> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.empiriolabs.ai/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.empiriolabs.ai/_mcp/server. # Gemma 4 26B-A4B > Gemma 4 26B A4B is a Google open multimodal model with 256K context, text, image, and video input, tools, and structured output. ![Gemma 4 26B-A4B](https://media.empiriolabs.ai/model-logos/gemma.png) [Google](/providers/google) · Text Generation `POST /v1/chat/completions` Gemma 4 26B A4B is a Google open multimodal model with 256K context, text, image, and video input, tools, and structured output. ## At a glance | Field | Value | | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------- | | Model id | `gemma-4-26b-a4b` | | Model release date | 2026-03-31 | | Input modalities | Text, Image, Video | | Output modalities | Text | | Context window | 256K | | Weight precision | FP8 weights + FP8 KV | | Max output tokens | 32,768 | | Features | reasoning, vision, video, function\_calling, cache, multimodal, json\_mode, logprobs | | Native inference | Yes | | New | No | | Structured output | JSON Schema | | Supported endpoints | `POST /v1/chat/completions`, `POST /v1/responses`, `POST /v1/messages`, `POST /v1/completions`, `POST /v1beta/models/gemma-4-26b-a4b:generateContent` | | Alternate model ids | `gemma-4-26b-a4b-it`, `google/gemma-4-26b-a4b`, `google/gemma-4-26b-a4b-it` | ## Pricing | Charge | Spec | Rate | | ------------------- | -------------------------- | -------------------- | | Input | per 1M prompt tokens | \$0.05 (was \$0.15) | | Output | per 1M generated tokens | \$0.29 (was \$0.50) | | Implicit cache read | per 1M cached input tokens | \$0.025 (was \$0.15) | | Web Search (Linkup) | per call when invoked | \$0.013 | ## Example request ```bash curl https://api.empiriolabs.ai/v1/chat/completions \ -H 'Authorization: Bearer $EMPIRIOLABS_API_KEY' \ -H 'Content-Type: application/json' \ -d '{"model": "gemma-4-26b-a4b", "messages": [{"role":"user","content":"Hello"}]}' ``` ## Parameters | Parameter | Type | Required | Default | Description | | -------------------- | ------- | -------- | ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `temperature` | number | no | `1.0` | Sampling temperature. Lower values are more deterministic. · Range: 0 – 2 | | `top_p` | number | no | `0.95` | Nucleus sampling probability mass. · Range: 0 – 1 | | `max_tokens` | integer | no | `4096` | Maximum output tokens. · Range: 1 – 32768 | | `stop` | string | no | - | One or more stop strings. | | `reasoning_effort` | enum | no | `"medium"` | Reasoning effort. none disables thinking; low, medium, high, and max set bounded thinking budgets. · Allowed: `none`, `low`, `medium`, `high`, `max` | | `enable_thinking` | boolean | no | true | Enable the model reasoning channel before final output. | | `thinking_budget` | integer | no | `4096` | Maximum thinking tokens before the final answer. If max\_tokens is lower, the service reserves room for the answer. · Range: 128 – 32768 | | `top_k` | integer | no | `20` | Limit sampling to the top K candidate tokens when supported. · Range: 1 – 200 | | `min_p` | number | no | `0` | Minimum probability threshold for token sampling. · Range: 0 – 1 | | `presence_penalty` | number | no | `0` | Penalty for tokens that already appeared in the generated text. · Range: -2 – 2 | | `frequency_penalty` | number | no | `0` | Penalty based on how often a token has already appeared. · Range: -2 – 2 | | `repetition_penalty` | number | no | `1` | Higher values discourage repeated phrasing. · Range: 0.1 – 2 | | `seed` | integer | no | - | Optional random seed for reproducible sampling. · Range: 0 – 2147483647 | | `logprobs` | boolean | no | false | Return token log probabilities when supported. | | `top_logprobs` | integer | no | - | Return up to this many top token log probabilities. · Range: 0 – 20 | | `logit_bias` | object | no | - | Bias token IDs by adding positive or negative values before sampling. | | `tools` | array | no | - | OpenAI-compatible function tool definitions. | | `tool_choice` | object | no | - | OpenAI-compatible function tool selection. | | `stream` | boolean | no | false | Stream response deltas using server-sent events. | | `response_format` | enum | no | - | Constrain the output to JSON. Use JSON mode for any valid JSON object, or JSON schema to force output that matches a schema you provide. | | `web_search_linkup` | boolean | no | false | Optional web search powered by Linkup. When enabled, recent web sources are retrieved using your latest user message as the query and provided to the model as additional context. Adds \$0.013 per call when invoked on top of the model's normal token cost. Disabled by default. | | `disable_formatting` | boolean | no | false | When enabled, the gateway will not append the "Sources" footer to assistant responses that used Linkup web search. Useful when the model output is piped to another system that expects no decoration. | ## Notes Supports text, image, and video input, streaming, function tools, structured JSON output, seed control, and thinking mode on by default. Use reasoning\_effort or thinking\_budget for bounded thinking, or enable\_thinking=false for direct answers. Automatic cache reads are billed at the cached-input rate when reported by the model service. Explicit cache controls are not supported. --- *Machine-readable schema:* `GET https://api.empiriolabs.ai/v1/models/gemma-4-26b-a4b`.