Nemotron 3.5 Super VL (120B A12B) vs Qwen3 14B
Nemotron 3.5 Super VL (120B A12B) leads the LLM Stats Score 35.0 to 17.8. Qwen3 14B is 2.7x cheaper per token.
NVIDIA · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Nemotron 3.5 Super VL (120B A12B) leads the overall LLM Stats Score 35.0 to 17.8, ranking #108 overall.
On price, Qwen3 14B is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Nemotron 3.5 Super VL (120B A12B) also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Nemotron 3.5 Super VL (120B A12B)
- overall performance matters — it scores 35.0 and ranks #108 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Qwen3 14B
- cost matters — it's about 2.7x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for Nemotron 3.5 Super VL (120B A12B) · 17 for Qwen3 14B
Nemotron 3.5 Super VL (120B A12B) and Qwen3 14Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Nemotron 3.5 Super VL (120B A12B) ($0.20/1M tokens) is 1.7x more expensive than Qwen3 14B ($0.12/1M tokens).
For output processing, Nemotron 3.5 Super VL (120B A12B) ($1.00/1M tokens) is 4.2x more expensive than Qwen3 14B ($0.24/1M tokens).
In conclusion, Nemotron 3.5 Super VL (120B A12B) is more expensive than Qwen3 14B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Nemotron 3.5 Super VL (120B A12B) has 106.0B more parameters than Qwen3 14B, making it 757.1% larger.
Context Window
Maximum input and output token capacity
Nemotron 3.5 Super VL (120B A12B) accepts 262,144 input tokens compared to Qwen3 14B's 40,960 tokens. Nemotron 3.5 Super VL (120B A12B) can generate longer responses up to 262,144 tokens, while Qwen3 14B is limited to 40,960 tokens.
Input capabilities
Documented input modalities across available providers
Nemotron 3.5 Super VL (120B A12B) supports multimodal inputs, whereas Qwen3 14B does not.
Nemotron 3.5 Super VL (120B A12B) can handle both text and other forms of data like images, making it suitable for multimodal applications.
Nemotron 3.5 Super VL (120B A12B)
Qwen3 14B
License
Usage and distribution terms
Nemotron 3.5 Super VL (120B A12B) is licensed under OpenMDW License v1.1, while Qwen3 14B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
OpenMDW License v1.1
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Nemotron 3.5 Super VL (120B A12B) was released on 2026-10-15, while Qwen3 14B was released on 2025-04-28.
Nemotron 3.5 Super VL (120B A12B) is 18 months newer than Qwen3 14B.
Oct 15, 2026
2 days ago
1.5yr newerApr 28, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Nemotron 3.5 Super VL (120B A12B) is available from DeepInfra. Qwen3 14B is available from DeepInfra.
Nemotron 3.5 Super VL (120B A12B)
Qwen3 14B
Outputs Comparison
Judge for yourself.
Run your own prompts against Nemotron 3.5 Super VL (120B A12B) and Qwen3 14B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Nemotron 3.5 Super VL (120B A12B) vs Qwen3 14B.
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