Laguna S 2.1 vs Ling 3.0 Flash Fin vs Ling 3.0 Flash VL
Ling 3.0 Flash VL comes out ahead, 76 to 68 and 63 on our weighted score, and it is the cheaper option too.
PoolsideLaguna S 2.1
68/100- ECI—
- Price$0.09 / $0.18
- Context1.05M
inclusionAILing 3.0 Flash Fin
63/100- ECI—
- Price$0.075 / $0.22
- Context262K
- Our pickinclusionAI
Ling 3.0 Flash VL
76/100- ECI—
- Price$0.06 / $0.18
- Context262K
Ling 3.0 Flash VL is our pick
Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Laguna S 2.1 (68) and Ling 3.0 Flash Fin (63). It leads on price and inputs & features. Laguna S 2.1 wins on context window. 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 priceLing 3.0 Flash VLLing 3.0 Flash VL $0.09 · Ling 3.0 Flash Fin $0.111 · Laguna S 2.1 $0.113 per 1M tokens (3:1 blend)
- Longest contextLaguna S 2.1Laguna S 2.1 1,048,576 · Ling 3.0 Flash Fin 262,144 · Ling 3.0 Flash VL 262,144 tokens
- Widest inputsLing 3.0 Flash VLLaguna S 2.1: Text · Ling 3.0 Flash Fin: Text · Ling 3.0 Flash VL: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Laguna S 2.1 | Ling 3.0 Flash Fin | Ling 3.0 Flash VL |
|---|---|---|---|---|
| Price | 50% | 91 | 91 | 95 |
| Inputs & features | 30% | 35 | 35 | 70 |
| Context window | 20% | 61 | 37 | 37 |
| Overall | 100% | 68/100 | 63/100 | 76/100 |
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 | Laguna S 2.1Poolside | Ling 3.0 Flash FininclusionAI | Ling 3.0 Flash VLinclusionAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.09 | $0.075 | $0.06 (best) |
| Output | $0.18 (best) | $0.22 | $0.18 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.113 | $0.111 | $0.09 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 2 providers | Median of 7 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 | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenMIT | OpenMIT |
| API model ID | poolside/laguna-s-2.1 | — | — |
| API providers | 4 | 3 | 7 (best) |
| Released | Jul 21, 2026 | Aug 27, 2026 | Sep 10, 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$1.26
- Ling 3.0 Flash Fin$1.19
- Ling 3.0 Flash VL$0.96
Which should you choose?
Which is better: Laguna S 2.1, Ling 3.0 Flash Fin or Ling 3.0 Flash VL?
Ling 3.0 Flash VL is the better all-round choice, scoring 76/100 against Laguna S 2.1 (68) and Ling 3.0 Flash Fin (63). It leads on price and inputs & features. Laguna S 2.1 wins on context window. 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, Ling 3.0 Flash Fin or Ling 3.0 Flash VL?
Ling 3.0 Flash VL is cheaper at $0.06 input / $0.18 output per million tokens (median across 7 API providers). Ling 3.0 Flash Fin costs $0.075 input / $0.22 output per million tokens (median across 2 API providers); Laguna S 2.1 costs $0.09 input / $0.18 output per million tokens (median across 2 API providers; free on Poolside). At a typical mix of three input tokens to one output token, that is $0.09 per million tokens for Ling 3.0 Flash VL versus $0.111 for Ling 3.0 Flash Fin (1.2× as much) and $0.113 for Laguna S 2.1 (1.3× 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, Ling 3.0 Flash Fin has not been scored yet and Ling 3.0 Flash VL has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna S 2.1, Ling 3.0 Flash Fin and Ling 3.0 Flash VL 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 3.0 Flash Fin and 262,144 for Ling 3.0 Flash VL. Maximum output per response: Laguna S 2.1 up to 32,768, Ling 3.0 Flash Fin up to 32,768, Ling 3.0 Flash VL up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Laguna S 2.1 accepts text; Ling 3.0 Flash Fin accepts text; Ling 3.0 Flash VL accepts text, images and video. Ling 3.0 Flash VL handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (MIT), so you can self-host them.
Which is newer?
Ling 3.0 Flash VL is the newest, released Sep 10, 2026. Ling 3.0 Flash Fin came out Aug 27, 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 Nov 2, 2026.
