Kimi K2.7 Code vs Ternary Bonsai 1.7B
At a Glance
| Compare |  Kimi K2.7 CodeMoonshot AI |  Ternary Bonsai 1.7BPrismML |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| CostLower is better · Published-token output estimate | #9 of 44$0.042 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.68Deepinfra ↗ · Sep 22, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $3.21Openrouter ↗ · Sep 22, 2026 | Not reported |
| Context windowMaximum documented tokens | 262K | 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 | Kimi K2.7 Code | Ternary Bonsai 1.7B |
|---|---|---|
| Developer | Moonshot AI | PrismML |
| Family | Kimi K2 7 | Bonsai 1 7b |
| Model | Kimi K2.7 Code | Ternary Bonsai 1.7B |
| Version | Kimi K2.7 Code | Ternary Bonsai 1.7B |
| Lifecycle | active | active |
| Released | 2026-06-11 | 2026-04-18 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video | Text |
| Output modalities | Text | Text |
| Context window | 262K | 33K |
| Total parameters | 1T | 1.7B |
| Active parameters | 32B | Unknown |
| License | modified-mit | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | No |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Openrouter (Standard), Together Ai (Standard) | Unknown |
| Capabilities | agents, chat, coding, reasoning, tools, vision | chat, generation |
| Effective bit width | Unknown | 1.58 bits per weight |
| Weight size | Unknown | 0.46 GB |
| Weight format | Unknown | Ternary Q2_0 |
Kimi K2.7 Code Capabilities
Ternary Bonsai 1.7B Capabilities
Related Comparisons
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|---|---|---|---|
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Kimi K2.7 CodeMoonshot AI | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text, video |
Kimi K2.7 CodeMoonshot AI | vs | Kimi-K3Moonshot AI | family variantsimage, text |
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Kimi K2.7 CodeMoonshot AI | vs |  GLM-5.3Z.ai | cross-developer peerstext |
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Primary Evidence
Sources and Freshness
Questions
Kimi K2.7 Code vs Ternary Bonsai 1.7B FAQs
Is Kimi K2.7 Code or Ternary Bonsai 1.7B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Kimi K2.7 Code and Ternary Bonsai 1.7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Kimi K2.7 Code or Ternary Bonsai 1.7B?+
Only Kimi K2.7 Code has a directly sourced input price: $0.68 per million tokens. Only Kimi K2.7 Code has a directly sourced output price: $3.21 per million tokens.
Which has a larger context window, Kimi K2.7 Code or Ternary Bonsai 1.7B?+
Kimi K2.7 Code has the larger sourced context window. Kimi K2.7 Code supports 262K and Ternary Bonsai 1.7B supports 33K.
Which performs better in benchmarks, Kimi K2.7 Code 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 Kimi K2.7 Code or Ternary Bonsai 1.7B be self-hosted?+
Both models have the same recorded self-hosting status: supported. Kimi K2.7 Code is open weight; Ternary Bonsai 1.7B is open weight.
Can Kimi K2.7 Code and Ternary Bonsai 1.7B understand images?+
Kimi K2.7 Code 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, Kimi K2.7 Code or Ternary Bonsai 1.7B?+
Neither has a larger sourced maximum output. Kimi K2.7 Code is — and Ternary Bonsai 1.7B is —.
Do Kimi K2.7 Code and Ternary Bonsai 1.7B support reasoning and tool use?+
Kimi K2.7 Code: 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, Kimi K2.7 Code or Ternary Bonsai 1.7B?+
Kimi K2.7 Code has 4 sourced provider routes; Ternary Bonsai 1.7B has 0, so Kimi K2.7 Code has broader tracked availability.
Which offers better value, Kimi K2.7 Code 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.