ModelRefs / Gemma 3 27B by Google — Benchmarks, Pricing & Review (2026)

Gemma 3 27B by Google — Benchmarks, Pricing & Review (2026)

Gemma 3 27B (Google): Gemma 3 27B by Google.. 128K context. Pricing: from $0.00010/1K in. Specs, benchmarks and code examples.

What this reference supports

Gemma 3 27B is the largest model of Google's open-weight Gemma 3 family, supporting text and image input for self-hosted and managed deployments. Open-weight results depend on the exact runtime, precision, and prompt template, and the Gemma license and acceptable-use terms must be reviewed before commercial use.

Gemma 3 27B is attributed to Google in ModelRefs' canonical registry. Tracked modalities: Text input and output, Image input. Primary use cases considered on ModelRefs: Self-hosted or managed open-weight deployment where data control and customization matter; Vision-enabled tasks on controllable infrastructure.

This ModelRefs profile is Provisional and pending review — decision-support material, not a final or universal ranking. Confirm current behavior, access, pricing, limits, licensing, and lifecycle in Google's own documentation, and evaluate Gemma 3 27B on representative workloads before implementation.

Benchmark & Evaluation

ModelRefs currently has partial, narrow benchmark coverage for Gemma 3 27B. Treat the available benchmark evidence as one input to the decision, not a guarantee that Gemma 3 27B is the strongest option for your workload, and evaluate it on representative workloads before selecting it.

  • No benchmark score is imported into this editorial record. Canonical benchmark runs and scores are governed separately with their own provenance and render only through those records; coverage in ModelRefs is currently narrow (partial), so any scored comparison must show its coverage limits.
  • ModelRefs holds canonical run evidence on common-sense/reasoning benchmarks (HellaSwag, WinoGrande); coverage is narrow and runtime-dependent.

Implementation considerations

  • Fix runtime, precision, and quantization explicitly; reference results do not transfer across serving stacks.
  • Review the Gemma license and acceptable-use policy before commercial deployment.
  • Open weights available through Google's Gemma distribution channels and common model hubs (per Google's current documentation).
  • Managed access is also offered via Google Cloud; verify the exact license and terms for your deployment path.

Risks and limitations

  • Open-weight results depend on the exact runtime, precision, quantization, and prompt template; reference results do not transfer automatically.
  • The release-specific license and acceptable-use policy must be reviewed before commercial deployment.

Source coverage

This reference is Provisional. Model behavior, access, pricing, limits, licensing, and lifecycle can change; verify the linked provider documentation and run task-specific evaluations before implementation.

Known coverage gaps:

  • Runtime/quantization-specific quality and throughput evidence is not attached.
  • Vision-task reliability needs task-level evaluation.

Sources

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Gemma 3 27B by Google — Benchmarks, Pricing & Review (2026).