Muse Spark 1.1 vs Ternary Bonsai 1.7B
At a Glance
| Compare |  Muse Spark 1.1Meta |  Ternary Bonsai 1.7BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 1,000K | 33K |
| Model facts checked | Sep 3, 2026View model evidence → | Sep 18, 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 | Ternary Bonsai 1.7B |
|---|---|---|
| Developer | Meta | PrismML |
| Family | Muse Spark | Bonsai 1 7b |
| Model | Muse Spark 1.1 | Ternary Bonsai 1.7B |
| Version | Muse Spark 1.1 | Ternary Bonsai 1.7B |
| Lifecycle | preview | active |
| Released | 2026-07-09 | 2026-04-18 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 33K |
| Total parameters | Unknown | 1.7B |
| Active parameters | Unknown | Unknown |
| License | Unknown | apache-2.0 |
| 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 | chat, generation |
| Effective bit width | Unknown | 1.58 bits per weight |
| Weight size | Unknown | 0.46 GB |
| Weight format | Unknown | Ternary Q2_0 |
Muse Spark 1.1 Capabilities
Ternary Bonsai 1.7B Capabilities
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Primary Evidence
Sources and Freshness
Questions
Muse Spark 1.1 vs Ternary Bonsai 1.7B FAQs
Is Muse Spark 1.1 or Ternary Bonsai 1.7B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Muse Spark 1.1 and Ternary Bonsai 1.7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Muse Spark 1.1 or Ternary Bonsai 1.7B?+
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 Ternary Bonsai 1.7B?+
Muse Spark 1.1 has the larger sourced context window. Muse Spark 1.1 supports 1,000K and Ternary Bonsai 1.7B supports 33K.
Which performs better in benchmarks, Muse Spark 1.1 or Ternary Bonsai 1.7B?+
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 Ternary Bonsai 1.7B be self-hosted?+
Ternary Bonsai 1.7B is the only model in this pair currently marked as self-hostable. Muse Spark 1.1 is not marked open weight; Ternary Bonsai 1.7B is open weight.
Can Muse Spark 1.1 and Ternary Bonsai 1.7B understand images?+
Muse Spark 1.1 is documented with image input; Ternary Bonsai 1.7B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Muse Spark 1.1 or Ternary Bonsai 1.7B?+
Neither has a larger sourced maximum output. Muse Spark 1.1 is — and Ternary Bonsai 1.7B is —.
Do Muse Spark 1.1 and Ternary Bonsai 1.7B support reasoning and tool use?+
Muse Spark 1.1: reasoning, tool calling, and image input. Ternary Bonsai 1.7B: 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 Ternary Bonsai 1.7B?+
Muse Spark 1.1 has 0 sourced provider routes; Ternary Bonsai 1.7B has 0, a tie.
Which offers better value, Muse Spark 1.1 or Ternary Bonsai 1.7B?+
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.