Gemma 4-26B-A4B
Gemma 是一系列生成式人工智能模型，可用于各种生成任务，包括问答、总结和推理。Gemma 模型提供开放权重，并允许负责任的商业用途，让您可以在自己的项目和应用中调整和部署它们。
- Starting price
- Input / Output · 1M
- Context
- —
- Maximum input window
- Modalities
- →
Pricing by Supplier
Capabilities / Supported modalities
Provider & data privacy
SentencePiece (Gemini)Performance
About Gemma 4-26B-A4B
Gemma 是一系列生成式人工智能模型，可用于各种生成任务，包括问答、总结和推理。Gemma 模型提供开放权重，并允许负责任的商业用途，让您可以在自己的项目和应用中调整和部署它们。
Use cases and prompting
Starting points for evaluation; supported inputs and options are listed in API access.
Use cases to explore
- Draft and revise text with explicit audience, tone and format requirements.
- Summarize supplied documents and compare answers against the original sources.
Practical tips
Separate instructions from source material, describe the desired output and provide an example. Test tool use or structured output only when listed as supported.
Example prompt
Summarize the following document in five bullet points. Separate confirmed facts from open questions, cite the relevant passages and do not invent missing information. Document: [paste your text]
API access
Code samples
/v1/chat/completions| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Replace <YOUR_API_KEY> with the API key from your token settings.
Authentication
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
Supported parameters
| Parameter | Type | Default / range | Description |
|---|---|---|---|
temperature | number | = 10 ~ 2 | Sampling temperature; lower is more deterministic |
top_p | number | = 10 ~ 1 | Nucleus sampling probability mass |
max_tokens | integer | >= 1 | Maximum number of tokens in the response |
frequency_penalty | number | = 0-2 ~ 2 | Penalises repetition of frequent tokens |
presence_penalty | number | = 0-2 ~ 2 | Encourages introducing new topics |
stop | array | — | Up to 4 strings that stop generation |
seed | integer | — | Deterministic sampling seed (best-effort) |
n | integer | = 1>= 1 | Number of completions to generate |
stream | boolean | = false | Stream tokens via Server-Sent Events |
response_format | object | — | Force JSON object or schema-conforming output |
tools | array | — | Tool / function declarations the model may call |
tool_choice | string | autononerequired | Tool-choice policy or specific tool name |
logprobs | boolean | = false | Return per-token log probabilities |
top_logprobs | integer | 0 ~ 20 | Number of top log probabilities returned per token |
logit_bias | object | — | Per-token logit bias map |
user | string | — | End-user identifier for abuse monitoring |
Rate limits
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| official | 460 | 184K | 9.2K |
RPM = requests per minute, TPM = tokens per minute, RPD = requests per day. Limits apply per token group.
Frequently asked questions about Gemma 4-26B-A4B
What is Gemma 4-26B-A4B?
Gemma 是一系列生成式人工智能模型，可用于各种生成任务，包括问答、总结和推理。Gemma 模型提供开放权重，并允许负责任的商业用途，让您可以在自己的项目和应用中调整和部署它们。
How do I call Gemma 4-26B-A4B?
Create an API key with access to Gemma 4-26B-A4B, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
How is Gemma 4-26B-A4B priced?
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
How should I evaluate Gemma 4-26B-A4B for my project?
Separate instructions from source material, describe the desired output and provide an example. Test tool use or structured output only when listed as supported.