Bonsai 1.7B vs Bonsai 27B
At a Glance
| Compare | Bonsai 1.7BPrismML | Bonsai 27BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 33K | 262K |
| Model facts checked | Sep 18, 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 | Bonsai 1.7B | Bonsai 27B |
|---|---|---|
| Developer | PrismML | PrismML |
| Family | Bonsai 1 7b | Bonsai 27b |
| Model | Bonsai 1.7B | Bonsai 27B |
| Version | Bonsai 1.7B | Bonsai 27B |
| Lifecycle | active | active |
| Released | 2026-03-29 | 2026-07-04 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 33K | 262K |
| Total parameters | 1.7B | 27B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | No | No |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Unknown |
| Capabilities | chat, generation | chat, generation, reasoning, tools, vision |
| Base model | Unknown | Qwen3.6 27B |
| Effective bit width | 1 bit per weight | 1 bit per weight |
| Language model size | Unknown | 3.53 GiB |
| Weight size | 0.25 GB | Unknown |
| Weight format | Binary Q1_0 | Binary Q1_0 |
Bonsai 1.7B Capabilities
Bonsai 27B Capabilities
Primary Evidence
Sources and Freshness
Questions
Bonsai 1.7B vs Bonsai 27B FAQs
Is Bonsai 1.7B or Bonsai 27B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Bonsai 1.7B and Bonsai 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Bonsai 1.7B or Bonsai 27B?+
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, Bonsai 1.7B or Bonsai 27B?+
Bonsai 27B has the larger sourced context window. Bonsai 1.7B supports 33K and Bonsai 27B supports 262K.
Which performs better in benchmarks, Bonsai 1.7B or Bonsai 27B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Bonsai 1.7B or Bonsai 27B be self-hosted?+
Both models have the same recorded self-hosting status: supported. Bonsai 1.7B is open weight; Bonsai 27B is open weight.
Can Bonsai 1.7B and Bonsai 27B understand images?+
Bonsai 1.7B is not documented with image input; Bonsai 27B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Bonsai 1.7B or Bonsai 27B?+
Neither has a larger sourced maximum output. Bonsai 1.7B is — and Bonsai 27B is —.
Do Bonsai 1.7B and Bonsai 27B support reasoning and tool use?+
Bonsai 1.7B: none of these features are definitively sourced. Bonsai 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Bonsai 1.7B or Bonsai 27B?+
Bonsai 1.7B has 0 sourced provider routes; Bonsai 27B has 0, a tie.
Which offers better value, Bonsai 1.7B or Bonsai 27B?+
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.