Lyria 3.5 vs Qwen3.7 Max

At a Glance

Compare
Lyria 3.5Google DeepMind
Intelligence, Cost, and Efficiency
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#13 of 44$0.057 per LiveBench case
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$1.475Openrouter · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$4.425Openrouter · Sep 22, 2026
Context windowMaximum documented tokens1,049K1,000K
Model facts checkedSep 22, 2026View model evidence →Sep 3, 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 3.5Qwen3.7 Max
DeveloperGoogle DeepMindQwen
FamilyLyriaQwen3 7
ModelLyria 3.5Qwen3.7 Max
VersionLyria 3.5Qwen3.7 Max
Lifecycleactiveactive
Released2026-07-292026-05-20
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Video
Output modalitiesText, AudioText
Context window1,049K1,000K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessGoogle AI (Standard), Google Gemini (Standard)Alibaba Cloud Model Studio (Standard), Deepinfra (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitiesgeneration, image-to-music, lyrics, music-generation, synthid, vocalsagents, chat, generation, reasoning, structured_outputs, tools, vision

Lyria 3.5 Capabilities

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

Qwen3.7 Max Capabilities

agentschatgenerationreasoningstructured outputstoolsvision
Serving providers4
Canonical IDqwen/qwen3.7-max

Primary Evidence

Sources and Freshness

Questions

Lyria 3.5 vs Qwen3.7 Max FAQs

Is Lyria 3.5 or Qwen3.7 Max better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Lyria 3.5 and Qwen3.7 Max, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Lyria 3.5 or Qwen3.7 Max?+

Only Qwen3.7 Max has a directly sourced input price: $1.475 per million tokens. Only Qwen3.7 Max has a directly sourced output price: $4.425 per million tokens.

Which has a larger context window, Lyria 3.5 or Qwen3.7 Max?+

Lyria 3.5 has the larger sourced context window. Lyria 3.5 supports 1,049K and Qwen3.7 Max supports 1,000K.

Which performs better in benchmarks, Lyria 3.5 or Qwen3.7 Max?+

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 Qwen3.7 Max be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Lyria 3.5 is not marked open weight; Qwen3.7 Max is not marked open weight.

Can Lyria 3.5 and Qwen3.7 Max understand images?+

Lyria 3.5 is documented with image input; Qwen3.7 Max is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Lyria 3.5 or Qwen3.7 Max?+

Neither has a larger sourced maximum output. Lyria 3.5 is 66K and Qwen3.7 Max is 66K.

Do Lyria 3.5 and Qwen3.7 Max support reasoning and tool use?+

Lyria 3.5: image input. Qwen3.7 Max: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Lyria 3.5 or Qwen3.7 Max?+

Lyria 3.5 has 2 sourced provider routes; Qwen3.7 Max has 4, so Qwen3.7 Max has broader tracked availability.

Which offers better value, Lyria 3.5 or Qwen3.7 Max?+

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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