NVIDIA Nemotron 3 Super vs GPT-5.6 Sol
Head-to-head specifications
| Metric | NVIDIA Nemotron 3 Super | GPT-5.6 Sol | Difference |
|---|---|---|---|
| Intelligence Index | 29.0 | 59.0 | -50.8% |
| Coding Index | 37.7 | 77.4 | -51.3% |
| Agentic Index | 8.7 | 54.0 | — |
| Context window | 1M tokens | 1M tokens | — |
| Blended price ($/1M tokens) | $0.22 | $1.54 | -85.7% |
| Output speed (tokens/s) | 158 | 57 | +177.2% |
| Access | Proprietary API | Proprietary API | — |
- GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 29.0).
- NVIDIA Nemotron 3 Super is the cheaper model to run at $0.22/1M blended tokens — about 7.0× cheaper.
Verdict: NVIDIA Nemotron 3 Super or GPT-5.6 Sol?
NVIDIA Nemotron 3 Super advantages
- Affordability (+86%)
- Output speed (+64%)
GPT-5.6 Sol advantages
- General intelligence (+51%)
- Coding ability (+51%)
- Agentic task performance (+84%)
Which should you choose?
- Choose the NVIDIA Nemotron 3 Super if you want the lowest cost per token at scale.
- Choose the GPT-5.6 Sol if you need the strongest overall reasoning and accuracy.
- Choose the NVIDIA Nemotron 3 Super if low latency and fast generation matter for your application.
Value for money
NVIDIA Nemotron 3 Super offers more intelligence per dollar (3.4× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
NVIDIA Nemotron 3 Super vs GPT-5.6 Sol: which should you choose?
NVIDIA Nemotron 3 Super — NVIDIA multimodal model with an Intelligence Index of 29, a 1M-token context window and a blended price of $0.22/1M tokens.
GPT-5.6 Sol — OpenAI multimodal model with an Intelligence Index of 59, a 1M-token context window and a blended price of $1.54/1M tokens.
NVIDIA Nemotron 3 Super vs GPT-5.6 Sol: GPT-5.6 Sol scores higher on the Intelligence Index. GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 29.0). NVIDIA Nemotron 3 Super is the cheaper model to run at $0.22/1M blended tokens — about 7.0× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the GPT-5.6 Sol scores 59.0 versus 29.0. For software development, the Coding Index puts GPT-5.6 Sol ahead (77.4 vs 37.7). On agentic, multi-step tool-use tasks, GPT-5.6 Sol measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The NVIDIA Nemotron 3 Super accepts up to 1 million tokens per request, which sets how much documentation, transcript or code it can reason over at once. In measured throughput, NVIDIA Nemotron 3 Super generates faster (158 vs 57 tokens/s), which matters for interactive apps and high-volume pipelines.
Pricing and access
At blended per-token rates, NVIDIA Nemotron 3 Super is the cheaper model to run ($0.22 vs $1.54 per 1M tokens). NVIDIA Nemotron 3 Super is proprietary api and GPT-5.6 Sol is proprietary api. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the NVIDIA Nemotron 3 Super better than the GPT-5.6 Sol?
GPT-5.6 Sol takes the overall edge, though NVIDIA Nemotron 3 Super wins in specific areas worth weighing. GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 29.0).
What is the main difference between the NVIDIA Nemotron 3 Super and the GPT-5.6 Sol?
GPT-5.6 Sol leads overall capability (Intelligence Index 59.0 vs 29.0). NVIDIA Nemotron 3 Super is the cheaper model to run at $0.22/1M blended tokens — about 7.0× cheaper.
Which is better value?
NVIDIA Nemotron 3 Super offers more intelligence per dollar (3.4× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use.
Which should I choose?
Choose the NVIDIA Nemotron 3 Super if you want the lowest cost per token at scale. Choose the GPT-5.6 Sol if you need the strongest overall reasoning and accuracy.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.