap & when to choose each
Nemotron 3.5 Super VL is ~12× cheaper than Mistral Large on output tokens ($0.5 vs $6 per M tokens).
- You want to self-host or run on your cloud
- You need the longer 1M context window
- You prioritize data privacy & control
- You want the lowest operating costs
- You are building open or reproducible AI
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You are building open or reproducible AI
Feature comparison
| Capability | Nemotron 3.5 Super VL | Mistral Large |
|---|---|---|
| Open weights (downloadable) | ✓ | ✓ |
| Self-hostable | ✓ | ✓ |
| Runs fully offline | ✓ | ✓ |
| Vision / multimodal | ✓ | ✗ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✗ |
Benchmarks: Nemotron 3.5 Super VL vs Mistral Large
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Nemotron 3.5 Super VL and Mistral Large score
| Criterion | Nemotron 3.5 Super VL | Mistral Large |
|---|---|---|
| Cost-efficiency | 5.0 | 4.0 |
| Context window | 5.0 | 3.5 |
| Openness | 5.0 | 5.0 |
| Self-hosting | 5.0 | 5.0 |
| Multimodality | 5.0 | 3.5 |
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...
Mistral Large Open
This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Nemotron 3.5 Super VL vs Mistral Large — which is cheaper?
Nemotron 3.5 Super VL is cheaper on output ($0.5/M vs $6/M).
Which has the larger context window?
Nemotron 3.5 Super VL offers the larger context window (1M tokens).
Nemotron 3.5 Super VL vs Mistral Large — which should I pick in 2026?
Choose Nemotron 3.5 Super VL for the lower output price ($0.5/M vs $6/M). It also gives you the larger 1M context window.
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