Lyria 3.5 vs NVIDIA Nemotron 3 Nano 30B A3B Base BF16
At a Glance
| Compare |  Lyria 3.5Google DeepMind | |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 1,049K | 262K |
| Model facts checked | Sep 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
Side-by-Side Facts
| Field | Lyria 3.5 | NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16 |
|---|---|---|
| Developer | Google DeepMind | NVIDIA |
| Family | Lyria | Nvidia Nemotron 3 Nano 30b A3b Base Bf16 |
| Model | Lyria 3.5 | NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16 |
| Version | Lyria 3.5 | NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16 |
| Lifecycle | active | active |
| Released | 2026-07-29 | 2025-12-15 |
| Knowledge cutoff | Unknown | 2025-06-25 |
| Input modalities | Text, Image | Text |
| Output modalities | Text, Audio | Text |
| Context window | 1,049K | 262K |
| Total parameters | Unknown | 31.6B |
| Active parameters | Unknown | Unknown |
| License | Unknown | other |
| Open weights | No | Yes |
| API available | Yes | Unknown |
| Self-hostable | No | Yes |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Unknown |
| Capabilities | generation, image-to-music, lyrics, music-generation, synthid, vocals | generation |
Lyria 3.5 Capabilities
NVIDIA Nemotron 3 Nano 30B A3B Base BF16 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Lyria 3.5 vs NVIDIA Nemotron 3 Nano 30B A3B Base BF16 FAQs
Is Lyria 3.5 or NVIDIA Nemotron 3 Nano 30B A3B Base BF16 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Lyria 3.5 and NVIDIA Nemotron 3 Nano 30B A3B Base 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 Nano 30B A3B Base 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 Nano 30B A3B Base BF16?+
Lyria 3.5 has the larger sourced context window. Lyria 3.5 supports 1,049K and NVIDIA Nemotron 3 Nano 30B A3B Base BF16 supports 262K.
Which performs better in benchmarks, Lyria 3.5 or NVIDIA Nemotron 3 Nano 30B A3B Base 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 Nano 30B A3B Base BF16 be self-hosted?+
NVIDIA Nemotron 3 Nano 30B A3B Base BF16 is the only model in this pair currently marked as self-hostable. Lyria 3.5 is not marked open weight; NVIDIA Nemotron 3 Nano 30B A3B Base BF16 is open weight.
Can Lyria 3.5 and NVIDIA Nemotron 3 Nano 30B A3B Base BF16 understand images?+
Lyria 3.5 is documented with image input; NVIDIA Nemotron 3 Nano 30B A3B Base 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 Nano 30B A3B Base BF16?+
NVIDIA Nemotron 3 Nano 30B A3B Base BF16 has the larger sourced maximum output: Lyria 3.5 supports 66K and NVIDIA Nemotron 3 Nano 30B A3B Base BF16 supports 131K output tokens.
Do Lyria 3.5 and NVIDIA Nemotron 3 Nano 30B A3B Base BF16 support reasoning and tool use?+
Lyria 3.5: image input. NVIDIA Nemotron 3 Nano 30B A3B Base BF16: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Lyria 3.5 or NVIDIA Nemotron 3 Nano 30B A3B Base BF16?+
Lyria 3.5 has 2 sourced provider routes; NVIDIA Nemotron 3 Nano 30B A3B Base BF16 has 0, so Lyria 3.5 has broader tracked availability.
Which offers better value, Lyria 3.5 or NVIDIA Nemotron 3 Nano 30B A3B Base 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.