Laguna S 2.1 vs Qwen3.5 Flash vs Gemma 4 12B IT
Qwen3.5 Flash comes out ahead, 79 to 75 and 69 on our weighted score, though Laguna S 2.1 is 29% cheaper per token.
PoolsideLaguna S 2.1
69/100- ECI—
- Price$0.10 / $0.20
- Context1.05M
- Our pick
Alibaba (Qwen)Qwen3.5 Flash
79/100- ECI144.0
- Price$0.10 / $0.40
- Context1M
GoogleGemma 4 12B IT
75/100- ECI—
- Price$0.075 / $0.275
- Context262K
Qwen3.5 Flash is our pick
Qwen3.5 Flash is the better all-round choice, scoring 79/100 against Gemma 4 12B IT (75) and Laguna S 2.1 (69). 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 S 2.1 and Gemma 4 12B ITLaguna S 2.1 $0.125 · Gemma 4 12B IT $0.125 · Qwen3.5 Flash $0.175 per 1M tokens (3:1 blend)
- Longest contextLaguna S 2.1Laguna S 2.1 1,048,576 · Qwen3.5 Flash 1,000,000 · Gemma 4 12B IT 262,144 tokens
- Widest inputsQwen3.5 FlashLaguna S 2.1: Text · Qwen3.5 Flash: Text, Images, Video · Gemma 4 12B IT: Text, Images
- Self-hostingLaguna S 2.1 and Gemma 4 12B ITPublishes downloadable weights
| Measure | Weight | Laguna S 2.1 | Qwen3.5 Flash | Gemma 4 12B IT |
|---|---|---|---|---|
| Price | 50% | 93 | 86 | 93 |
| Inputs & features | 30% | 35 | 80 | 70 |
| Context window | 20% | 61 | 60 | 37 |
| Overall | 100% | 69/100 | 79/100 | 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 | Qwen3.5 FlashAlibaba (Qwen) | Gemma 4 12B ITGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 144.0 | — |
| ECI rank | — | #82 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 82.3% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 18.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 84.4% | — |
| SimpleQA VerifiedShort factual questions | — | 20.3% | — |
| Price per million tokens | |||
| Input | $0.10 | $0.10 | $0.075 (best) |
| Output | $0.20 (best) | $0.40 | $0.275 |
| Cached input | — | $0.01 | — |
| Blended (3:1) | $0.125 (best) | $0.175 | $0.125 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 4 providers | Official Alibaba 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 | 65,536 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 | Yes | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | poolside/laguna-s-2.1 | qwen3.5-flash | — |
| API providers | 6 | 8 (best) | 2 |
| Released | Jul 21, 2026 | Feb 23, 2026 | Jun 9, 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
- Qwen3.5 Flash$1.80
- Gemma 4 12B IT$1.30
Which should you choose?
Which is better: Laguna S 2.1, Qwen3.5 Flash or Gemma 4 12B IT?
Qwen3.5 Flash is the better all-round choice, scoring 79/100 against Gemma 4 12B IT (75) and Laguna S 2.1 (69). 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, Laguna S 2.1, Qwen3.5 Flash 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); Qwen3.5 Flash costs $0.10 input / $0.40 output per million tokens (official Alibaba 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 $0.175 for Qwen3.5 Flash (1.4× 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, Qwen3.5 Flash has an ECI of 144.0 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, Qwen3.5 Flash 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 Qwen3.5 Flash and 262,144 for Gemma 4 12B IT. Maximum output per response: Laguna S 2.1 up to 32,768, Qwen3.5 Flash up to 65,536, Gemma 4 12B IT up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Laguna S 2.1 accepts text; Qwen3.5 Flash accepts text, images and video; Gemma 4 12B IT accepts text and images. Qwen3.5 Flash 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; Qwen3.5 Flash is proprietary.
Which is newer?
Laguna S 2.1 is the newest, released Jul 21, 2026. Gemma 4 12B IT came out Jun 9, 2026; Qwen3.5 Flash came out Feb 23, 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.
