Laguna S 2.1 vs Viv Fast vs Gemma 4 12B IT
Too close to call on our weighted score (Gemma 4 12B IT 75, Viv Fast 75, Laguna S 2.1 69). The right pick depends on what you value most.
PoolsideLaguna S 2.1
69/100- ECI—
- Price$0.10 / $0.20
- Context1.05M
VivgridViv Fast
75/100- ECI—
- Price$0.13 / $0.40
- Context1M
GoogleGemma 4 12B IT
75/100- ECI—
- Price$0.075 / $0.275
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Gemma 4 12B IT 75/100, Viv Fast 75/100, Laguna S 2.1 69/100), so choose by what matters most for your work: Laguna S 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 S 2.1 and Gemma 4 12B ITLaguna S 2.1 $0.125 · Gemma 4 12B IT $0.125 · Viv Fast $0.198 per 1M tokens (3:1 blend)
- Longest contextLaguna S 2.1Laguna S 2.1 1,048,576 · Viv Fast 1,000,000 · Gemma 4 12B IT 262,144 tokens
- Widest inputsViv Fast and Gemma 4 12B ITLaguna S 2.1: Text · Viv Fast: Text, Images · Gemma 4 12B IT: Text, Images
- Self-hostingLaguna S 2.1 and Gemma 4 12B ITPublishes downloadable weights
| Measure | Weight | Laguna S 2.1 | Viv Fast | Gemma 4 12B IT |
|---|---|---|---|---|
| Price | 50% | 93 | 83 | 93 |
| Inputs & features | 30% | 35 | 70 | 70 |
| Context window | 20% | 61 | 60 | 37 |
| Overall | 100% | 69/100 | 75/100 | 75/100 |
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 | Viv FastVivgrid | Gemma 4 12B ITGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 | $0.13 | $0.075 (best) |
| Output | $0.20 (best) | $0.40 | $0.275 |
| Cached input | — | $0.05 | — |
| Blended (3:1) | $0.125 (best) | $0.198 | $0.125 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Official Vivgrid API | Median of 2 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,000,000 tokens | 262,144 tokens |
| Max output | 32,768 tokens | 256,000 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · high · max | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | poolside/laguna-s-2.1 | viv-fast | — |
| API providers | 6 (best) | 1 | 2 |
| Released | Jul 21, 2026 | Sep 21, 2026 | Jun 9, 2026 |
| Knowledge cutoff | — | Sep 2026 | — |
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
- Viv Fast$2.10
- Gemma 4 12B IT$1.30
Which should you choose?
Which is better: Laguna S 2.1, Viv Fast or Gemma 4 12B IT?
It is close. Our weighted score puts them within a point (Gemma 4 12B IT 75/100, Viv Fast 75/100, Laguna S 2.1 69/100), so choose by what matters most for your work: Laguna S 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, Viv Fast or Gemma 4 12B IT?
Laguna S 2.1 is cheaper at $0.10 input / $0.20 output per million tokens (median across 4 API providers; free on Poolside). Gemma 4 12B IT costs $0.075 input / $0.275 output per million tokens (median across 2 API providers); Viv Fast costs $0.13 input / $0.40 output per million tokens (official Vivgrid API price). At a typical mix of three input tokens to one output token, that is $0.125 per million tokens for Laguna S 2.1 versus $0.125 for Gemma 4 12B IT (1× as much) and $0.198 for Viv Fast (1.6× 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, Viv Fast has not been scored yet and Gemma 4 12B IT has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna S 2.1, Viv Fast and Gemma 4 12B IT 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 1,000,000 for Viv Fast and 262,144 for Gemma 4 12B IT. Maximum output per response: Laguna S 2.1 up to 32,768, Viv Fast up to 256,000, Gemma 4 12B IT up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Laguna S 2.1 accepts text; Viv Fast accepts text and images; Gemma 4 12B IT accepts text and images. Viv Fast handles the widest range of inputs.
Are any of these open source?
Laguna S 2.1 and Gemma 4 12B IT publishes its weights and can be self-hosted; Viv Fast is proprietary.
Which is newer?
Viv Fast is the newest, released Sep 21, 2026. Laguna S 2.1 came out Jul 21, 2026; Gemma 4 12B IT came out Jun 9, 2026. Knowledge cutoff: Viv Fast Sep 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.
