LLM Reference

Gemma 4 12B IT

Released
2026-06-03
Last refreshed
2026-06-29
Status
Researched 38d ago
Open sourceCommercial use: permittedMultimodalCodingRAGAgentsLong contextVisionClassificationJSON / Tool useopen-sourcemultimodal

Gemma 4 12B IT is worth evaluating for coding, rag, and agents when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding, rag, and agents
  • Workloads that can use a 256k context window
  • Buyers comparing 2 tracked provider routes

Do not use it for

  • Workloads where another current model has stronger sourced task evidence
Specifications
Family
Gemma 4
Released
2026-06-03
Context
256k
Parameters
12B
Architecture
Decoder Only
Knowledge cutoff
2025-01
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Weights
Available
Code
Unknown
Training
Fine-tuned
Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website
Pricing
Output / 1M
-
Input / 1M
-

Cheapest of 2 routes · Hugging Face Inference Endpoints

About

Instruction-tuned version of Gemma 4 12B. Open weight (Apache 2.0), 12B parameters, encoder-free multimodal (text, image, audio). Optimized for chat and instruction-following. Runs on a 16GB laptop.

Gemma 4 12B IT is an open-source model in the Gemma 4 family. The structured metadata tracks a 256k-token context window, multimodal input, audio, reasoning, function calling, tool use, and structured outputs. This page tracks provider routes through Hugging Face Inference Endpoints and Kaggle Models. Headline tracked benchmarks include Google-Proof Q&A 78.8, MMLU PRO 77.2, and LiveCodeBench 72.0.

Top use-case fit: coding, agents, and build tasks

Coding

1 relevant benchmark in the decision map.

RAG

Included by capability and metadata signals in the decision map.

Agents

Included by capability and metadata signals in the decision map.

Provider price ladder

Compare all 2

Compare API pricing across 2 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Hugging Face Inference Endpoints--
Partial
Kaggle Models--
Partial

Capabilities

VisionMultimodalReasoningFunction CallingTool UseStructured OutputsAudioFine-tuning

Benchmark peer barsfor Coding

Benchmark scores(4)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
Google-Proof Q&A78.8DiamondObserved 2026-06-03Source
MMLU PRO77.2MMLU ProObserved 2026-06-03Source
LiveCodeBench72.0v6 pass@1Observed 2026-06-03Source
AIME 202677.5no tools / no calculatorObserved 2026-06-03Source

Migration checks

No linked migration route is available for this model yet.

Frequently asked questions

What is the context window of Gemma 4 12B IT?

Gemma 4 12B IT has a context window of 256k tokens.

When was Gemma 4 12B IT released?

Gemma 4 12B IT was released on 2026-06-03.

Which providers offer Gemma 4 12B IT?

Gemma 4 12B IT is available from 2 providers: Hugging Face Inference Endpoints, Kaggle Models.

What benchmarks has Gemma 4 12B IT been tested on?

Gemma 4 12B IT has been evaluated on 4 benchmarks, including Google-Proof Q&A, MMLU PRO, LiveCodeBench, AIME 2026.