Nemotron 3 Nano Omni 30B A3B Reasoning vs GPT-5.6 Sol vs Trinity Large Thinking
Nemotron 3 Nano Omni 30B A3B Reasoning comes out ahead, 69 to 55 and 40 on our weighted score.
- Our pick
NVIDIA
Nemotron 3 Nano Omni 30B A3B Reasoning
69/100- ECI—
- Price$0.25 / $0.85
- Context256K
OpenAI
GPT-5.6 Sol
40/100- ECI161.8
- Price$4.00 / $20.00
- Context1.05M
Arcee AI
Trinity Large Thinking
55/100- ECI—
- Price$0.25 / $0.80
- Context524K
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 Trinity Large Thinking (55) and GPT-5.6 Sol (40). It leads on 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 priceTrinity Large ThinkingTrinity Large Thinking $0.388 · Nemotron 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 · Trinity Large Thinking 524,288 · Nemotron 3 Nano Omni 30B A3B Reasoning 256,000 tokens
- Widest inputsNemotron 3 Nano Omni 30B A3B ReasoningNemotron 3 Nano Omni 30B A3B Reasoning: Text, Images, Audio, Video · GPT-5.6 Sol: Text, Images, PDFs · Trinity Large Thinking: Text
- Self-hostingNemotron 3 Nano Omni 30B A3B Reasoning and Trinity Large ThinkingPublishes downloadable weights (OpenMDW-1.1)
| Measure | Weight | Nemotron 3 Nano Omni 30B A3B Reasoning | GPT-5.6 Sol | Trinity Large Thinking |
|---|---|---|---|---|
| Price | 50% | 69 | 7 | 69 |
| Inputs & features | 30% | 90 | 80 | 35 |
| Context window | 20% | 36 | 61 | 49 |
| Overall | 100% | 69/100 | 40/100 | 55/100 |
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 | |||
|---|---|---|---|
| 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 | $0.25 (best) | $4.00 | $0.25 (best) |
| Output | $0.85 | $20.00 | $0.80 (best) |
| Cached input | — | $0.40 | $0.06 (best) |
| Blended (3:1) | $0.40 | $8.00 | $0.388 (best) |
| Long-context rate | Same rate | Over 272K: $8.00 / $30.00 | Same rate |
| Price source | Median of 4 providers | Official OpenAI API | Official Arcee API |
| Limits | |||
| Context window | 256,000 tokens | 1,050,000 tokens (best) | 524,288 tokens |
| Max output | 65,536 tokens | 128,000 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | Yes | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenOpenMDW-1.1 |
| API model ID | nvidia/nemotron-3-nano-omni-30b-a3b-reasoning | gpt-5.6-sol | trinity-large-thinking |
| API providers | 8 | 40 (best) | 6 |
| Released | Apr 28, 2026 | Jul 9, 2026 | Apr 1, 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.
Nemotron 3 Nano Omni 30B A3B Reasoning$4.20
GPT-5.6 Sol$80.00
Trinity Large Thinking$4.10
Which should you choose?
Which is better: Nemotron 3 Nano Omni 30B A3B Reasoning, GPT-5.6 Sol or Trinity Large Thinking?
Nemotron 3 Nano Omni 30B A3B Reasoning is the better all-round choice, scoring 69/100 against Trinity Large Thinking (55) and GPT-5.6 Sol (40). It leads on 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, Nemotron 3 Nano Omni 30B A3B Reasoning, GPT-5.6 Sol or Trinity Large Thinking?
Trinity Large Thinking is cheaper at $0.25 input / $0.80 output per million tokens (official Arcee API price). Nemotron 3 Nano Omni 30B A3B Reasoning costs $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 $0.388 per million tokens for Trinity Large Thinking versus $0.40 for Nemotron 3 Nano Omni 30B A3B Reasoning (1× as much) and $8.00 for GPT-5.6 Sol (21× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Nemotron 3 Nano Omni 30B A3B Reasoning has not been scored yet, GPT-5.6 Sol has an ECI of 161.8 and Trinity Large Thinking has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Nemotron 3 Nano Omni 30B A3B Reasoning, GPT-5.6 Sol and Trinity Large Thinking yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three 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 524,288 for Trinity Large Thinking and 256,000 for Nemotron 3 Nano Omni 30B A3B Reasoning. Maximum output per response: Nemotron 3 Nano Omni 30B A3B Reasoning up to 65,536, GPT-5.6 Sol up to 128,000, Trinity Large Thinking up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Nemotron 3 Nano Omni 30B A3B Reasoning accepts text, images, audio and video; GPT-5.6 Sol accepts text, images and PDFs; Trinity Large Thinking accepts text. 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 and Trinity Large Thinking publishes its weights (OpenMDW-1.1) 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; Trinity Large Thinking came out Apr 1, 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.