Model profile
Google

Google: Lyria 3 Pro Preview

Google: Lyria 3 Pro Preview is a budget-priced multimodal generalist from Google with partial runtime data, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalN/A latencyLarge contextBudget pricing
Intelligence
N/A

Benchmark blend

Coding
N/A

Dev workflow signal

Context
1049K Tokens

Large

Input Price
$0.00

Budget tier

Decision snapshot
93

Google: Lyria 3 Pro Preview currently reads as a budget multimodal option with large context and a partially published runtime profile.

Overall profile
Flagship profile
Best for
Long-context research / Multimodal
Latency tier
N/A
Price tier
Budget
Source coverage
OpenRouterVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
N/A
N/A

General reasoning and benchmark headroom.

Unavailable
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
1049K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$0.00
86

$0.00 output / 1M

Efficient

Editorial Profile

Google: Lyria 3 Pro Preview in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Flagship profileCoding score N/AMath score N/AVision enabled

Full-length songs are priced at $0.08 per song. Lyria 3 is Google's family of music generation models, available through the Gemini API. With Lyria 3, you can generate high-quality, 48kHz stereo audio from text prompts or from images. These models deliver structural coherence, including vocals, timed lyrics, and full instrumental arrangements. Lyria 3 Pro can generate full-length songs with verses, choruses, bridges.

Identity

Google multimodal profile

Positioning

Long-context research / Multimodal with large context and partially published runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

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Context
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Input Price
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Intelligence
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Context
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Intelligence
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Context
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

No benchmark data is available for this model yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
1049K Tokens
Vision
Enabled
Modalities
audio, image, text
Tokenizer
Other
Max Completion
65536
Moderation
No
Supported Parameters
max_tokensresponse_formatseedtemperaturetop_p
Input Modalities
imagetext
Output Modalities
audiotext
Price architecture
Input
per 1M input tokens
$0.00
Output
per 1M output tokens
$0.00
Blended
AA 3:1 mix
N/A

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.