DiffusionGemma 26B A4B IT vs Gemma 4 E2B IT vs Schematron V2 Turbo
Too close to call on our weighted score (Gemma 4 E2B IT 76, DiffusionGemma 26B A4B IT 75, Schematron V2 Turbo 55). The right pick depends on what you value most.
GoogleDiffusionGemma 26B A4B IT
75/100- ECI—
- Price$0.05 / $0.15
- Context262K
- Google
Gemma 4 E2B IT
76/100- ECI—
- Price$0.04 / $0.08
- Context131K
Inference.net
Schematron V2 Turbo
55/100- ECI—
- Price$0.03 / $0.15
- Context128K
Too close to call
It is close. Our weighted score puts them within 1 points (Gemma 4 E2B IT 76/100, DiffusionGemma 26B A4B IT 75/100, Schematron V2 Turbo 55/100), so choose by what matters most for your work: Gemma 4 E2B IT on price and DiffusionGemma 26B A4B IT 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 ITGemma 4 E2B IT $0.05 · Schematron V2 Turbo $0.06 · DiffusionGemma 26B A4B IT $0.075 per 1M tokens (3:1 blend)
- Longest contextDiffusionGemma 26B A4B ITDiffusionGemma 26B A4B IT 262,144 · Gemma 4 E2B IT 131,072 · Schematron V2 Turbo 128,000 tokens
- Widest inputsGemma 4 E2B ITDiffusionGemma 26B A4B IT: Text, Images · Gemma 4 E2B IT: Text, Images, Audio · Schematron V2 Turbo: Text
- Self-hostingDiffusionGemma 26B A4B IT and Gemma 4 E2B ITPublishes downloadable weights (Apache 2.0)
| Measure | Weight | DiffusionGemma 26B A4B IT | Gemma 4 E2B IT | Schematron V2 Turbo |
|---|---|---|---|---|
| Price | 50% | 99 | 100 | 100 |
| Inputs & features | 30% | 60 | 70 | 0 |
| Context window | 20% | 37 | 25 | 24 |
| Overall | 100% | 75/100 | 76/100 | 55/100 |
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 | DiffusionGemma 26B A4B ITGoogle | Gemma 4 E2B ITGoogle | Schematron V2 TurboInference.net |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.05 | $0.04 | $0.03 (best) |
| Output | $0.15 | $0.08 (best) | $0.15 |
| Cached input | — | — | — |
| Blended (3:1) | $0.075 | $0.05 (best) | $0.06 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers | Median of 5 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 131,072 tokens | 128,000 tokens |
| Max output | 32,768 tokens (best) | 8,192 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Proprietary |
| API model ID | — | — | — |
| API providers | 2 | 1 | 5 (best) |
| Released | Jun 9, 2026 | Apr 2, 2026 | Apr 16, 2026 |
| Knowledge cutoff | Jan 2025 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DiffusionGemma 26B A4B IT$0.80
- Gemma 4 E2B IT$0.56
- Schematron V2 Turbo$0.60
Which should you choose?
Which is better: DiffusionGemma 26B A4B IT, Gemma 4 E2B IT or Schematron V2 Turbo?
It is close. Our weighted score puts them within 1 points (Gemma 4 E2B IT 76/100, DiffusionGemma 26B A4B IT 75/100, Schematron V2 Turbo 55/100), so choose by what matters most for your work: Gemma 4 E2B IT on price and DiffusionGemma 26B A4B IT 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, DiffusionGemma 26B A4B IT, Gemma 4 E2B IT or Schematron V2 Turbo?
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); DiffusionGemma 26B A4B IT costs $0.05 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 $0.075 for DiffusionGemma 26B A4B IT (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DiffusionGemma 26B A4B IT has not been scored yet, Gemma 4 E2B IT has not been scored yet and Schematron V2 Turbo has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for DiffusionGemma 26B A4B IT, Gemma 4 E2B IT and Schematron V2 Turbo 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?
DiffusionGemma 26B A4B IT has the largest context window at 262,144 tokens, against 131,072 for Gemma 4 E2B IT and 128,000 for Schematron V2 Turbo. Maximum output per response: DiffusionGemma 26B A4B IT up to 32,768, Gemma 4 E2B IT up to 8,192, Schematron V2 Turbo up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DiffusionGemma 26B A4B IT accepts text and images; Gemma 4 E2B IT accepts text, images and audio; Schematron V2 Turbo accepts text. Gemma 4 E2B IT handles the widest range of inputs.
Are any of these open source?
DiffusionGemma 26B A4B IT and Gemma 4 E2B IT publishes its weights (Apache 2.0) and can be self-hosted; Schematron V2 Turbo is proprietary.
Which is newer?
DiffusionGemma 26B A4B IT is the newest, released Jun 9, 2026. Schematron V2 Turbo came out Apr 16, 2026; Gemma 4 E2B IT came out Apr 2, 2026. Knowledge cutoff: DiffusionGemma 26B A4B IT Jan 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.
