PaddleOCR-VL
novita-ai/paddleocr-vlمن novita-ai · أُصدِر 2025-10-22
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 |
|---|---|---|---|---|---|
| NovitaAI novita-ai | paddlepaddle/paddleocr-vl | $0.020 | $0.020 | 16K | 2025-10-22 |
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 Ling-2.6-1T, Ling-2.6-flash, baichuan-m2-32b. 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
More novita-ai models
- Ling-2.6-1TUnknown pricing
- Ling-2.6-flash$0.10 in / $0.30 out
- baichuan-m2-32b$0.07 in / $0.07 out
- Mythomax L2 13B$0.09 in / $0.09 out
- L31 70B Euryale V2.2$1.48 in / $1.48 out
Capability lists this model is in
آخر تحديث:
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.