Schematron V2 Turbo vs Trinity Mini vs Gemma 4 E2B IT
Gemma 4 E2B IT comes out ahead, 76 to 65 and 55 on our weighted score, and it is the cheaper option too.
Inference.net
Schematron V2 Turbo
55/100- ECI—
- Price$0.03 / $0.15
- Context128K
Arcee AITrinity Mini
65/100- ECI—
- Price$0.045 / $0.15
- Context131K
- Our pick
GoogleGemma 4 E2B IT
76/100- ECI—
- Price$0.04 / $0.08
- Context131K
Gemma 4 E2B IT is our pick
Gemma 4 E2B IT is the better all-round choice, scoring 76/100 against Trinity Mini (65) and Schematron V2 Turbo (55). 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 priceGemma 4 E2B ITGemma 4 E2B IT $0.05 · Schematron V2 Turbo $0.06 · Trinity Mini $0.071 per 1M tokens (3:1 blend)
- Longest contextTrinity Mini and Gemma 4 E2B ITTrinity Mini 131,072 · Gemma 4 E2B IT 131,072 · Schematron V2 Turbo 128,000 tokens
- Widest inputsGemma 4 E2B ITSchematron V2 Turbo: Text · Trinity Mini: Text · Gemma 4 E2B IT: Text, Images, Audio
- Self-hostingTrinity Mini and Gemma 4 E2B ITPublishes downloadable weights (OpenMDW-1.1)
| Measure | Weight | Schematron V2 Turbo | Trinity Mini | Gemma 4 E2B IT |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 0 | 35 | 70 |
| Context window | 20% | 24 | 25 | 25 |
| Overall | 100% | 55/100 | 65/100 | 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 | Schematron V2 TurboInference.net | Trinity MiniArcee AI | Gemma 4 E2B ITGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.03 (best) | $0.045 | $0.04 |
| Output | $0.15 | $0.15 | $0.08 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.06 | $0.071 | $0.05 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 5 providers | Median of 1 providers | Median of 1 providers |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Max output | 8,192 tokens | 131,072 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | OpenOpenMDW-1.1 | Open |
| API model ID | — | — | — |
| API providers | 5 (best) | 1 | 1 |
| Released | Apr 16, 2026 | Dec 1, 2025 | Apr 2, 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.
- Schematron V2 Turbo$0.60
- Trinity Mini$0.75
- Gemma 4 E2B IT$0.56
Which should you choose?
Which is better: Schematron V2 Turbo, Trinity Mini or Gemma 4 E2B IT?
Gemma 4 E2B IT is the better all-round choice, scoring 76/100 against Trinity Mini (65) and Schematron V2 Turbo (55). 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, Schematron V2 Turbo, Trinity Mini or Gemma 4 E2B IT?
Gemma 4 E2B IT is cheaper at $0.04 input / $0.08 output per million tokens (median across 1 API provider). Schematron V2 Turbo costs $0.03 input / $0.15 output per million tokens (median across 5 API providers); Trinity Mini costs $0.045 input / $0.15 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.05 per million tokens for Gemma 4 E2B IT versus $0.06 for Schematron V2 Turbo (1.2× as much) and $0.071 for Trinity Mini (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Schematron V2 Turbo has not been scored yet, Trinity Mini has not been scored yet and Gemma 4 E2B IT has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Schematron V2 Turbo, Trinity Mini and Gemma 4 E2B IT yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Schematron V2 Turbo does not support tool calling, which most coding agents need.
Which has the bigger context window?
Trinity Mini and Gemma 4 E2B IT have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Schematron V2 Turbo. Maximum output per response: Schematron V2 Turbo up to 8,192, Trinity Mini up to 131,072, Gemma 4 E2B IT up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Schematron V2 Turbo accepts text; Trinity Mini accepts text; Gemma 4 E2B IT accepts text, images and audio. Gemma 4 E2B IT handles the widest range of inputs.
Are any of these open source?
Trinity Mini and Gemma 4 E2B IT publishes its weights (OpenMDW-1.1) and can be self-hosted; Schematron V2 Turbo is proprietary.
Which is newer?
Schematron V2 Turbo is the newest, released Apr 16, 2026. Gemma 4 E2B IT came out Apr 2, 2026; Trinity Mini came out Dec 1, 2025.
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.
