Nemotron 3 Nano Omni 30B A3B Reasoning vs Laguna M.1 vs Trinity Large Thinking
Too close to call on our weighted score (Nemotron 3 Nano Omni 30B A3B Reasoning 69, Laguna M.1 68, Trinity Large Thinking 55). The right pick depends on what you value most.
NVIDIANemotron 3 Nano Omni 30B A3B Reasoning
69/100- ECI—
- Price$0.25 / $0.85
- Context256K
PoolsideLaguna M.1
68/100- ECI—
- PriceFree / Free
- Context262K
Arcee AITrinity Large Thinking
55/100- ECI—
- Price$0.25 / $0.80
- Context524K
Too close to call
It is close. Our weighted score puts them within a point (Nemotron 3 Nano Omni 30B A3B Reasoning 69/100, Laguna M.1 68/100, Trinity Large Thinking 55/100), so choose by what matters most for your work: Laguna M.1 on price and Trinity Large Thinking for long inputs. 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 priceLaguna M.1Laguna M.1 Free · Trinity Large Thinking $0.388 · Nemotron 3 Nano Omni 30B A3B Reasoning $0.40 per 1M tokens (3:1 blend)
- Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · Laguna M.1 262,144 · 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 · Laguna M.1: Text · Trinity Large Thinking: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Nemotron 3 Nano Omni 30B A3B Reasoning | Laguna M.1 | Trinity Large Thinking |
|---|---|---|---|---|
| Price | 50% | 69 | 100 | 69 |
| Inputs & features | 30% | 90 | 35 | 35 |
| Context window | 20% | 36 | 37 | 49 |
| Overall | 100% | 69/100 | 68/100 | 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 | Nemotron 3 Nano Omni 30B A3B ReasoningNVIDIA | Laguna M.1Poolside | Trinity Large ThinkingArcee AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.25 | Free (best) | $0.25 |
| Output | $0.85 | Free (best) | $0.80 |
| Cached input | — | — | $0.06 |
| Blended (3:1) | $0.40 | Free (best) | $0.388 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Official Poolside API | Official Arcee API |
| Limits | |||
| Context window | 256,000 tokens | 262,144 tokens | 524,288 tokens (best) |
| Max output | 65,536 tokens | 32,768 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Open | OpenOpenMDW-1.1 |
| API model ID | nvidia/nemotron-3-nano-omni-30b-a3b-reasoning | poolside/laguna-m.1 | trinity-large-thinking |
| API providers | 8 (best) | 2 | 6 |
| Released | Apr 28, 2026 | Apr 28, 2026 | Apr 1, 2026 |
| Knowledge cutoff | — | — | — |
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
- Laguna M.1Free
- Trinity Large Thinking$4.10
Which should you choose?
Which is better: Nemotron 3 Nano Omni 30B A3B Reasoning, Laguna M.1 or Trinity Large Thinking?
It is close. Our weighted score puts them within a point (Nemotron 3 Nano Omni 30B A3B Reasoning 69/100, Laguna M.1 68/100, Trinity Large Thinking 55/100), so choose by what matters most for your work: Laguna M.1 on price and Trinity Large Thinking for long inputs. 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, Laguna M.1 or Trinity Large Thinking?
Laguna M.1 is cheaper at Free input / Free output per million tokens (official Poolside API price). Trinity Large Thinking costs $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). Laguna M.1 is listed as free.
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, Laguna M.1 has not been scored yet 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, Laguna M.1 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?
Trinity Large Thinking has the largest context window at 524,288 tokens, against 262,144 for Laguna M.1 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, Laguna M.1 up to 32,768, 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; Laguna M.1 accepts text; Trinity Large Thinking accepts text. Nemotron 3 Nano Omni 30B A3B Reasoning handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (OpenMDW-1.1), so you can self-host them.
Which is newer?
Nemotron 3 Nano Omni 30B A3B Reasoning is the newest, released Apr 28, 2026. Laguna M.1 came out Apr 28, 2026; Trinity Large Thinking came out Apr 1, 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.
