API cost decision in 10 seconds

Nemotron 3.5 Content Safety (free) vs Qianfan-OCR-Fast

Pick Nemotron 3.5 Content Safety (free) when budget and context both matter.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Nemotron 3.5 Content Safety (free) when budget and context both matter.

On the standard 1M input plus 500K output workload, Nemotron 3.5 Content Safety (free) is estimated at $0 vs $2.08 for Qianfan-OCR-Fast, saving $2.08 (100% lower).

Cost-first pickNemotron 3.5 Content Safety (free)
Context-first pickNemotron 3.5 Content Safety (free)
Sample savings$2.08100%
10x traffic gap$20.85

Nemotron 3.5 Content Safety (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $20.85. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Nemotron 3.5 Content Safety (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickNemotron 3.5 Content Safety (free)Qianfan-OCR-Fast
Input-heavy / RAG5M input + 500K outputNemotron 3.5 Content Safety (free)$0$4.81
Balanced workload1M input + 1M outputNemotron 3.5 Content Safety (free)$0$3.49
Output-heavy chatbot1M input + 5M outputNemotron 3.5 Content Safety (free)$0$14.73
Cheaper input Nemotron 3.5 Content Safety (free) $0 vs $0.68 / 1M

Nemotron 3.5 Content Safety (free) is free for input tokens while Qianfan-OCR-Fast costs $0.68 per 1M tokens.

Cheaper output Nemotron 3.5 Content Safety (free) $0 vs $2.81 / 1M

Nemotron 3.5 Content Safety (free) is free for output tokens while Qianfan-OCR-Fast costs $2.81 per 1M tokens.

Larger context Nemotron 3.5 Content Safety (free) 128K vs 65.54K

Nemotron 3.5 Content Safety (free) has 62.46K more context (1.95x larger).

Sample workload Nemotron 3.5 Content Safety (free) $0 vs $2.08

Nemotron 3.5 Content Safety (free) is free for the standard workload while the other model is estimated at $2.08.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Nemotron 3.5 Content Safety (free) Calculating… Estimated API cost
Qianfan-OCR-Fast Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Nemotron 3.5 Content Safety (free) has the lower input price; Nemotron 3.5 Content Safety (free) has the lower output price; Nemotron 3.5 Content Safety (free) offers the larger context window. For the 1M input plus 500K output sample, Nemotron 3.5 Content Safety (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Nemotron 3.5 Content Safety (free) and $2.08 for Qianfan-OCR-Fast.

Best Fit

Choose Nemotron 3.5 Content Safety (free) when you care most about lower input-token price, lower output-token price, and larger context window.

Choose Qianfan-OCR-Fast when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes
  • On the standard 1M input plus 500K output workload, Nemotron 3.5 Content Safety (free) is estimated at $0 vs $2.08 for Qianfan-OCR-Fast, saving $2.08 (100% lower).
  • Nemotron 3.5 Content Safety (free) is free for the standard workload while the other model is estimated at $2.08.
  • Nemotron 3.5 Content Safety (free) is free for input tokens while Qianfan-OCR-Fast costs $0.68 per 1M tokens.
  • Nemotron 3.5 Content Safety (free) is free for output tokens while Qianfan-OCR-Fast costs $2.81 per 1M tokens.
  • Nemotron 3.5 Content Safety (free) has 62.46K more context (1.95x larger).
Head-to-Head Specs
FeatureNemotron 3.5 Content Safety (free)
(NVIDIA)
Qianfan-OCR-Fast
(Baidu)
Input Price
prompt tokens per 1M
$0$0.68
Completion Price
per 1M tokens
$0$2.81
Sample Workload Cost
1M input + 500K output
$0$2.08
Context Window128K65.54K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionNemotron 3.5 Content Safety (free)On the standard 1M input plus 500K output workload, Nemotron 3.5 Content Safety (free) is estimated at $0 vs $2.08 for Qianfan-OCR-Fast, saving $2.08 (100% lower).
High-volume input processingNemotron 3.5 Content Safety (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsNemotron 3.5 Content Safety (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workNemotron 3.5 Content Safety (free)A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • ERNIE 4.5 21B A3B Thinking can replace Qianfan-OCR-Fast when lower sample workload cost matters most: $0.21.
  • ERNIE 4.5 21B A3B can replace Qianfan-OCR-Fast when lower sample workload cost matters most: $0.21.
  • ERNIE 4.5 VL 28B A3B can replace Qianfan-OCR-Fast when lower sample workload cost matters most: $0.42.
  • ERNIE 4.5 300B A47B can replace Qianfan-OCR-Fast when lower sample workload cost matters most: $0.83.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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NVIDIA catalog

Review all tracked NVIDIA models before deciding whether this matchup is the right shortlist.

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Baidu catalog

Check other Baidu models with comparable pricing, context, or release timing.

Open Baidu models
Nemotron 3.5 Content Safety (free)

NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting...

Qianfan-OCR-Fast

Qianfan-OCR-Fast is a domain-specific multimodal large model purpose-built for OCR. By leveraging specialized OCR training data while preserving versatile multimodal intelligence, it provides a powerful performance upgrade over Qianfan-OCR.