Lyria 3.5 vs NVIDIA Nemotron 3 Super 120B A12B BF16

At a Glance

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Lyria 3.5Google DeepMind
Pricing and Limits
Context windowMaximum documented tokens1,049K262K
Model facts checkedSep 22, 2026View model evidence →Aug 28, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldLyria 3.5NVIDIA-Nemotron-3-Super-120B-A12B-BF16
DeveloperGoogle DeepMindNVIDIA
FamilyLyriaNvidia Nemotron 3 Super 120b A12b Bf16
ModelLyria 3.5NVIDIA-Nemotron-3-Super-120B-A12B-BF16
VersionLyria 3.5NVIDIA-Nemotron-3-Super-120B-A12B-BF16
Lifecycleactiveactive
Released2026-07-292026-03-11
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesText, AudioText
Context window1,049K262K
Total parametersUnknown123.6B
Active parametersUnknown12B
LicenseUnknownother
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Hugging Face (Standard), Together Ai (Standard)
Capabilitiesgeneration, image-to-music, lyrics, music-generation, synthid, vocalschat, generation, reasoning, tools

Lyria 3.5 Capabilities

generationimage-to-musiclyricsmusic-generationsynthidvocals
Serving providers2
Canonical IDlyria-3.5

NVIDIA Nemotron 3 Super 120B A12B BF16 Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDnvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16

Primary Evidence

Sources and Freshness

Questions

Lyria 3.5 vs NVIDIA Nemotron 3 Super 120B A12B BF16 FAQs

Is Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Lyria 3.5 and NVIDIA Nemotron 3 Super 120B A12B BF16, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16?+

Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.

Which has a larger context window, Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16?+

Lyria 3.5 has the larger sourced context window. Lyria 3.5 supports 1,049K and NVIDIA Nemotron 3 Super 120B A12B BF16 supports 262K.

Which performs better in benchmarks, Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16 be self-hosted?+

NVIDIA Nemotron 3 Super 120B A12B BF16 is the only model in this pair currently marked as self-hostable. Lyria 3.5 is not marked open weight; NVIDIA Nemotron 3 Super 120B A12B BF16 is open weight.

Can Lyria 3.5 and NVIDIA Nemotron 3 Super 120B A12B BF16 understand images?+

Lyria 3.5 is documented with image input; NVIDIA Nemotron 3 Super 120B A12B BF16 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16?+

Neither has a larger sourced maximum output. Lyria 3.5 is 66K and NVIDIA Nemotron 3 Super 120B A12B BF16 is —.

Do Lyria 3.5 and NVIDIA Nemotron 3 Super 120B A12B BF16 support reasoning and tool use?+

Lyria 3.5: image input. NVIDIA Nemotron 3 Super 120B A12B BF16: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16?+

Lyria 3.5 has 2 sourced provider routes; NVIDIA Nemotron 3 Super 120B A12B BF16 has 2, a tie.

Which offers better value, Lyria 3.5 or NVIDIA Nemotron 3 Super 120B A12B BF16?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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