Nemotron 3.5 Lightning 30B A3B vs Laguna XS 2.1 vs Ling 3.0 Flash Fin
Nemotron 3.5 Lightning 30B A3B comes out ahead, 71 to 68 and 65 on our weighted score, though Laguna XS 2.1 is 14% cheaper per token.
- Our pick
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
inclusionAILing 3.0 Flash Fin
65/100- ECI—
- Price$0.075 / $0.22
- Context262K
Nemotron 3.5 Lightning 30B A3B is our pick
Nemotron 3.5 Lightning 30B A3B is the better all-round choice, scoring 71/100 against Laguna XS 2.1 (68) and Ling 3.0 Flash Fin (65). It leads 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 3.5 Lightning 30B A3B $0.087 · Ling 3.0 Flash Fin $0.111 per 1M tokens (3:1 blend)
- Longest contextAbout the sameNemotron 3.5 Lightning 30B A3B 262,144 · Laguna XS 2.1 262,144 · Ling 3.0 Flash Fin 262,144 tokens
- Widest inputsSame inputsNemotron 3.5 Lightning 30B A3B: Text · Laguna XS 2.1: Text · Ling 3.0 Flash Fin: Text
- Self-hostingNemotron 3.5 Lightning 30B A3B and Laguna XS 2.1Publishes downloadable weights
| Measure | Weight | Nemotron 3.5 Lightning 30B A3B | Laguna XS 2.1 | Ling 3.0 Flash Fin |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 95 |
| Inputs & features | 30% | 45 | 35 | 35 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 71/100 | 68/100 | 65/100 |
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 3.5 Lightning 30B A3BNVIDIA | Laguna XS 2.1Poolside | Ling 3.0 Flash FininclusionAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.06 | $0.075 |
| Output | $0.20 | $0.12 (best) | $0.22 |
| Cached input | — | — | — |
| Blended (3:1) | $0.087 | $0.075 (best) | $0.111 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 9 providers | Median of 1 providers | Median of 1 providers |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 262,144 tokens (best) | 32,768 tokens | 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 | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | nvidia/nemotron-3.5-lightning-30b-a3b | poolside/laguna-xs-2.1 | — |
| API providers | 12 (best) | 4 | 2 |
| Released | Aug 11, 2026 | Jul 2, 2026 | Aug 27, 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 3.5 Lightning 30B A3B$0.90
- Laguna XS 2.1$0.84
- Ling 3.0 Flash Fin$1.19
Which should you choose?
Which is better: Nemotron 3.5 Lightning 30B A3B, Laguna XS 2.1 or Ling 3.0 Flash Fin?
Nemotron 3.5 Lightning 30B A3B is the better all-round choice, scoring 71/100 against Laguna XS 2.1 (68) and Ling 3.0 Flash Fin (65). It leads 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 3.5 Lightning 30B A3B, Laguna XS 2.1 or Ling 3.0 Flash Fin?
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 3.5 Lightning 30B A3B costs $0.05 input / $0.20 output per million tokens (median across 9 API providers; free on Nvidia); Ling 3.0 Flash Fin costs $0.075 input / $0.22 output per million tokens (median across 1 API provider). 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 $0.087 for Nemotron 3.5 Lightning 30B A3B (1.2× as much) and $0.111 for Ling 3.0 Flash Fin (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Nemotron 3.5 Lightning 30B A3B has not been scored yet, Laguna XS 2.1 has not been scored yet and Ling 3.0 Flash Fin has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Nemotron 3.5 Lightning 30B A3B, Laguna XS 2.1 and Ling 3.0 Flash Fin 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 3.5 Lightning 30B A3B, Laguna XS 2.1 and Ling 3.0 Flash Fin share the same 262,144-token context window. Maximum output per response: Nemotron 3.5 Lightning 30B A3B up to 262,144, Laguna XS 2.1 up to 32,768, Ling 3.0 Flash Fin up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Nemotron 3.5 Lightning 30B A3B accepts text; Laguna XS 2.1 accepts text; Ling 3.0 Flash Fin 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; Ling 3.0 Flash Fin is proprietary.
Which is newer?
Ling 3.0 Flash Fin is the newest, released Aug 27, 2026. Nemotron 3.5 Lightning 30B A3B came out Aug 11, 2026; Laguna XS 2.1 came out Jul 2, 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.
