Gemma 4 E2B IT vs Laguna XS 2.1 vs Qwen3.5 Flash
Too close to call on our weighted score (Gemma 4 E2B IT 79, Qwen3.5 Flash 79, Laguna XS 2.1 68). The right pick depends on what you value most.
GoogleGemma 4 E2B IT
79/100- ECI—
- Price$0.07 / $0.09
- Context131K
PoolsideLaguna XS 2.1
68/100- ECI—
- Price$0.06 / $0.12
- Context262K
Alibaba (Qwen)Qwen3.5 Flash
79/100- ECI144.0
- Price$0.10 / $0.40
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (Gemma 4 E2B IT 79/100, Qwen3.5 Flash 79/100, Laguna XS 2.1 68/100), so choose by what matters most for your work: Gemma 4 E2B IT on price and Qwen3.5 Flash 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 priceGemma 4 E2B IT and Laguna XS 2.1Gemma 4 E2B IT $0.075 · Laguna XS 2.1 $0.075 · Qwen3.5 Flash $0.175 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 FlashQwen3.5 Flash 1,000,000 · Laguna XS 2.1 262,144 · Gemma 4 E2B IT 131,072 tokens
- Widest inputsGemma 4 E2B IT and Qwen3.5 FlashGemma 4 E2B IT: Text, Images, Audio · Laguna XS 2.1: Text · Qwen3.5 Flash: Text, Images, Video
- Self-hostingGemma 4 E2B IT and Laguna XS 2.1Publishes downloadable weights
| Measure | Weight | Gemma 4 E2B IT | Laguna XS 2.1 | Qwen3.5 Flash |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 86 |
| Inputs & features | 30% | 80 | 35 | 80 |
| Context window | 20% | 24 | 37 | 60 |
| Overall | 100% | 79/100 | 68/100 | 79/100 |
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 | Gemma 4 E2B ITGoogle | Laguna XS 2.1Poolside | Qwen3.5 FlashAlibaba (Qwen) |
|---|---|---|---|
| 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 | $0.07 | $0.06 (best) | $0.10 |
| Output | $0.09 (best) | $0.12 | $0.40 |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.075 (best) | $0.075 (best) | $0.175 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 1 providers | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | poolside/laguna-xs-2.1 | qwen3.5-flash |
| API providers | 2 | 4 | 8 (best) |
| Released | Apr 2, 2026 | Jul 2, 2026 | Feb 23, 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.
- Gemma 4 E2B IT$0.88
- Laguna XS 2.1$0.84
- Qwen3.5 Flash$1.80
Which should you choose?
Which is better: Gemma 4 E2B IT, Laguna XS 2.1 or Qwen3.5 Flash?
It is close. Our weighted score puts them within a point (Gemma 4 E2B IT 79/100, Qwen3.5 Flash 79/100, Laguna XS 2.1 68/100), so choose by what matters most for your work: Gemma 4 E2B IT on price and Qwen3.5 Flash 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, Gemma 4 E2B IT, Laguna XS 2.1 or Qwen3.5 Flash?
Gemma 4 E2B IT is cheaper at $0.07 input / $0.09 output per million tokens (median across 2 API providers). Laguna XS 2.1 costs $0.06 input / $0.12 output per million tokens (median across 1 API provider; free on Poolside); 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 $0.075 per million tokens for Gemma 4 E2B IT versus $0.075 for Laguna XS 2.1 (1× as much) and $0.175 for Qwen3.5 Flash (2.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma 4 E2B IT has not been scored yet, Laguna XS 2.1 has not been scored yet and Qwen3.5 Flash has an ECI of 144.0.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 4 E2B IT, Laguna XS 2.1 and Qwen3.5 Flash 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?
Qwen3.5 Flash has the largest context window at 1,000,000 tokens, against 262,144 for Laguna XS 2.1 and 131,072 for Gemma 4 E2B IT. Maximum output per response: Gemma 4 E2B IT up to 8,192, Laguna XS 2.1 up to 32,768, Qwen3.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemma 4 E2B IT accepts text, images and audio; Laguna XS 2.1 accepts text; Qwen3.5 Flash accepts text, images and video. Gemma 4 E2B IT handles the widest range of inputs.
Are any of these open source?
Gemma 4 E2B IT and Laguna XS 2.1 publishes its weights and can be self-hosted; Qwen3.5 Flash is proprietary.
Which is newer?
Laguna XS 2.1 is the newest, released Jul 2, 2026. Gemma 4 E2B IT came out Apr 2, 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.
