Ling 3.1 Flash vs Nemotron 3.5 Lightning 30B A3B vs Laguna S 2.1
Too close to call on our weighted score (Nemotron 3.5 Lightning 30B A3B 71, Laguna S 2.1 69, Ling 3.1 Flash 65). The right pick depends on what you value most.
inclusionAI
Ling 3.1 Flash
65/100- ECI—
- Price$0.075 / $0.22
- Context262K
NVIDIA
Nemotron 3.5 Lightning 30B A3B
71/100- ECI—
- Price$0.05 / $0.20
- Context262K
Poolside
Laguna S 2.1
69/100- ECI—
- Price$0.10 / $0.20
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 2 points (Nemotron 3.5 Lightning 30B A3B 71/100, Laguna S 2.1 69/100, Ling 3.1 Flash 65/100), so choose by what matters most for your work: Nemotron 3.5 Lightning 30B A3B on price and Laguna S 2.1 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 priceNemotron 3.5 Lightning 30B A3BNemotron 3.5 Lightning 30B A3B $0.087 · Ling 3.1 Flash $0.111 · Laguna S 2.1 $0.125 per 1M tokens (3:1 blend)
- Longest contextLaguna S 2.1Laguna S 2.1 1,048,576 · Ling 3.1 Flash 262,144 · Nemotron 3.5 Lightning 30B A3B 262,144 tokens
- Widest inputsSame inputsLing 3.1 Flash: Text · Nemotron 3.5 Lightning 30B A3B: Text · Laguna S 2.1: Text
- Self-hostingNemotron 3.5 Lightning 30B A3B and Laguna S 2.1Publishes downloadable weights
| Measure | Weight | Ling 3.1 Flash | Nemotron 3.5 Lightning 30B A3B | Laguna S 2.1 |
|---|---|---|---|---|
| Price | 50% | 95 | 100 | 93 |
| Inputs & features | 30% | 35 | 45 | 35 |
| Context window | 20% | 37 | 37 | 61 |
| Overall | 100% | 65/100 | 71/100 | 69/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.075 | $0.05 (best) | $0.10 |
| Output | $0.22 | $0.20 (best) | $0.20 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.111 | $0.087 (best) | $0.125 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 9 providers | Median of 4 providers |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 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 | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | nvidia/nemotron-3.5-lightning-30b-a3b | poolside/laguna-s-2.1 |
| API providers | 3 | 12 (best) | 6 |
| Released | Sep 29, 2026 | Aug 11, 2026 | Jul 21, 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.
Ling 3.1 Flash$1.19
Nemotron 3.5 Lightning 30B A3B$0.90
Laguna S 2.1$1.40
Which should you choose?
Which is better: Ling 3.1 Flash, Nemotron 3.5 Lightning 30B A3B or Laguna S 2.1?
It is close. Our weighted score puts them within 2 points (Nemotron 3.5 Lightning 30B A3B 71/100, Laguna S 2.1 69/100, Ling 3.1 Flash 65/100), so choose by what matters most for your work: Nemotron 3.5 Lightning 30B A3B on price and Laguna S 2.1 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, Ling 3.1 Flash, Nemotron 3.5 Lightning 30B A3B or Laguna S 2.1?
Nemotron 3.5 Lightning 30B A3B is cheaper at $0.05 input / $0.20 output per million tokens (median across 9 API providers; free on Nvidia). Ling 3.1 Flash costs $0.075 input / $0.22 output per million tokens (median across 1 API provider); Laguna S 2.1 costs $0.10 input / $0.20 output per million tokens (median across 4 API providers; free on Poolside). At a typical mix of three input tokens to one output token, that is $0.087 per million tokens for Nemotron 3.5 Lightning 30B A3B versus $0.111 for Ling 3.1 Flash (1.3× as much) and $0.125 for Laguna S 2.1 (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Ling 3.1 Flash has not been scored yet, Nemotron 3.5 Lightning 30B A3B has not been scored yet and Laguna S 2.1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Ling 3.1 Flash, Nemotron 3.5 Lightning 30B A3B and Laguna S 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?
Laguna S 2.1 has the largest context window at 1,048,576 tokens, against 262,144 for Ling 3.1 Flash and 262,144 for Nemotron 3.5 Lightning 30B A3B. Maximum output per response: Ling 3.1 Flash up to 32,768, Nemotron 3.5 Lightning 30B A3B up to 262,144, Laguna S 2.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Ling 3.1 Flash accepts text; Nemotron 3.5 Lightning 30B A3B accepts text; Laguna S 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 S 2.1 publishes its weights and can be self-hosted; Ling 3.1 Flash is proprietary.
Which is newer?
Ling 3.1 Flash is the newest, released Sep 29, 2026. Nemotron 3.5 Lightning 30B A3B came out Aug 11, 2026; Laguna S 2.1 came out Jul 21, 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.