GPT-6 Sol vs Nemotron 3 Nano (30B A3B)
GPT-6 Sol leads the LLM Stats Score 49.4 to 21.0. Nemotron 3 Nano (30B A3B) is 45.7x cheaper per token.
OpenAI · NVIDIA · Updated for 2026
Which is better?
GPT-6 Sol leads the overall LLM Stats Score 49.4 to 21.0, ranking #21 overall.
On price, Nemotron 3 Nano (30B A3B) is roughly 45.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Sol also accepts a larger context window (1,050,000 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-6 Sol
- overall performance matters — it scores 49.4 and ranks #21 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Nemotron 3 Nano (30B A3B)
- cost matters — it's about 45.7x cheaper per token
- 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
5 reported for GPT-6 Sol · 15 for Nemotron 3 Nano (30B A3B)
GPT-6 Sol and Nemotron 3 Nano (30B A3B)don'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, GPT-6 Sol ($2.00/1M tokens) is 40.0x more expensive than Nemotron 3 Nano (30B A3B) ($0.05/1M tokens).
For output processing, GPT-6 Sol ($10.00/1M tokens) is 50.0x more expensive than Nemotron 3 Nano (30B A3B) ($0.20/1M tokens).
In conclusion, GPT-6 Sol is more expensive than Nemotron 3 Nano (30B A3B).*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Sol accepts 1,050,000 input tokens compared to Nemotron 3 Nano (30B A3B)'s 262,144 tokens. Nemotron 3 Nano (30B A3B) can generate longer responses up to 262,144 tokens, while GPT-6 Sol is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Sol supports multimodal inputs, whereas Nemotron 3 Nano (30B A3B) does not.
GPT-6 Sol can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Sol
Nemotron 3 Nano (30B A3B)
License
Usage and distribution terms
GPT-6 Sol is licensed under a proprietary license, while Nemotron 3 Nano (30B A3B) uses NVIDIA Open Model License Agreement .
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
NVIDIA Open Model License Agreement
Open weights
Release Timeline
When each model was launched
GPT-6 Sol was released on 2026-09-22, while Nemotron 3 Nano (30B A3B) was released on 2025-12-15.
GPT-6 Sol is 9 months newer than Nemotron 3 Nano (30B A3B).
Sep 22, 2026
0 days ago
9mo newerDec 15, 2025
9 months ago
Knowledge Cutoff
When training data ends
GPT-6 Sol has a knowledge cutoff of 2026-04-20, while Nemotron 3 Nano (30B A3B) has a cutoff of 2025-11-28.
GPT-6 Sol has more recent training data (up to 2026-04-20), making it potentially better informed about events through that date compared to Nemotron 3 Nano (30B A3B) (2025-11-28).
Apr 2026
5 mo newerNov 2025
Provider Availability
GPT-6 Sol is available from OpenAI. Nemotron 3 Nano (30B A3B) is available from DeepInfra.
GPT-6 Sol
Nemotron 3 Nano (30B A3B)
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Sol and Nemotron 3 Nano (30B A3B) side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Sol vs Nemotron 3 Nano (30B A3B).