Nemotron 3 Super 120B A12B vs Laguna XS 2.1 vs Mercury 2
Laguna XS 2.1 comes out ahead, 68 to 54 and 53 on our weighted score, and it is the cheaper option too.
NVIDIANemotron 3 Super 120B A12B
54/100- ECI—
- Price$0.20 / $0.80
- Context262K
- Our pick
PoolsideLaguna XS 2.1
68/100- ECI—
- Price$0.06 / $0.12
- Context262K
InceptionMercury 2
53/100- ECI—
- Price$0.25 / $0.75
- Context128K
Laguna XS 2.1 is our pick
Laguna XS 2.1 is the better all-round choice, scoring 68/100 against Nemotron 3 Super 120B A12B (54) and Mercury 2 (53). It leads on price. Mercury 2 wins on inputs & features. 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 XS 2.1Laguna XS 2.1 $0.075 · Nemotron 3 Super 120B A12B $0.35 · Mercury 2 $0.375 per 1M tokens (3:1 blend)
- Longest contextNemotron 3 Super 120B A12B and Laguna XS 2.1Nemotron 3 Super 120B A12B 262,144 · Laguna XS 2.1 262,144 · Mercury 2 128,000 tokens
- Widest inputsSame inputsNemotron 3 Super 120B A12B: Text · Laguna XS 2.1: Text · Mercury 2: Text
- Self-hostingNemotron 3 Super 120B A12B and Laguna XS 2.1Publishes downloadable weights
| Measure | Weight | Nemotron 3 Super 120B A12B | Laguna XS 2.1 | Mercury 2 |
|---|---|---|---|---|
| Price | 50% | 72 | 100 | 70 |
| Inputs & features | 30% | 35 | 35 | 45 |
| Context window | 20% | 37 | 37 | 24 |
| Overall | 100% | 54/100 | 68/100 | 53/100 |
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 Super 120B A12BNVIDIA | Laguna XS 2.1Poolside | Mercury 2Inception |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.06 (best) | $0.25 |
| Output | $0.80 | $0.12 (best) | $0.75 |
| Cached input | — | — | $0.025 |
| Blended (3:1) | $0.35 | $0.075 (best) | $0.375 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Nvidia API | Median of 1 providers | Official Inception API |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 128,000 tokens |
| Max output | 262,144 tokens (best) | 32,768 tokens | 50,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yeslow · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | nvidia/nemotron-3-super-120b-a12b | poolside/laguna-xs-2.1 | mercury-2 |
| API providers | 19 (best) | 4 | 1 |
| Released | Mar 11, 2026 | Jul 2, 2026 | Feb 24, 2026 |
| Knowledge cutoff | — | — | Jan 1, 2025 |
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 Super 120B A12B$3.60
- Laguna XS 2.1$0.84
- Mercury 2$4.00
Which should you choose?
Which is better: Nemotron 3 Super 120B A12B, Laguna XS 2.1 or Mercury 2?
Laguna XS 2.1 is the better all-round choice, scoring 68/100 against Nemotron 3 Super 120B A12B (54) and Mercury 2 (53). It leads on price. Mercury 2 wins on inputs & features. 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 Super 120B A12B, Laguna XS 2.1 or Mercury 2?
Laguna XS 2.1 is cheaper at $0.06 input / $0.12 output per million tokens (median across 1 API provider; free on Poolside). Nemotron 3 Super 120B A12B costs $0.20 input / $0.80 output per million tokens (official Nvidia API price); Mercury 2 costs $0.25 input / $0.75 output per million tokens (official Inception API price). At a typical mix of three input tokens to one output token, that is $0.075 per million tokens for Laguna XS 2.1 versus $0.35 for Nemotron 3 Super 120B A12B (4.7× as much) and $0.375 for Mercury 2 (5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Nemotron 3 Super 120B A12B has not been scored yet, Laguna XS 2.1 has not been scored yet and Mercury 2 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Nemotron 3 Super 120B A12B, Laguna XS 2.1 and Mercury 2 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?
Nemotron 3 Super 120B A12B and Laguna XS 2.1 have the largest context windows (262,144 and 262,144 tokens), against 128,000 for Mercury 2. Maximum output per response: Nemotron 3 Super 120B A12B up to 262,144, Laguna XS 2.1 up to 32,768, Mercury 2 up to 50,000 tokens.
Which can read images, PDFs, audio or video?
Nemotron 3 Super 120B A12B accepts text; Laguna XS 2.1 accepts text; Mercury 2 accepts text. They handle the same number of input types.
Are any of these open source?
Nemotron 3 Super 120B A12B and Laguna XS 2.1 publishes its weights and can be self-hosted; Mercury 2 is proprietary.
Which is newer?
Laguna XS 2.1 is the newest, released Jul 2, 2026. Nemotron 3 Super 120B A12B came out Mar 11, 2026; Mercury 2 came out Feb 24, 2026. Knowledge cutoff: Mercury 2 Jan 1, 2025.
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.
