PaddleOCR VL 1.5 vs Qwen3.5 35B A3B
At a Glance
| Compare |  PaddleOCR VL 1.5Baidu |  Qwen3.5 35B A3BQwen |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.14Deepinfra ↗ · Sep 21, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $1.00Deepinfra ↗ · Sep 21, 2026 |
| Context windowMaximum documented tokens | 131K | 262K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 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 | Qwen3.5-35B-A3B |
|---|---|---|
| Developer | Baidu | Qwen |
| Family | Paddleocr VL 1 5 | Qwen3 5 35b A3b |
| Model | PaddleOCR-VL-1.5 | Qwen3.5-35B-A3B |
| Version | PaddleOCR-VL-1.5 | Qwen3.5-35B-A3B |
| Lifecycle | active | active |
| Released | 2026-01-29 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 262K |
| Total parameters | 958.6M | 36B |
| Active parameters | Unknown | 3B |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Unknown | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation | chat, generation, reasoning, tools |
PaddleOCR VL 1.5 Capabilities
Qwen3.5 35B A3B 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 Qwen3.5 35B A3B FAQs
Is PaddleOCR VL 1.5 or Qwen3.5 35B A3B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both PaddleOCR VL 1.5 and Qwen3.5 35B A3B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, PaddleOCR VL 1.5 or Qwen3.5 35B A3B?+
Only Qwen3.5 35B A3B has a directly sourced input price: $0.14 per million tokens. Only Qwen3.5 35B A3B has a directly sourced output price: $1.00 per million tokens.
Which has a larger context window, PaddleOCR VL 1.5 or Qwen3.5 35B A3B?+
Qwen3.5 35B A3B has the larger sourced context window. PaddleOCR VL 1.5 supports 131K and Qwen3.5 35B A3B supports 262K.
Which performs better in benchmarks, PaddleOCR VL 1.5 or Qwen3.5 35B A3B?+
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 Qwen3.5 35B A3B be self-hosted?+
Both models have the same recorded self-hosting status: supported. PaddleOCR VL 1.5 is open weight; Qwen3.5 35B A3B is open weight.
Can PaddleOCR VL 1.5 and Qwen3.5 35B A3B understand images?+
PaddleOCR VL 1.5 is documented with image input; Qwen3.5 35B A3B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, PaddleOCR VL 1.5 or Qwen3.5 35B A3B?+
Neither has a larger sourced maximum output. PaddleOCR VL 1.5 is — and Qwen3.5 35B A3B is —.
Do PaddleOCR VL 1.5 and Qwen3.5 35B A3B support reasoning and tool use?+
PaddleOCR VL 1.5: image input. Qwen3.5 35B A3B: 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 Qwen3.5 35B A3B?+
PaddleOCR VL 1.5 has 0 sourced provider routes; Qwen3.5 35B A3B has 4, so Qwen3.5 35B A3B has broader tracked availability.
Which offers better value, PaddleOCR VL 1.5 or Qwen3.5 35B A3B?+
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.