GPT-5.6 Sol vs Nemotron 3 Nano Omni 30B A3B Reasoning
Nemotron 3 Nano Omni 30B A3B Reasoning comes out ahead, 69 to 40 on our weighted score, and it is the cheaper option too.
OpenAIGPT-5.6 Sol
40/100- ECI161.8
- Price$4.00 / $20.00
- Context1.05M
- Our pick
NVIDIANemotron 3 Nano Omni 30B A3B Reasoning
69/100- ECI—
- Price$0.25 / $0.85
- Context256K
Add a model
Make it a three-way comparison.
Nemotron 3 Nano Omni 30B A3B Reasoning is our pick
Nemotron 3 Nano Omni 30B A3B Reasoning is the better all-round choice, scoring 69/100 against GPT-5.6 Sol (40). It leads on price and inputs & features. GPT-5.6 Sol wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceNemotron 3 Nano Omni 30B A3B ReasoningNemotron 3 Nano Omni 30B A3B Reasoning $0.40 · GPT-5.6 Sol $8.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.6 SolGPT-5.6 Sol 1,050,000 · Nemotron 3 Nano Omni 30B A3B Reasoning 256,000 tokens
- Widest inputsNemotron 3 Nano Omni 30B A3B ReasoningGPT-5.6 Sol: Text, Images, PDFs · Nemotron 3 Nano Omni 30B A3B Reasoning: Text, Images, Audio, Video
- Self-hostingNemotron 3 Nano Omni 30B A3B ReasoningPublishes downloadable weights
| Measure | Weight | GPT-5.6 Sol | Nemotron 3 Nano Omni 30B A3B Reasoning |
|---|---|---|---|
| Price | 50% | 7 | 69 |
| Inputs & features | 30% | 80 | 90 |
| Context window | 20% | 61 | 36 |
| Overall | 100% | 40/100 | 69/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5.6 SolOpenAI | Nemotron 3 Nano Omni 30B A3B ReasoningNVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 161.8 | — |
| ECI rank | #8 of 148 | — |
| GPQA DiamondGraduate-level science questions | 93.5% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 89.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% | — |
| SimpleQA VerifiedShort factual questions | 69.7% | — |
| Price per million tokens | ||
| Input | $4.00 | $0.25 (best) |
| Output | $20.00 | $0.85 (best) |
| Cached input | $0.40 | — |
| Blended (3:1) | $8.00 | $0.40 (best) |
| Long-context rate | Over 272K: $8.00 / $30.00 | Same rate |
| Price source | Official OpenAI API | Median of 4 providers |
| Limits | ||
| Context window | 1,050,000 tokens (best) | 256,000 tokens |
| Max output | 128,000 tokens (best) | 65,536 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | No |
| Audio | No | Yes |
| Video | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | gpt-5.6-sol | nvidia/nemotron-3-nano-omni-30b-a3b-reasoning |
| API providers | 40 (best) | 8 |
| Released | Jul 9, 2026 | Apr 28, 2026 |
| Knowledge cutoff | Feb 16, 2026 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.6 Sol$80.00
- Nemotron 3 Nano Omni 30B A3B Reasoning$4.20
Which should you choose?
Which is better: GPT-5.6 Sol or Nemotron 3 Nano Omni 30B A3B Reasoning?
Nemotron 3 Nano Omni 30B A3B Reasoning is the better all-round choice, scoring 69/100 against GPT-5.6 Sol (40). It leads on price and inputs & features. GPT-5.6 Sol wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GPT-5.6 Sol or Nemotron 3 Nano Omni 30B A3B Reasoning?
Nemotron 3 Nano Omni 30B A3B Reasoning is cheaper at $0.25 input / $0.85 output per million tokens (median across 4 API providers; free on Nvidia). GPT-5.6 Sol costs $4.00 input / $20.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.40 per million tokens for Nemotron 3 Nano Omni 30B A3B Reasoning versus $8.00 for GPT-5.6 Sol (20× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GPT-5.6 Sol has an ECI of 161.8 and Nemotron 3 Nano Omni 30B A3B Reasoning has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.6 Sol and Nemotron 3 Nano Omni 30B A3B Reasoning yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
GPT-5.6 Sol has the largest context window at 1,050,000 tokens, against 256,000 for Nemotron 3 Nano Omni 30B A3B Reasoning. Maximum output per response: GPT-5.6 Sol up to 128,000, Nemotron 3 Nano Omni 30B A3B Reasoning up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-5.6 Sol accepts text, images and PDFs; Nemotron 3 Nano Omni 30B A3B Reasoning accepts text, images, audio and video. Nemotron 3 Nano Omni 30B A3B Reasoning handles the widest range of inputs.
Are any of these open source?
Nemotron 3 Nano Omni 30B A3B Reasoning publishes its weights and can be self-hosted; GPT-5.6 Sol is proprietary.
Which is newer?
GPT-5.6 Sol is the newest, released Jul 9, 2026. Nemotron 3 Nano Omni 30B A3B Reasoning came out Apr 28, 2026. Knowledge cutoff: GPT-5.6 Sol Feb 16, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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