Gemini 2.5 Pro vs Bonsai 27B
At a Glance
| Compare |  Gemini 2.5 ProGoogle DeepMind |  Bonsai 27BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $1.25Google AI ↗ · Aug 29, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $10.00Google AI ↗ · Aug 29, 2026 | Not reported |
| Context windowMaximum documented tokens | 1,049K | 262K |
| 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 2.5 Pro | Bonsai 27B |
|---|---|---|
| Developer | Google DeepMind | PrismML |
| Family | Gemini 2 5 | Bonsai 27b |
| Model | Gemini 2.5 Pro | Bonsai 27B |
| Version | Gemini 2.5 Pro | Bonsai 27B |
| Lifecycle | active | active |
| Released | Unknown | 2026-07-04 |
| Knowledge cutoff | 2025-01-01 | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 262K |
| Total parameters | Unknown | 27B |
| 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, reasoning, tools, vision |
| Base model | Unknown | Qwen3.6 27B |
| Effective bit width | Unknown | 1 bit per weight |
| Language model size | Unknown | 3.53 GiB |
| Weight format | Unknown | Binary Q1_0 |
Gemini 2.5 Pro Capabilities
Bonsai 27B Capabilities
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Primary Evidence
Sources and Freshness
Questions
Gemini 2.5 Pro vs Bonsai 27B FAQs
Is Gemini 2.5 Pro or Bonsai 27B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 2.5 Pro and Bonsai 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 2.5 Pro or Bonsai 27B?+
Only Gemini 2.5 Pro has a directly sourced input price: $1.25 per million tokens. Only Gemini 2.5 Pro has a directly sourced output price: $10.00 per million tokens.
Which has a larger context window, Gemini 2.5 Pro or Bonsai 27B?+
Gemini 2.5 Pro has the larger sourced context window. Gemini 2.5 Pro supports 1,049K and Bonsai 27B supports 262K.
Which performs better in benchmarks, Gemini 2.5 Pro or Bonsai 27B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini 2.5 Pro or Bonsai 27B be self-hosted?+
Bonsai 27B is the only model in this pair currently marked as self-hostable. Gemini 2.5 Pro is not marked open weight; Bonsai 27B is open weight.
Can Gemini 2.5 Pro and Bonsai 27B understand images?+
Gemini 2.5 Pro is documented with image input; Bonsai 27B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 2.5 Pro or Bonsai 27B?+
Neither has a larger sourced maximum output. Gemini 2.5 Pro is 66K and Bonsai 27B is —.
Do Gemini 2.5 Pro and Bonsai 27B support reasoning and tool use?+
Gemini 2.5 Pro: reasoning, tool calling, and image input. Bonsai 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 2.5 Pro or Bonsai 27B?+
Gemini 2.5 Pro has 2 sourced provider routes; Bonsai 27B has 0, so Gemini 2.5 Pro has broader tracked availability.
Which offers better value, Gemini 2.5 Pro 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.