AI Model Intelligence

PaddlePaddle/PaddleOCR-VL-1.5

siliconflow-cn/paddleocr-vl-1-5

By siliconflow-cn · released 2026-01-29

Unknown
Input / 1M tokens
Unknown
Output / 1M tokens
16K
Context window
16K
Max output

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

Capabilities

✗ Tool calling✗ Reasoning? Structured output✓ Attachments✓ Open weights✓ Temperature control
Modalities: input text, image · output text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding1
  • Tool calling0/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)0/20
  • Provider availability1/10
Agents11
  • Tool calling0/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit10/15
  • Provider availability1/10
JSON / structured output10
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control10/10
  • Price-friendly for high-volume0/20
Cost efficiency0
  • Has published price0/100
Long context0
  • Context ≥ 100K0/100
Vision54
  • Accepts image input50/50
  • Context window (10K → 1M)3/30
  • Has published price0/10
  • Provider availability1/10
Production-readiness38
  • Number of independent providers5/40
  • Has published per-token price0/20
  • Context window ≥ 8K8/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)15/15

Cost Efficiency Index

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Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

This model has no published per-token price, so we can't compute a cost estimate. See the provider's official pricing page for current rates.

Available on 1 providers

ProviderProvider model idInput / 1MOutput / 1MContextReleased
SiliconFlow (China)
siliconflow-cn
PaddlePaddle/PaddleOCR-VL-1.5UnknownUnknown16K2026-01-29

Frequently asked questions

How much does PaddlePaddle/PaddleOCR-VL-1.5 cost?

PaddlePaddle/PaddleOCR-VL-1.5 does not have a publicly published per-token price in our data source. This usually means it is gated behind enterprise sales or invite access. Check siliconflow-cn's official pricing page for the most current rates.

What is the context window of PaddlePaddle/PaddleOCR-VL-1.5?

PaddlePaddle/PaddleOCR-VL-1.5 has a context window of 16K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.

Does PaddlePaddle/PaddleOCR-VL-1.5 support tool calling?

No. PaddlePaddle/PaddleOCR-VL-1.5 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does PaddlePaddle/PaddleOCR-VL-1.5 support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for PaddlePaddle/PaddleOCR-VL-1.5 in our data source. Verify with siliconflow-cn's official documentation before relying on it in production.

Can PaddlePaddle/PaddleOCR-VL-1.5 accept image input?

Yes. PaddlePaddle/PaddleOCR-VL-1.5 accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check siliconflow-cn's docs for the exact rule.

Is PaddlePaddle/PaddleOCR-VL-1.5 open-weight?

Yes. PaddlePaddle/PaddleOCR-VL-1.5's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to PaddlePaddle/PaddleOCR-VL-1.5?

If PaddlePaddle/PaddleOCR-VL-1.5 doesn't fit, consider inclusionAI/Ling-flash-2.0, inclusionAI/Ling-mini-2.0, inclusionAI/Ring-flash-2.0. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

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Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.