Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3.6 27B vs Trinity Large Thinking

Nemotron 3 Nano Omni 30B A3B Reasoning is the better all-round choice, scoring 69/100 against Qwen3.6 27B (56) and Trinity Large Thinking (55). Trinity Large Thinking 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.

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); Qwen3.6 27B costs $0.60 input / $3.60 output per million tokens (official Alibaba 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 $1.35 for Qwen3.6 27B (3.5× as much).

There is no independent benchmark that covers all three models yet. Nemotron 3 Nano Omni 30B A3B Reasoning has not been scored yet, Qwen3.6 27B has an ECI of 146.5 and Trinity Large Thinking has not been scored yet.

There are no published SWE-bench Verified results for Nemotron 3 Nano Omni 30B A3B Reasoning, Qwen3.6 27B 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.

Trinity Large Thinking has the largest context window at 524,288 tokens, against 262,144 for Qwen3.6 27B 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, Qwen3.6 27B up to 65,536, Trinity Large Thinking up to 262,144 tokens.

Nemotron 3 Nano Omni 30B A3B Reasoning accepts text, images, audio and video; Qwen3.6 27B accepts text, images, audio and video; Trinity Large Thinking accepts text. Nemotron 3 Nano Omni 30B A3B Reasoning handles the widest range of inputs.

Yes, all three publish their weights (OpenMDW-1.1), so you can self-host them.

Nemotron 3 Nano Omni 30B A3B Reasoning is the newest, released Apr 28, 2026. Qwen3.6 27B came out Apr 22, 2026; Trinity Large Thinking came out Apr 1, 2026.

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.