PaddleOCR-VL-1.5 vs Sonar
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | PaddleOCR-VL-1.5 | Sonar |
|---|---|---|
| Developer | Baidu | Perplexity |
| Family | Paddleocr VL 1 5 | Sonar |
| Model | PaddleOCR-VL-1.5 | Sonar |
| Version | PaddleOCR-VL-1.5 | Sonar |
| Lifecycle | active | active |
| Released | 2026-01-29 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 131,072 | 128,000 |
| Total parameters | 958,588,736 | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Unknown | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Openrouter (Standard), Perplexity (Standard) |
| Capabilities | chat, generation | chat, citations, search |
11 comparable fields · 9 material differences · Pair passes the primary-source comparison gate
PaddleOCR-VL-1.5 Capabilities
Sonar Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
PaddleOCR-VL-1.5Baidu | vs |  GLM-OCRZ.ai | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Phi-4-multimodal-instructMicrosoft | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Ministral-3-3B-Instruct-2512Mistral AI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Ministral-3-8B-Instruct-2512Mistral AI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs |  Molmo2-8BAi2 | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Ministral-3-3B-Base-2512Mistral AI | cross-developer peersimage, text |
PaddleOCR-VL-1.5Baidu | vs | Ministral-3-14B-Base-2512Mistral AI | cross-developer peersimage, text |
SonarPerplexity | vs | Sonar Reasoning ProPerplexity | family variantstext |
SonarPerplexity | vs | Sonar ProPerplexity | family variantstext |
PaddleOCR-VL-1.5Baidu | vs | cross-developer peersimage, text | |
SonarPerplexity | vs | Sonar Deep ResearchPerplexity | family variantstext |
ERNIE 5.1Baidu | vs | SonarPerplexity | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
PaddleOCR-VL-1.5 vs Sonar FAQs
Is PaddleOCR-VL-1.5 or Sonar better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both PaddleOCR-VL-1.5 and Sonar, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, PaddleOCR-VL-1.5 or Sonar?+
Only Sonar has a directly sourced input price: $1.00 per million tokens. Only Sonar has a directly sourced output price: $1.00 per million tokens.
Which has a larger context window, PaddleOCR-VL-1.5 or Sonar?+
PaddleOCR-VL-1.5 has the larger sourced context window. PaddleOCR-VL-1.5 supports 131,072 and Sonar supports 128,000.
Which performs better in benchmarks, PaddleOCR-VL-1.5 or Sonar?+
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 Sonar be self-hosted?+
PaddleOCR-VL-1.5 is the only model in this pair currently marked as self-hostable. PaddleOCR-VL-1.5 is open weight; Sonar is not marked open weight.
Can PaddleOCR-VL-1.5 and Sonar understand images?+
PaddleOCR-VL-1.5 is documented with image input; Sonar is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, PaddleOCR-VL-1.5 or Sonar?+
Neither has a larger sourced maximum output. PaddleOCR-VL-1.5 is — and Sonar is —.
Do PaddleOCR-VL-1.5 and Sonar support reasoning and tool use?+
PaddleOCR-VL-1.5: image input. Sonar: 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 Sonar?+
PaddleOCR-VL-1.5 has 0 sourced provider routes; Sonar has 2, so Sonar has broader tracked availability.
Which offers better value, PaddleOCR-VL-1.5 or Sonar?+
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.