Gemma 4 26B A4B model profile

Profile facts

Profile type

Model research profile

Provider or publisher

Google

Context window

262,144 tokens

Snapshot date

2026-09-06

Knowledge cutoff

Not disclosed

Reference catalog ID

google/gemma-4-26b-a4b-it

When to pick Gemma 4 26B A4B

Gemma 4 26B A4B 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 $0.042 in and $0.22 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.

Context, modalities, and identity

Gemma 4 26B A4B accepts image, text, and video and returns text. The snapshot records reasoning controls, structured output, text generation, tool calling, video input, and vision as capabilities or interfaces.

Provider or publisher

Google

Context window

262,144 tokens

Maximum output

16,384 tokens

Input modalities

image, text, and video

Output modalities

text

Knowledge cutoff

Not disclosed

Model overview

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at a fraction of the compute cost. Supports multimodal input including text, images, and video (up to 60s at 1fps). Features a 256K token context window, native function calling, configurable thinking/reasoning mode, and structured output support. Released under Apache 2.0.

Reference model ID

google/gemma-4-26b-a4b-it

Canonical version

google/gemma-4-26b-a4b-it-20260403

Hugging Face ID

google/gemma-4-26B-A4B-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, include_reasoning, logit_bias, logprobs, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

• reasoning controls
• structured output
• text generation
• tool calling
• video input
• vision

Dated pricing snapshot

The dated reference snapshot lists $0.042 input and $0.22 output per million tokens. Cached input is $0.05 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

$0.042 per 1M tokens

Cached input

$0.05 per 1M tokens

Output

$0.22 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 9 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints

9

Best p50 latency

0.44 s

Best p50 throughput

50 tok/s

Availability with routing

99.37% over the sampled window

Availability without routing

97.33% over the sampled window

Performance date

2026-09-06

Benchmark evidence and limitations

The 2026-09-06 snapshot includes 1 Artificial Analysis index and AutoExacto results for 11 provider observations. 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.

Coding Index

39.3

AutoExacto coverage

11 provider observations over 32 days

AutoExacto provider benchmarks

Rolling provider observations from the cited third-party benchmark view. The lookback is 32 days; GPQA Diamond and TAU-Bench Airline measure different abilities and should not be blended into one score.

Popularity and market context

Gemma 4 26B A4B ranked #41 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.

Third-party catalog rank

#41

Global market share

Not inferred

Observation date

2026-09-06

Frequently asked questions

Sources and evidence dates

1. Gemma 4 26B A4B third-party catalog record (catalog, checked 2026-09-06)
2. Third-party model catalog methodology (methodology, checked 2026-09-06)
3. Google official model documentation (primary, checked 2026-09-06)
4. Artificial Analysis capability indices methodology (benchmark, checked 2026-09-06)
5. Gemma 4 26B A4B third-party catalog record (benchmark, checked 2026-09-06)