Mercury 2.5 vs Nemotron 3.5 Lightning 30B A3B vs Laguna XS 2.1
Too close to call on our weighted score (Nemotron 3.5 Lightning 30B A3B 71, Mercury 2.5 71, Laguna XS 2.1 68). The right pick depends on what you value most.
InceptionMercury 2.5
71/100- ECI—
- Price$0.04 / $0.15
- Context260K
NVIDIANemotron 3.5 Lightning 30B A3B
71/100- ECI—
- Price$0.05 / $0.20
- Context262K
PoolsideLaguna XS 2.1
68/100- ECI—
- Price$0.06 / $0.12
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Nemotron 3.5 Lightning 30B A3B 71/100, Mercury 2.5 71/100, Laguna XS 2.1 68/100), so choose by what matters most for your work: Mercury 2.5 on price. 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 priceMercury 2.5Mercury 2.5 $0.068 · Laguna XS 2.1 $0.075 · Nemotron 3.5 Lightning 30B A3B $0.087 per 1M tokens (3:1 blend)
- Longest contextAbout the sameNemotron 3.5 Lightning 30B A3B 262,144 · Laguna XS 2.1 262,144 · Mercury 2.5 260,000 tokens
- Widest inputsSame inputsMercury 2.5: Text · Nemotron 3.5 Lightning 30B A3B: Text · Laguna XS 2.1: Text
- Self-hostingNemotron 3.5 Lightning 30B A3B and Laguna XS 2.1Publishes downloadable weights
| Measure | Weight | Mercury 2.5 | Nemotron 3.5 Lightning 30B A3B | Laguna XS 2.1 |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 45 | 45 | 35 |
| Context window | 20% | 36 | 37 | 37 |
| Overall | 100% | 71/100 | 71/100 | 68/100 |
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 | Mercury 2.5Inception | Nemotron 3.5 Lightning 30B A3BNVIDIA | Laguna XS 2.1Poolside |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.04 (best) | $0.05 | $0.06 |
| Output | $0.15 | $0.20 | $0.12 (best) |
| Cached input | $0.004 | — | — |
| Blended (3:1) | $0.068 (best) | $0.087 | $0.075 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Inception API | Median of 9 providers | Median of 1 providers |
| Limits | |||
| Context window | 260,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 65,536 tokens | 262,144 tokens (best) | 32,768 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 | Yeslow · medium · high | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | mercury-2.5 | nvidia/nemotron-3.5-lightning-30b-a3b | poolside/laguna-xs-2.1 |
| API providers | 1 | 12 (best) | 4 |
| Released | Sep 8, 2026 | Aug 11, 2026 | Jul 2, 2026 |
| Knowledge cutoff | Nov 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.
- Mercury 2.5$0.70
- Nemotron 3.5 Lightning 30B A3B$0.90
- Laguna XS 2.1$0.84
Which should you choose?
Which is better: Mercury 2.5, Nemotron 3.5 Lightning 30B A3B or Laguna XS 2.1?
It is close. Our weighted score puts them within a point (Nemotron 3.5 Lightning 30B A3B 71/100, Mercury 2.5 71/100, Laguna XS 2.1 68/100), so choose by what matters most for your work: Mercury 2.5 on price. 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, Mercury 2.5, Nemotron 3.5 Lightning 30B A3B or Laguna XS 2.1?
Mercury 2.5 is cheaper at $0.04 input / $0.15 output per million tokens (official Inception API price). Laguna XS 2.1 costs $0.06 input / $0.12 output per million tokens (median across 1 API provider; free on Poolside); Nemotron 3.5 Lightning 30B A3B costs $0.05 input / $0.20 output per million tokens (median across 9 API providers; free on Nvidia). At a typical mix of three input tokens to one output token, that is $0.068 per million tokens for Mercury 2.5 versus $0.075 for Laguna XS 2.1 (1.1× as much) and $0.087 for Nemotron 3.5 Lightning 30B A3B (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mercury 2.5 has not been scored yet, Nemotron 3.5 Lightning 30B A3B has not been scored yet and Laguna XS 2.1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mercury 2.5, Nemotron 3.5 Lightning 30B A3B and Laguna XS 2.1 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?
Their context windows are effectively the same size: Mercury 2.5 260,000, Nemotron 3.5 Lightning 30B A3B 262,144 and Laguna XS 2.1 262,144 tokens. Maximum output per response: Mercury 2.5 up to 65,536, Nemotron 3.5 Lightning 30B A3B up to 262,144, Laguna XS 2.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Mercury 2.5 accepts text; Nemotron 3.5 Lightning 30B A3B accepts text; Laguna XS 2.1 accepts text. They handle the same number of input types.
Are any of these open source?
Nemotron 3.5 Lightning 30B A3B and Laguna XS 2.1 publishes its weights and can be self-hosted; Mercury 2.5 is proprietary.
Which is newer?
Mercury 2.5 is the newest, released Sep 8, 2026. Nemotron 3.5 Lightning 30B A3B came out Aug 11, 2026; Laguna XS 2.1 came out Jul 2, 2026. Knowledge cutoff: Mercury 2.5 Nov 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.
