PaddleOCR VL 1.5 vs Bonsai Image Binary 4B
At a Glance
| Compare |  PaddleOCR VL 1.5Baidu |  Bonsai Image Binary 4BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 131K | Not reported |
| 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 | PaddleOCR-VL-1.5 | Bonsai Image Binary 4B |
|---|---|---|
| Developer | Baidu | PrismML |
| Family | Paddleocr VL 1 5 | Bonsai Image 4b |
| Model | PaddleOCR-VL-1.5 | Bonsai Image Binary 4B |
| Version | PaddleOCR-VL-1.5 | Bonsai Image Binary 4B |
| Lifecycle | active | active |
| Released | 2026-01-29 | 2026-05-18 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Image |
| Context window | 131K | Unknown |
| Total parameters | 958.6M | 4B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Unknown | No |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Unknown |
| Capabilities | chat, generation | generation |
| Base model | Unknown | FLUX.2 Klein 4B |
| Default resolution | Unknown | 512 × 512 |
| Transformer size | Unknown | 0.93 GB |
| Weight format | Unknown | Binary weights with FP16 group scales |
PaddleOCR VL 1.5 Capabilities
Bonsai Image Binary 4B Capabilities
Related Comparisons
All image comparisons →| A | Pair | B | Context |
|---|---|---|---|
PaddleOCR-VL-1.5Baidu | vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Claude Fable 5.1Anthropic | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
PaddleOCR-VL-1.5Baidu | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Grok 4.6xAI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text |
 MiniMax-M3MiniMax | vs | PaddleOCR-VL-1.5Baidu | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  GLM-5.3Z.ai | cross-developer peerstext |
PaddleOCR-VL-1.5Baidu | vs |  Hy4 previewTencent | cross-developer peerstext |
PaddleOCR-VL-1.5Baidu | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
PaddleOCR VL 1.5 vs Bonsai Image Binary 4B FAQs
Is PaddleOCR VL 1.5 or Bonsai Image Binary 4B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both PaddleOCR VL 1.5 and Bonsai Image Binary 4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, PaddleOCR VL 1.5 or Bonsai Image Binary 4B?+
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, PaddleOCR VL 1.5 or Bonsai Image Binary 4B?+
Neither model has a larger sourced context window in this comparison. PaddleOCR VL 1.5 is 131K and Bonsai Image Binary 4B is —.
Which performs better in benchmarks, PaddleOCR VL 1.5 or Bonsai Image Binary 4B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can PaddleOCR VL 1.5 or Bonsai Image Binary 4B be self-hosted?+
Both models have the same recorded self-hosting status: supported. PaddleOCR VL 1.5 is open weight; Bonsai Image Binary 4B is open weight.
Can PaddleOCR VL 1.5 and Bonsai Image Binary 4B understand images?+
PaddleOCR VL 1.5 is documented with image input; Bonsai Image Binary 4B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, PaddleOCR VL 1.5 or Bonsai Image Binary 4B?+
Neither has a larger sourced maximum output. PaddleOCR VL 1.5 is — and Bonsai Image Binary 4B is —.
Do PaddleOCR VL 1.5 and Bonsai Image Binary 4B support reasoning and tool use?+
PaddleOCR VL 1.5: image input. Bonsai Image Binary 4B: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, PaddleOCR VL 1.5 or Bonsai Image Binary 4B?+
PaddleOCR VL 1.5 has 0 sourced provider routes; Bonsai Image Binary 4B has 0, a tie.
Which offers better value, PaddleOCR VL 1.5 or Bonsai Image Binary 4B?+
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.