Gemma 3 27B model profile

Evidence snapshot: 2026-09-06

Gemma 3 27B is a Google model profile with a 131,072-token context window. The dated catalog snapshot records text, image modalities and interfaces for prompt caching, structured output, text generation, tool calling, vision.

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to Gemma 2

Gemma 3 27B is a reference profile: Google publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Gemma 3 27B is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.

Gemma 3 27B accepts text and image and returns text. The snapshot records prompt caching, structured output, text generation, tool calling, and vision as capabilities or interfaces.

The dated reference snapshot lists $0.08 input and $0.16 output per million tokens. Cached input is $0.04 per million tokens.

Gemma 3 27B ranked #94 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.

Profile facts

Profile type: Model research profile
Provider or publisher: Google
Context window: 131,072 tokens
Snapshot date: 2026-09-06
Knowledge cutoff: 2024-08-31
Reference catalog ID: google/gemma-3-27b-it

When to pick Gemma 3 27B

Gemma 3 27B is a reference profile: Google publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.

Reach for it when cost is the binding constraint. At $0.08 in and $0.16 out per 1M tokens, combined token price sits in the cheapest quarter of the 146 models publishing both rates in this snapshot.
Reach for it when the input includes images. The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described.
Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.
Look elsewhere when the prompt is long. The 131K-token context window is in the bottom quarter of the 163 models publishing a limit. Long documents need chunking or a wider-context route.

Context, modalities, and identity

Gemma 3 27B accepts text and image and returns text. The snapshot records prompt caching, structured output, text generation, tool calling, and vision as capabilities or interfaces.

Provider or publisher: Google
Context window: 131,072 tokens
Maximum output: 117,964 tokens
Input modalities: text and image
Output modalities: text
Knowledge cutoff: 2024-08-31

Model overview

Reference model ID: google/gemma-3-27b-it
Canonical version: google/gemma-3-27b-it
Hugging Face ID: google/gemma-3-27b-it

Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

Supported parameters: frequency_penalty, logit_bias, logprobs, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

prompt caching
structured output
text generation
tool calling
vision

Dated pricing snapshot

The dated reference snapshot lists $0.08 input and $0.16 output per million tokens. Cached input is $0.04 per million tokens.

These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.

Price date: 2026-09-06
Input: $0.08 per 1M tokens
Cached input: $0.04 per 1M tokens
Output: $0.16 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 4 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints: 3
Best p50 latency: 1.33 s
Best p50 throughput: 25 tok/s
Availability with routing: 99.83% over the sampled window
Availability without routing: 96.05% over the sampled window
Performance date: 2026-09-06

Provider	Quantization	Input / 1M	Output / 1M	Cache read / 1M	Context	p50 latency	p50 throughput	Uptime (1d)
DeepInfra	fp8	$0.08 / 1M	$0.16 / 1M	No verified rate	131,072 tokens	1.66 s	24 tok/s	99.38%
Parasail	fp8	$0.08 / 1M	$0.45 / 1M	$0.04 / 1M	131,072 tokens	1.36 s	21 tok/s	99.40%
NovitaAI	bf16	$0.119 / 1M	$0.2 / 1M	No verified rate	98,304 tokens	1.46 s	25 tok/s	98.55%
Nebius Token Factory	fp8	$0.1 / 1M	$0.3 / 1M	No verified rate	110,000 tokens	1.33 s	12 tok/s	92.79%

Benchmark evidence and limitations

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Coding Index: 10.1

Popularity and market context

Third-party catalog rank: #94
Global market share: Not inferred
Observation date: 2026-09-06

Frequently asked questions

When should I use Gemma 3 27B?

Gemma 3 27B is a reference profile: Google publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when cost is the binding constraint: At $0.08 in and $0.16 out per 1M tokens, combined token price sits in the cheapest quarter of the 146 models publishing both rates in this snapshot. Reach for it when the input includes images: The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr. Look elsewhere when the prompt is long: The 131K-token context window is in the bottom quarter of the 163 models publishing a limit. Long documents need chunking or a wider-context route.

What is Gemma 3 27B?

What context window does Gemma 3 27B have?

The dated profile lists 131,072 tokens of context and up to 117,964 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.

What benchmark evidence is available for Gemma 3 27B?

The 2026-09-06 snapshot includes 1 Artificial Analysis index. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Is Gemma 3 27B available through Kendr?

This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.

Does the popularity rank represent Gemma 3 27B's global market share?

Sources and evidence dates

Gemma 3 27B third-party catalog record (catalog, checked 2026-09-06)
Third-party model catalog methodology (methodology, checked 2026-09-06)
Google official model documentation (primary, checked 2026-09-06)
Artificial Analysis capability indices methodology (benchmark, checked 2026-09-06)