Kimi K2 Instruct vs Ternary Bonsai 27B
At a Glance
| Compare |  Kimi K2 InstructMoonshot AI |  Ternary Bonsai 27BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.57Openrouter ↗ · Aug 29, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $2.30Openrouter ↗ · Aug 29, 2026 | Not reported |
| Context windowMaximum documented tokens | 131K | 262K |
| Model facts checked | Aug 28, 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-Instruct | Ternary Bonsai 27B |
|---|---|---|
| Developer | Moonshot AI | PrismML |
| Family | Kimi K2 Instruct | Bonsai 27b |
| Model | Kimi-K2-Instruct | Ternary Bonsai 27B |
| Version | Kimi-K2-Instruct | Ternary Bonsai 27B |
| Lifecycle | active | active |
| Released | 2025-07-11 | 2026-07-04 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 262K |
| Total parameters | 1T | 27B |
| Active parameters | 32B | Unknown |
| License | other | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard), Openrouter (Standard) | Together Ai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, tools, vision |
| Base model | Unknown | Qwen3.6 27B |
| Effective bit width | Unknown | 1.58 bits per weight |
| Language model size | Unknown | 6.66 GiB |
| Weight format | Unknown | Ternary Q2_0 |
Kimi K2 Instruct Capabilities
Ternary Bonsai 27B Capabilities
Related Comparisons
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|---|---|---|---|
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 Gemini 3.1 ProGoogle DeepMind | vs | Kimi-K2-InstructMoonshot AI | cross-developer peerstext |
 DeepSeek-V4.1-FlashDeepSeek | vs | Kimi-K2-InstructMoonshot AI | cross-developer peerstext |
Kimi-K2-InstructMoonshot AI | vs | Grok 4.6xAI | cross-developer peerstext |
Kimi-K2-InstructMoonshot AI | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
Kimi-K2-InstructMoonshot AI | vs | Kimi-K3Moonshot AI | family variantstext |
 MiniMax-M3MiniMax | vs | Kimi-K2-InstructMoonshot AI | cross-developer peerstext |
Kimi-K2-InstructMoonshot AI | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Kimi-K2-InstructMoonshot AI | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | Kimi-K2-InstructMoonshot AI | cross-developer peerstext |
 Mistral Large 3Mistral AI | vs | Kimi-K2-InstructMoonshot AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Kimi K2 Instruct vs Ternary Bonsai 27B FAQs
Is Kimi K2 Instruct or Ternary Bonsai 27B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Kimi K2 Instruct and Ternary Bonsai 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Kimi K2 Instruct or Ternary Bonsai 27B?+
Only Kimi K2 Instruct has a directly sourced input price: $0.57 per million tokens. Only Kimi K2 Instruct has a directly sourced output price: $2.30 per million tokens.
Which has a larger context window, Kimi K2 Instruct or Ternary Bonsai 27B?+
Ternary Bonsai 27B has the larger sourced context window. Kimi K2 Instruct supports 131K and Ternary Bonsai 27B supports 262K.
Which performs better in benchmarks, Kimi K2 Instruct or Ternary Bonsai 27B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Kimi K2 Instruct or Ternary Bonsai 27B be self-hosted?+
Both models have the same recorded self-hosting status: supported. Kimi K2 Instruct is open weight; Ternary Bonsai 27B is open weight.
Can Kimi K2 Instruct and Ternary Bonsai 27B understand images?+
Kimi K2 Instruct is not documented with image input; Ternary Bonsai 27B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Kimi K2 Instruct or Ternary Bonsai 27B?+
Neither has a larger sourced maximum output. Kimi K2 Instruct is — and Ternary Bonsai 27B is —.
Do Kimi K2 Instruct and Ternary Bonsai 27B support reasoning and tool use?+
Kimi K2 Instruct: tool calling. Ternary Bonsai 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Kimi K2 Instruct or Ternary Bonsai 27B?+
Kimi K2 Instruct has 2 sourced provider routes; Ternary Bonsai 27B has 1, so Kimi K2 Instruct has broader tracked availability.
Which offers better value, Kimi K2 Instruct or Ternary 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.