PaddleOCR VL 1.5 vs Qwen3 VL Flash
At a Glance
| Compare |  PaddleOCR VL 1.5Baidu |  Qwen3 VL FlashQwen |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 131K | 262K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 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 | Qwen3 VL Flash |
|---|---|---|
| Developer | Baidu | Qwen |
| Family | Paddleocr VL 1 5 | Qwen3 VL |
| Model | PaddleOCR-VL-1.5 | Qwen3 VL Flash |
| Version | PaddleOCR-VL-1.5 | Qwen3 VL Flash |
| Lifecycle | active | active |
| Released | 2026-01-29 | 2026-01-22 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Video |
| Output modalities | Text | Text |
| Context window | 131K | 262K |
| Total parameters | 958.6M | 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 | Alibaba Cloud Model Studio (Standard) |
| Capabilities | chat, generation | chat, generation, reasoning, structured_outputs, tools, vision |
PaddleOCR VL 1.5 Capabilities
Qwen3 VL Flash 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 Qwen3 VL Flash FAQs
Is PaddleOCR VL 1.5 or Qwen3 VL Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both PaddleOCR VL 1.5 and Qwen3 VL Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, PaddleOCR VL 1.5 or Qwen3 VL Flash?+
Only Qwen3 VL Flash has a directly sourced input price: $0.15 per million tokens. Only Qwen3 VL Flash has a directly sourced output price: $1.50 per million tokens.
Which has a larger context window, PaddleOCR VL 1.5 or Qwen3 VL Flash?+
Qwen3 VL Flash has the larger sourced context window. PaddleOCR VL 1.5 supports 131K and Qwen3 VL Flash supports 262K.
Which performs better in benchmarks, PaddleOCR VL 1.5 or Qwen3 VL Flash?+
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 Qwen3 VL Flash 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; Qwen3 VL Flash is not marked open weight.
Can PaddleOCR VL 1.5 and Qwen3 VL Flash understand images?+
PaddleOCR VL 1.5 is documented with image input; Qwen3 VL Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, PaddleOCR VL 1.5 or Qwen3 VL Flash?+
Neither has a larger sourced maximum output. PaddleOCR VL 1.5 is — and Qwen3 VL Flash is —.
Do PaddleOCR VL 1.5 and Qwen3 VL Flash support reasoning and tool use?+
PaddleOCR VL 1.5: image input. Qwen3 VL Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, PaddleOCR VL 1.5 or Qwen3 VL Flash?+
PaddleOCR VL 1.5 has 0 sourced provider routes; Qwen3 VL Flash has 1, so Qwen3 VL Flash has broader tracked availability.
Which offers better value, PaddleOCR VL 1.5 or Qwen3 VL Flash?+
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.