Google: Gemma 4 26B A4B

Gemma 4 26B A4B is a Mixture-of-Experts model from Google, released 2026-04, with 25.2B total parameters and only 3.8B active per token. It handles video up to 60 seconds at 1fps and is instruction-tuned for near-31B quality at a fraction of the compute cost.

Modalities
inImageinTextinVideooutText
Price / 1M
$0.08 / $0.37
Context
262K
Released
Apr 3, 2026

Channels

Every channel serves the same model, but they differ in price and stability. On each API key in the Platform, you pick a primary and a backup channel per vendor, and each billing line shows which channel served the request.

Provider
Discount
Input /M
Output /M
Cache read /M
Cache write 5m /M
Cache write 1h /M
Officialstable
+54%
$0.08
$0.37
$0.08
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Capabilities

ReasoningVisionTool useLong contextPrompt cachingStructured output

Parameters

Request parameters this model accepts through the API.

frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p

Cost calculator

Pick a channel and a usage scenario, then drag the sliders to match your workload. Each scenario assumes a different prompt-cache hit rate.

Channel
Scenario
Unit $0.08 / $0.37 /1MDaily chat: 40% cache hit rate assumed · cache read $0.08 /1M
On MirAPI$25.34/ moCreate an API key

Benchmarks

bar = score (0–100) · ▏ median

Scores come from vendor reports and public leaderboards, not private evals.

Intelligence Index
General ability
16.7
#91
Coding Index
Code
39.3
#59
Agentic Index
Agentic
2.9
#49
GPQA Diamond
Science QA
70.6
#96
τ-bench (airline)
Agentic tool use
69.5
#75

Showcase

Every chat model gets the same three fixed prompts. Outputs are archived verbatim, so you can copy a prompt and reproduce the result.

Task prompt · identical for all models
Build a single-file HTML page using three.js from a CDN: a low-poly planet with a tilted ring of ~200 orbiting particles, a soft key light plus rim light, slow auto-rotation, and drag-to-orbit controls. No build tools — one file only.
Archived output
Archive not published yet

Every model will run this exact prompt, and its output will appear here verbatim with token counts and the cost per run.

Quick start

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.mirapi.ai/v1",   # changed
    api_key=os.environ["MIRAPI_API_KEY"],   # changed
)

resp = client.chat.completions.create(
    model="gemma-4-26b-a4b-it",
    messages=[{"role": "user", "content": "Hello"}],
)
Wire Gemma 4 26B A4B into your product

1M free tokens to start, no card required. It’s OpenAI-compatible, so you only change the base URL.

Start free