PaddleOCR VL
novita-ai/paddleocr-vlمن novita-ai · أُصدِر 2025-10-16
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
القدرات
Model fit scores
0–100 · higher is betterThese 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 output30
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control10/10
- Price-friendly for high-volume20/20
Cost efficiency95
- Headline price (log-scaled)95/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Vision64
- Accepts image input50/50
- Context window (10K → 1M)3/30
- Has published price10/10
- Provider availability1/10
Production-readiness58
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K8/15
- No data inconsistencies across providers10/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.11 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $0.22 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.05 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.18 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.25 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
تفاصيل التسعير
السعر المُوصى به من novita-ai · paddlepaddle/paddleocr-vl
متاح لدى 1 مزود
| المزود | معرف نموذج المزود | إدخال / 1M | إخراج / 1M | السياق | تاريخ الإصدار |
|---|---|---|---|---|---|
| Novita AI novita-ai | paddlepaddle/paddleocr-vl | $0.020 | $0.020 | 16K | 2025-10-16 |
Frequently asked questions
How much does PaddleOCR VL cost?
PaddleOCR VL costs $0.020 per 1M input tokens and $0.020 per 1M output tokens, sourced from novita-ai. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of PaddleOCR VL?
PaddleOCR VL 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 PaddleOCR VL support tool calling?
No. PaddleOCR VL does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does PaddleOCR VL support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for PaddleOCR VL in our data source. Verify with novita-ai's official documentation before relying on it in production.
Can PaddleOCR VL accept image input?
Yes. PaddleOCR VL accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check novita-ai's docs for the exact rule.
Is PaddleOCR VL open-weight?
Yes. PaddleOCR VL'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 PaddleOCR VL?
If PaddleOCR VL doesn't fit, consider Macaron V1 Tall, Macaron V1 Venti, BGE Reranker V2 M3. 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 are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More novita-ai models
- Macaron V1 Tall$0.25 in / $1.43 out
- Macaron V1 Venti$0.82 in / $2.48 out
- BGE Reranker V2 M3$0.01 in / $0.00 out
- BGE M3$0.01 in / $0.00 out
- Ling 3.0 Flash VL$0.07 in / $0.22 out
Capability lists this model is in
آخر تحديث:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.