How much does Gemma 3 12B cost?

Gemma 3 12B costs $0.05/M input tokens and $0.15/M output tokens.

What is the context length of Gemma 3 12B?

Gemma 3 12B has a 131,072 token context window. It supports up to 16,384 completion tokens.

Does Gemma 3 12B support tool calling and structured outputs?

Yes. Gemma 3 12B accepts tools and tool_choice for function calling on 1 of the 2 providers serving it, and requests that send tools are routed to those providers. It also supports structured outputs via a JSON schema in response_format.

What inputs and outputs does Gemma 3 12B support?

Gemma 3 12B accepts text and images as input and returns text.

Which providers serve Gemma 3 12B?

Gemma 3 12B is served by 2 providers on OpenRouter: DeepInfra and NextBit. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

When was Gemma 3 12B released?

Gemma 3 12B was released on March 13, 2025. Its knowledge cutoff is August 31, 2024.

Google: Gemma 3 12B

google/gemma-3-12b-it

Model weights

Compare

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 12B is the second largest in the family of Gemma 3 models after Gemma 3 27B

Modalities

In / out price

$0.05 / $0.15per 1M

Context

131K

Released

Mar 13, 2025

Knowledge cutoff

Aug 2024

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Latency / throughput


	$0.05	$0.15	--	0.51s	50 tok/s	92.65%
Priority	$0.075	$0.225	--	1.00s	51 tok/s	91.66%
	$0.075	$0.15	$0.05	1.62s	55 tok/s	99.96%
Not used in Standard routing:Why these endpoints are not used
Flex	$0.04	$0.12	--	1.26s	26 tok/s	0.00%

Input $0.05Output $0.15
50 tok/s92.65% uptime
Input $0.075Output $0.225
Priority
51 tok/s91.66% uptime
Input $0.075Output $0.15
55 tok/s99.96% uptime
Not used in Standard routing:Why these endpoints are not used
Input $0.04Output $0.12
Flex
26 tok/s0.00% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.05504/M tokens

Output

$0.1522/M tokens

Gemma 3 12B — Price history

Price history

No effective price data for this selection

		$0.0487	$0.1392	0.0%	65.5%
		$0.0676	$0.1490	28.1%	23.2%
	Priority	$0.0744	$0.2220	0.0%	10.4%
Not used in Standard routing:Why these endpoints are not used
	Flex	$0.0394	$0.0995	0.0%	0.9%

Effective in $0.0487Effective out $0.1392
Token share
65.5%
Effective in $0.0676Effective out $0.1490
Token share
23.2%
Effective in $0.0744Effective out $0.2220
PriorityToken share
10.4%
Not used in Standard routing:Why these endpoints are not used
Effective in $0.0394Effective out $0.0995
FlexToken share
0.9%

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

97.13%

Availability over the last 3 days

Last 72 hours

Availability 97.13%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.06%

Without Routing

80.49%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Google: Gemma 3 12B (Artificial Analysis)
Source	Benchmark	Score
Artificial Analysis	Gemma 3 12B Instruct Coding Index	5.8
Artificial Analysis	Gemma 3 12B Instruct Agentic Index	0.1
Artificial Analysis	Gemma 3 12B Instruct GPQA Diamond	34.9%
Artificial Analysis	Gemma 3 12B Instruct HLE	4.2%
Artificial Analysis	Gemma 3 12B Instruct IFBench	36.7%
Artificial Analysis	Gemma 3 12B Instruct τ²-Bench Telecom	10.8%
Artificial Analysis	Gemma 3 12B Instruct AA-LCR	8.3%
Artificial Analysis	Gemma 3 12B Instruct τ-Bench Banking	0.8%
Artificial Analysis	Gemma 3 12B Instruct GDPval-AA	0.0%
Artificial Analysis	Gemma 3 12B Instruct CritPt	0.0%
Artificial Analysis	Gemma 3 12B Instruct LiveCodeBench	13.7%
Artificial Analysis	Gemma 3 12B Instruct SciCode	16.4%
Artificial Analysis	Gemma 3 12B Instruct Terminal-Bench Hard	0.8%
Artificial Analysis	Gemma 3 12B Instruct Terminal-Bench 4.0	0.0%
Artificial Analysis	Gemma 3 12B Instruct Terminal-Bench 2.1	0.0%
Artificial Analysis	Gemma 3 12B Instruct MMLU-Pro	59.5%
Artificial Analysis	Gemma 3 12B Instruct AIME 2025	18.3%
Artificial Analysis	Gemma 3 12B Instruct AIME	22.0%
Artificial Analysis	Gemma 3 12B Instruct MATH-500	85.3%

Not currently available through EU in-region routing. In-region routing docs

More models from Google

Gemini 4 Hydrogen

Gemini 4 Hydrogen is the high-efficiency workhorse model of the Gemini 4 family from Google, built for high-throughput agentic workflows, coding and multi-model routing at lower cost and latency than Gemini 4 Carbon. It takes text, image, audio, video and file input, supports long decode of up to 1M output tokens through continuation, and controls thinking depth with low, medium, high and xhigh reasoning effort.

Text1.0M context$1.50 / $7.50

Gemini 4 Hydrogen (batch)

Text1.0M context$0.75 / $3.75

Gemini Decision 1

Gemini Decision 1 is Google's model for the Decisions API. It answers structured questions about an input state (true/false, multiple choice with up to 255 options, and score with up to 255 levels) and returns a confidence for every answer, plus a legend and probabilities for score questions.

It reads text, images, audio, video, and documents (PDF, CSV, and Office files) sent inline as base64 or by public URL. Every question needs instructions.

Decisions$0.10 / $0

Gemini 4 Carbon

Gemini 4 Carbon is a frontier Gemini 4 model from Google for coding, agentic and complex reasoning work. It takes text, image, audio, video and file input, supports long decode of up to 1M output tokens through continuation, and controls thinking depth with low, medium and high reasoning effort.

Text1.0M context$2 / $10

Gemini 4 Carbon (batch)

Text1.0M context$1 / $5

Gemini Omni 1.2 Flash

Gemini Omni 1.2 Flash is Google's native multimodal video generation and editing model, the successor to Gemini Omni 1.1 Flash. It generates clips up to 15 seconds long with native audio in 16:9 or 9:16, from 360p drafts up to 4K, and supports text-to-video, image-to-video, first and last frame interpolation, subject and video references with improved reference management, and editing or extending an uploaded video. Multi-turn editing and extension of a prior generation is supported through previous_job_id.

Note: video generation is only supported through the Video Generation API. See the guide: https://openrouter.ai/docs/guides/overview/multimodal/video-generation

Text131K context$1.50 / $9

Gemini Omni 1.1 Flash

Gemini Omni 1.1 Flash is Google's native multimodal video generation and editing model, the generally available successor to Gemini Omni Flash Preview. It is suited for text-to-video, image-to-video, first and last frame interpolation, subject and video references (up to three reference clips), and editing or extending an uploaded video, and generates clips from 360p drafts up to 4K with native audio in 16:9 or 9:16. Multi-turn editing and extension of a prior generation is supported through previous_job_id, up to 40 seconds of total video.

Note: video generation is only supported through the Video Generation API. See the guide: https://openrouter.ai/docs/guides/overview/multimodal/video-generation

Text131K context$1.50 / $9

Gemini 4 Argon

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

Text1.0M context$2 / $10

Gemini 4 Argon (batch)

Text1.0M context$1 / $5

Nano Banana 2.1

Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization, mask- and ink-based editing, and factual accuracy, and renders photorealistic skin tones, detailed materials, lighting, and coherent backgrounds. It accepts text and image inputs, returns images with optional text, and supports 1K, 2K, and 4K output plus extended aspect ratios via the image_config API Parameter.

Image66K context$1.50 / $30

Gemini 3.5 Transcribe

Gemini 3.5 Transcribe is a speech-to-text model from Google. It is suited for synchronous transcription that needs word-level timestamps or speaker diarization, with support for up to eight speakers. Audio can be up to one hour, or 30 minutes when timestamps or diarization are enabled.

Transcription$2 / $12

Gemini 3.8 Flash Lite TTS

Gemini 3.8 Flash Lite TTS is a text-to-speech model from Google and the fast, high-throughput member of the 3.8 TTS family alongside Gemini 3.8 Flash TTS. It is suited for conversational voice-agent pipelines, high-volume read-aloud, and voice replication workloads where latency and cost matter more than maximum expressiveness.

It accepts the same speech configuration as Gemini 3.1 Flash TTS Preview, including the 30 prebuilt studio voices, and supports Google's Voice Design and Voice Replication through voice_... identifiers.

Speech$0.50 / $6

Gemini 3.8 Flash TTS

Gemini 3.8 Flash TTS is a text-to-speech model from Google and the successor to Gemini 3.1 Flash TTS Preview. It is the creative tier of the 3.8 TTS family, suited for narration, character work, and multi-speaker dialogue where voice fidelity, acting nuance, and regional dialect coverage matter more than latency.

It accepts the same speech configuration as its predecessor, including the 30 prebuilt studio voices, and supports Google's Voice Design (custom voices from a text description) and Voice Replication (voices cloned from a short sample) through voice_... identifiers.

Speech$0.50 / $9

Gemini 3.8 Flash

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Text1.0M context$0.75 / $3.75

Gemini 3.8 Flash (batch)

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Text1.0M context$0.375 / $1.875

Gemini 3.7 Flash

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step problem solving.

Text1.0M context$0.75 / $3.75

Gemini 3.7 Flash (batch)

Text1.0M context$0.375 / $1.875

Gemini 3.6 Flash

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and less hedging, while reducing token use and the number of model calls needed to complete a task.

Text1.0M context$0.75 / $3.75

Gemini 3.6 Flash (batch)

Text1.0M context$0.375 / $1.875

Gemini 3.5 Flash Lite

Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.

Text1.0M context$0.30 / $2.50

Google: Gemma 3 12B

Providers