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Model Comparison

Gemma 3 27B vs Schematron V2 SmallWhich Is Better in 2026?

Google: Gemma 3 27B logoGoogle•
Inference net

Gemma 3 27B vs Schematron V2 Small: which should you choose in 2026?

Gemma 3 27B (by Google) and Schematron V2 Small (by Inference net) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Schematron V2 Small is about 1.8× cheaper on a blended 3:1 input/output basis ($0.095 vs $0.1725 per 1M tokens).

Choose Gemma 3 27B if…

  • • you need image inputs

Choose Schematron V2 Small if…

  • • lower blended API cost matters for your workload

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

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Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

Gemma 3 27B and Schematron V2 Small benchmark results
BenchmarkGemma 3 27BSchematron V2 Small
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

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BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

——
OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

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SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

——
Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

——
AutoBench

A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench.

Weighted peer-assessment score

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GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

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Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

——
Arena preference scores
Arena (Text)

Human preference score

1365 ±4
—

Benchmark sources

Reviewed evidence last updated 2026-08-09. Arena data last refreshed Sep 12, 2026.

Pricing, capabilities, and model facts

Gemma 3 27B and Schematron V2 Small model facts
FeatureGemma 3 27BSchematron V2 Small
Context & model facts
DeveloperGoogleInference net
API providerGoogleInference.net
Input context131,072 tokens128,000 tokens
Maximum output117,964 tokens4,096 tokens
Released——
Added to WritingmateMar 12, 2025Sep 12, 2026
LicenseNot availableNot available
Knowledge cutoff2024-08-31—
Capabilities
InputsText, ImageText
OutputsTextText
Provider endpoint accepts tool parametersYesNo
ReasoningNoNo
VisionYesNo
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$0.08$0.05
Output (per 1M tokens)$0.45$0.23
Blended 3:1 input/output$0.1725$0.095
API performance
p95 latencyNot measuredNot measured
Output throughputNot measuredNot measured
Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

Data sources

  • Writingmate model catalog (pricing, limits, and availability)

Catalog data last updated Sep 12, 2026.

Why Pay for Multiple Subscriptions?

Comparing Gemma 3 27B from Google with Schematron V2 Small from Inference net? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for Gemma 3 27B and Schematron V2 Small
PlanPriceGemma 3 27BSchematron V2 SmallAI ImagesAI Video
Writingmate Pro
Most popular
$20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
Writingmate Ultimate
Power users
$60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
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Gemma 3 27B vs Schematron V2 Small FAQ

Which is better, Gemma 3 27B or Schematron V2 Small?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Schematron V2 Small is about 1.8× cheaper on a blended 3:1 input/output basis ($0.095 vs $0.1725 per 1M tokens).

Which model is cheaper to use through an API?

Schematron V2 Small is about 1.8× cheaper on a blended 3:1 input/output basis ($0.095 vs $0.1725 per 1M tokens).

Which model supports more context?

The published context windows are close enough that this page does not treat the difference as a material advantage.

Can I switch between Gemma 3 27B and Schematron V2 Small?

Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.