Gemini 3.5 Flash Lite vs Bonsai 1.7B
At a Glance
| Compare |  Gemini 3.5 Flash LiteGoogle DeepMind |  Bonsai 1.7BPrismML |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #39 of 4617.6 score · 3/3 sources · complete | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #8 of 44$0.029 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #32 of 3846.2 score · 3/3 sources · complete | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.30Google AI ↗ · Aug 29, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $2.50Google AI ↗ · Aug 29, 2026 | Not reported |
| Context windowMaximum documented tokens | 1,049K | 33K |
| Model facts checked | Aug 29, 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 | Gemini 3.5 Flash-Lite | Bonsai 1.7B |
|---|---|---|
| Developer | Google DeepMind | PrismML |
| Family | Gemini 3 | Bonsai 1 7b |
| Model | Gemini 3.5 Flash-Lite | Bonsai 1.7B |
| Version | Gemini 3.5 Flash-Lite | Bonsai 1.7B |
| Lifecycle | active | active |
| Released | Unknown | 2026-03-29 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text |
| Output modalities | Text | Text |
| Context window | 1,049K | 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 | Google AI (Standard), Google Gemini (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | chat, generation |
| Effective bit width | Unknown | 1 bit per weight |
| Weight size | Unknown | 0.25 GB |
| Weight format | Unknown | Binary Q1_0 |
Gemini 3.5 Flash Lite Capabilities
Bonsai 1.7B Capabilities
Related Comparisons
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Gemini 3.5 Flash-LiteGoogle DeepMind | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
Gemini 3.5 Flash-LiteGoogle DeepMind | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | Gemini 3.5 Flash-LiteGoogle DeepMind | cross-developer peerstext |
Gemini 3.5 Flash-LiteGoogle DeepMind | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Gemini 3.5 Flash-LiteGoogle DeepMind | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | Gemini 3.5 Flash-LiteGoogle DeepMind | cross-developer peerstext |
Gemini 3.5 Flash-LiteGoogle DeepMind | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini 3.5 Flash Lite vs Bonsai 1.7B FAQs
Is Gemini 3.5 Flash Lite or Bonsai 1.7B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.5 Flash Lite and Bonsai 1.7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3.5 Flash Lite or Bonsai 1.7B?+
Only Gemini 3.5 Flash Lite has a directly sourced input price: $0.30 per million tokens. Only Gemini 3.5 Flash Lite has a directly sourced output price: $2.50 per million tokens.
Which has a larger context window, Gemini 3.5 Flash Lite or Bonsai 1.7B?+
Gemini 3.5 Flash Lite has the larger sourced context window. Gemini 3.5 Flash Lite supports 1,049K and Bonsai 1.7B supports 33K.
Which performs better in benchmarks, Gemini 3.5 Flash Lite or Bonsai 1.7B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini 3.5 Flash Lite or Bonsai 1.7B be self-hosted?+
Bonsai 1.7B is the only model in this pair currently marked as self-hostable. Gemini 3.5 Flash Lite is not marked open weight; Bonsai 1.7B is open weight.
Can Gemini 3.5 Flash Lite and Bonsai 1.7B understand images?+
Gemini 3.5 Flash Lite is documented with image input; Bonsai 1.7B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 3.5 Flash Lite or Bonsai 1.7B?+
Neither has a larger sourced maximum output. Gemini 3.5 Flash Lite is 66K and Bonsai 1.7B is —.
Do Gemini 3.5 Flash Lite and Bonsai 1.7B support reasoning and tool use?+
Gemini 3.5 Flash Lite: reasoning, tool calling, and image input. Bonsai 1.7B: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 3.5 Flash Lite or Bonsai 1.7B?+
Gemini 3.5 Flash Lite has 2 sourced provider routes; Bonsai 1.7B has 0, so Gemini 3.5 Flash Lite has broader tracked availability.
Which offers better value, Gemini 3.5 Flash Lite or 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.