Laguna S 2.1 vs Laguna XS 2.1 vs Ling 3.0 Flash Fin
Too close to call on our weighted score (Laguna S 2.1 69, Laguna XS 2.1 68, Ling 3.0 Flash Fin 65). The right pick depends on what you value most.
Poolside
Laguna S 2.1
69/100- ECI—
- Price$0.10 / $0.20
- Context1.05M
Poolside
Laguna XS 2.1
68/100- ECI—
- Price$0.06 / $0.12
- Context262K
inclusionAI
Ling 3.0 Flash Fin
65/100- ECI—
- Price$0.075 / $0.22
- Context262K
Too close to call
It is close. Our weighted score puts them within 1 points (Laguna S 2.1 69/100, Laguna XS 2.1 68/100, Ling 3.0 Flash Fin 65/100), so choose by what matters most for your work: Laguna XS 2.1 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 priceLaguna XS 2.1Laguna XS 2.1 $0.075 · Ling 3.0 Flash Fin $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 · Laguna XS 2.1 262,144 · Ling 3.0 Flash Fin 262,144 tokens
- Widest inputsSame inputsLaguna S 2.1: Text · Laguna XS 2.1: Text · Ling 3.0 Flash Fin: Text
- Self-hostingLaguna S 2.1 and Laguna XS 2.1Publishes downloadable weights
| Measure | Weight | Laguna S 2.1 | Laguna XS 2.1 | Ling 3.0 Flash Fin |
|---|---|---|---|---|
| Price | 50% | 93 | 100 | 95 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 61 | 37 | 37 |
| Overall | 100% | 69/100 | 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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 | $0.06 (best) | $0.075 |
| Output | $0.20 | $0.12 (best) | $0.22 |
| Cached input | — | — | — |
| Blended (3:1) | $0.125 | $0.075 (best) | $0.111 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Median of 1 providers | Median of 1 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 262,144 tokens |
| Max output | 32,768 tokens | 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 | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | poolside/laguna-s-2.1 | poolside/laguna-xs-2.1 | — |
| API providers | 6 (best) | 4 | 2 |
| Released | Jul 21, 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.
Laguna S 2.1$1.40
Laguna XS 2.1$0.84
Ling 3.0 Flash Fin$1.19
Which should you choose?
Which is better: Laguna S 2.1, Laguna XS 2.1 or Ling 3.0 Flash Fin?
It is close. Our weighted score puts them within 1 points (Laguna S 2.1 69/100, Laguna XS 2.1 68/100, Ling 3.0 Flash Fin 65/100), so choose by what matters most for your work: Laguna XS 2.1 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, Laguna S 2.1, 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). Ling 3.0 Flash Fin 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 $0.075 per million tokens for Laguna XS 2.1 versus $0.111 for Ling 3.0 Flash Fin (1.5× as much) and $0.125 for Laguna S 2.1 (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Laguna S 2.1 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 Laguna S 2.1, 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?
Laguna S 2.1 has the largest context window at 1,048,576 tokens, against 262,144 for Laguna XS 2.1 and 262,144 for Ling 3.0 Flash Fin. Maximum output per response: Laguna S 2.1 up to 32,768, 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?
Laguna S 2.1 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?
Laguna S 2.1 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. Laguna S 2.1 came out Jul 21, 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.