GPT-5.2 Pro vs Nemotron 3.5 Super VL (120B A12B)
GPT-5.2 Pro leads the LLM Stats Score 42.8 to 35.0. Nemotron 3.5 Super VL (120B A12B) is 144.4x cheaper per token.
OpenAI · NVIDIA · Updated for 2026
Which is better?
GPT-5.2 Pro leads the overall LLM Stats Score 42.8 to 35.0, ranking #58 overall.
In the 3 individual benchmarks reported for both models, GPT-5.2 Pro wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Nemotron 3.5 Super VL (120B A12B) is roughly 144.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.2 Pro also accepts a larger context window (400,000 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 GPT-5.2 Pro
- overall performance matters — it scores 42.8 and ranks #58 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you process long inputs — it offers a 400,000 token context window
Choose Nemotron 3.5 Super VL (120B A12B)
- cost matters — it's about 144.4x cheaper per token
- you want the most recent training data — it shipped Oct 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
7 reported for GPT-5.2 Pro · 19 for Nemotron 3.5 Super VL (120B A12B)
GPT-5.2 Pro outperforms in 2 benchmarks (GPQA, Humanity's Last Exam), while Nemotron 3.5 Super VL (120B A12B) is better at 1 benchmark (BrowseComp).
GPT-5.2 Pro shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.2 Pro ($21.00/1M tokens) is 105.0x more expensive than Nemotron 3.5 Super VL (120B A12B) ($0.20/1M tokens).
For output processing, GPT-5.2 Pro ($168.00/1M tokens) is 168.0x more expensive than Nemotron 3.5 Super VL (120B A12B) ($1.00/1M tokens).
In conclusion, GPT-5.2 Pro is more expensive than Nemotron 3.5 Super VL (120B A12B).*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.2 Pro accepts 400,000 input tokens compared to Nemotron 3.5 Super VL (120B A12B)'s 262,144 tokens. Nemotron 3.5 Super VL (120B A12B) can generate longer responses up to 262,144 tokens, while GPT-5.2 Pro is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.2 Pro and Nemotron 3.5 Super VL (120B A12B) support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.2 Pro
Nemotron 3.5 Super VL (120B A12B)
License
Usage and distribution terms
GPT-5.2 Pro is licensed under a proprietary license, while Nemotron 3.5 Super VL (120B A12B) uses OpenMDW License v1.1.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
OpenMDW License v1.1
Open weights
Release Timeline
When each model was launched
GPT-5.2 Pro was released on 2025-12-11, while Nemotron 3.5 Super VL (120B A12B) was released on 2026-10-15.
Nemotron 3.5 Super VL (120B A12B) is 10 months newer than GPT-5.2 Pro.
Dec 11, 2025
10 months ago
Oct 15, 2026
4 days ago
10mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT-5.2 Pro is available from OpenAI. Nemotron 3.5 Super VL (120B A12B) is available from DeepInfra.
GPT-5.2 Pro
Nemotron 3.5 Super VL (120B A12B)
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.2 Pro and Nemotron 3.5 Super VL (120B A12B) side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.2 Pro vs Nemotron 3.5 Super VL (120B A12B).
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