API cost decision in 10 seconds

Gemini 3.5 Flash Lite (batch) vs Qianfan-OCR-Fast

Pick Gemini 3.5 Flash Lite (batch) 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 Gemini 3.5 Flash Lite (batch) when budget and context both matter.

On the standard 1M input plus 500K output workload, Gemini 3.5 Flash Lite (batch) is estimated at $0.78 vs $2.08 for Qianfan-OCR-Fast, saving $1.31 (62.8% lower).

Cost-first pickGemini 3.5 Flash Lite (batch)
Context-first pickGemini 3.5 Flash Lite (batch)
Sample savings$1.3162.8%
10x traffic gap$13.1

Gemini 3.5 Flash Lite (batch) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $13.1. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Gemini 3.5 Flash Lite (batch) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickGemini 3.5 Flash Lite (batch)Qianfan-OCR-Fast
Input-heavy / RAG5M input + 500K outputGemini 3.5 Flash Lite (batch)$1.38$4.81
Balanced workload1M input + 1M outputGemini 3.5 Flash Lite (batch)$1.4$3.49
Output-heavy chatbot1M input + 5M outputGemini 3.5 Flash Lite (batch)$6.4$14.73
Cheaper input Gemini 3.5 Flash Lite (batch) $0.15 vs $0.68 / 1M

Gemini 3.5 Flash Lite (batch) is $0.53 cheaper per 1M input tokens (77.9% lower; 4.53x difference).

Cheaper output Gemini 3.5 Flash Lite (batch) $1.25 vs $2.81 / 1M

Gemini 3.5 Flash Lite (batch) is $1.56 cheaper per 1M output tokens (55.5% lower; 2.25x difference).

Larger context Gemini 3.5 Flash Lite (batch) 1.05M vs 65.54K

Gemini 3.5 Flash Lite (batch) has 983.04K more context (16x larger).

Sample workload Gemini 3.5 Flash Lite (batch) $0.78 vs $2.08

Gemini 3.5 Flash Lite (batch) is $1.31 cheaper on the standard workload (62.8% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Gemini 3.5 Flash Lite (batch) 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

Gemini 3.5 Flash Lite (batch) has the lower input price; Gemini 3.5 Flash Lite (batch) has the lower output price; Gemini 3.5 Flash Lite (batch) offers the larger context window. For the 1M input plus 500K output sample, Gemini 3.5 Flash Lite (batch) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.78 for Gemini 3.5 Flash Lite (batch) and $2.08 for Qianfan-OCR-Fast.

Best Fit

Choose Gemini 3.5 Flash Lite (batch) 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, Gemini 3.5 Flash Lite (batch) is estimated at $0.78 vs $2.08 for Qianfan-OCR-Fast, saving $1.31 (62.8% lower).
  • Gemini 3.5 Flash Lite (batch) is $1.31 cheaper on the standard workload (62.8% lower).
  • Gemini 3.5 Flash Lite (batch) is $0.53 cheaper per 1M input tokens (77.9% lower; 4.53x difference).
  • Gemini 3.5 Flash Lite (batch) is $1.56 cheaper per 1M output tokens (55.5% lower; 2.25x difference).
  • Gemini 3.5 Flash Lite (batch) has 983.04K more context (16x larger).
Head-to-Head Specs
FeatureGemini 3.5 Flash Lite (batch)
(Google)
Qianfan-OCR-Fast
(Baidu)
Input Price
prompt tokens per 1M
$0.15$0.68
Completion Price
per 1M tokens
$1.25$2.81
Sample Workload Cost
1M input + 500K output
$0.78$2.08
Context Window1.05M65.54K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionGemini 3.5 Flash Lite (batch)On the standard 1M input plus 500K output workload, Gemini 3.5 Flash Lite (batch) is estimated at $0.78 vs $2.08 for Qianfan-OCR-Fast, saving $1.31 (62.8% lower).
High-volume input processingGemini 3.5 Flash Lite (batch)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsGemini 3.5 Flash Lite (batch)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGemini 3.5 Flash Lite (batch)A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • Gemma 4 26B A4B (free) can replace Gemini 3.5 Flash Lite (batch) when lower sample workload cost matters most: $0.
  • Gemma 4 31B (free) can replace Gemini 3.5 Flash Lite (batch) when lower sample workload cost matters most: $0.
  • Lyria 3 Pro Preview can replace Gemini 3.5 Flash Lite (batch) when lower sample workload cost matters most: $0.
  • Lyria 3 Clip Preview can replace Gemini 3.5 Flash Lite (batch) when lower sample workload cost matters most: $0.

Cheaper alternatives

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

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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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Google catalog

Review all tracked Google 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
Gemini 3.5 Flash Lite (batch)

Gemini 3.5 Flash Lite is a high-efficiency model from Google with upgraded agentic capabilities. It is suited for subagents that execute focused tasks within complex, multi-agent workflows.

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.