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Gemma 3 27B GPU requirements and hosting.

Google's instruction-tuned Gemma checkpoint supports text and image understanding upstream. The current catalog profile is text chat; image serving needs separate validation.

Sources reviewed 2026-09-30 · B3IQ engineering

Checkpoint overview.

Model creator

Google DeepMind
Task in catalog
Chat / reasoning
Approx. total parameters (catalog)
27B
Runtime families
ollama
Upstream access at review
Access approval or acceptance of terms required
Canonical checkpoint
google/gemma-3-27b-it ↗

The creator identifies the original checkpoint. Runtime profiles may use separately packaged artifacts; their publishers and configuration can differ. Check the selected profile below.

Configuration matters

Choose a runtime profile.

An upstream multimodal capability does not establish that the catalog profile exposes it. The memory figures below apply only to the stated catalog profile.

Catalog GPU threshold
24 GB
Configured context
8,192 tokens
Catalog system RAM
48 GB
Runtime
ollama
Artifact identifier
gemma3:27b
Precision
Not pinned in catalog
Configured concurrency
1 request(s)
Profile inputs / outputs
text → text
Deployed artifact revision
Not verified

Catalog thresholds are configuration guidance, not measured peak memory. A positive GPU requirement is not recorded for every profile; unspecified is not zero. Context, concurrency and runtime overhead can increase memory use. Configured context is a profile setting, not the upstream maximum. Concurrency is configuration, not a load-test result.

Memory components

Account for the whole workload.

ollamagemma3:27b

Stored weights~54 GB16-bit arithmetic only
Context / cacheNot sized8,192 tokens configured · 1 concurrent
Runtime reserveNot sizedActivations, buffers, overhead

Total GPU allocation Not established

Weights = 27 billion parameters × 2 bytes. This reference does not describe the selected artifact’s unrecorded precision. Cache and runtime reserve need the exact workload. Band widths are schematic, not memory shares; the separate 24 GB catalog threshold is guidance. A multi-GPU total needs a supported model split and topology.

Weight-only arithmetic and a planning estimate

Using the catalog's approximate 27B total parameters, 16-bit weights alone occupy about 54 GB (parameters × 2 bytes). The shared sizing helper rounds a 20% planning reserve to 65 GB.

This arithmetic does not describe the selected quantized artifact. It excludes a workload-specific KV-cache calculation and cannot guarantee fit at the configured context or concurrency. A mixture-of-experts model still stores its full weights.

See the assumptions →

Plan the machine.

RTX 5090 machine

Memory-based machine candidate

1× RTX 5090

32 GB total GPU memory · 32 GB per GPU

ollama · gemma3-27b1× 32 GB

24 GB sizing figure · 32 GB installed GPU memory. Remaining capacity is not a measured runtime reserve.

This configuration includes 64 GB system RAM. Memory capacity alone does not establish runtime compatibility, latency or throughput.

View this configuration

Current pricing and availability are shown on the machine page.

Before deployment

Test the workload you need.

For a text workload, compare it with similarly sized text models. For images, test the exact image processor, resolution and runtime path you intend to use.

These are catalog profiles and planning figures. No B3IQ performance measurement or live capacity is claimed. Confirm the artifact, runtime, workload and machine before deployment.

Evidence available

Upstream identity / license
Source reviewed
Runtime settings
Catalog configuration
Memory fit
Guidance; not a measured peak
B3IQ performance
No published benchmark
Installation / live capacity
Confirm for your machine
Read our evidence standard →

Source and access.

Upstream checkpoint
google/gemma-3-27b-it ↗
Upstream license metadata
Gemma Terms of Use ↗
Access
Upstream repository requires access approval or acceptance of terms.

The reviewed revision identifies the source used for this guide. It is not a claim that this revision is installed on a B3IQ machine. Review the publisher's current license and acceptable-use terms for your application.

Guide updates and corrections.

These are changes to the guide. Source-review dates and workload-test evidence are recorded separately.

· Update

Added creator attribution and a canonical checkpoint overview. The guide now explains how the original creator differs from a runtime artifact publisher.

To report a correction, send the affected claim and a source URL to hello@b3iq.org.

Continue your evaluation.

Compare another checkpoint or explore a complementary task. Each guide explains the workload it is intended for.