Muse Spark 1.1 vs VibeVoice ASR Streaming 1.5B
At a Glance
| Compare |  Muse Spark 1.1Meta |  VibeVoice ASR Streaming 1.5BMicrosoft |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 1,000K | Not reported |
| Model facts checked | Sep 3, 2026View model evidence → | Sep 2, 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 | Muse Spark 1.1 | VibeVoice-ASR-Streaming-1.5B |
|---|---|---|
| Developer | Meta | Microsoft |
| Family | Muse Spark | Vibevoice ASR Streaming |
| Model | Muse Spark 1.1 | VibeVoice-ASR-Streaming-1.5B |
| Version | Muse Spark 1.1 | VibeVoice-ASR-Streaming-1.5B |
| Lifecycle | preview | active |
| Released | 2026-07-09 | 2026-09-03 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio | Audio |
| Output modalities | Text | Text |
| Context window | 1,000K | Unknown |
| Total parameters | Unknown | 2.8B |
| Active parameters | Unknown | Unknown |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | No |
| Self-hostable | No | Yes |
| Provider access | Unknown | Unknown |
| Capabilities | chat, computer-use, generation, reasoning, research, structured_outputs, tools | diarization, hotwords, multilingual, streaming, transcription |
| Streaming chunk | Unknown | 22 frames |
| Streaming lookahead | Unknown | 4 frames |
| Supported languages | Unknown | Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, Spanish |
| Target sample rate | Unknown | 24000 Hz |
Muse Spark 1.1 Capabilities
VibeVoice ASR Streaming 1.5B Capabilities
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Primary Evidence
Sources and Freshness
Questions
Muse Spark 1.1 vs VibeVoice ASR Streaming 1.5B FAQs
Is Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Muse Spark 1.1 and VibeVoice ASR Streaming 1.5B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B?+
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, Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B?+
Neither model has a larger sourced context window in this comparison. Muse Spark 1.1 is 1,000K and VibeVoice ASR Streaming 1.5B is —.
Which performs better in benchmarks, Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B be self-hosted?+
VibeVoice ASR Streaming 1.5B is the only model in this pair currently marked as self-hostable. Muse Spark 1.1 is not marked open weight; VibeVoice ASR Streaming 1.5B is open weight.
Can Muse Spark 1.1 and VibeVoice ASR Streaming 1.5B understand images?+
Muse Spark 1.1 is documented with image input; VibeVoice ASR Streaming 1.5B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B?+
Neither has a larger sourced maximum output. Muse Spark 1.1 is — and VibeVoice ASR Streaming 1.5B is —.
Do Muse Spark 1.1 and VibeVoice ASR Streaming 1.5B support reasoning and tool use?+
Muse Spark 1.1: reasoning, tool calling, and image input. VibeVoice ASR Streaming 1.5B: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B?+
Muse Spark 1.1 has 0 sourced provider routes; VibeVoice ASR Streaming 1.5B has 0, a tie.
Which offers better value, Muse Spark 1.1 or VibeVoice ASR Streaming 1.5B?+
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.