KAT-Coder-Air V2.5 is $0.53 cheaper per 1M input tokens (77.9% lower; 4.53x difference).
API cost decision in 10 seconds
KAT-Coder-Air V2.5 vs Qianfan-OCR-Fast
Pick KAT-Coder-Air V2.5 when budget and context both matter.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick KAT-Coder-Air V2.5 when budget and context both matter.
On the standard 1M input plus 500K output workload, KAT-Coder-Air V2.5 is estimated at $0.45 vs $2.08 for Qianfan-OCR-Fast, saving $1.64 (78.4% lower).
Cost-first pickKAT-Coder-Air V2.5
Context-first pickKAT-Coder-Air V2.5
Sample savings$1.6478.4%
10x traffic gap$16.35
KAT-Coder-Air V2.5 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $16.35. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
KAT-Coder-Air V2.5 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | KAT-Coder-Air V2.5 | Qianfan-OCR-Fast |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | KAT-Coder-Air V2.5 | $1.05 | $4.81 |
| Balanced workload | 1M input + 1M output | KAT-Coder-Air V2.5 | $0.75 | $3.49 |
| Output-heavy chatbot | 1M input + 5M output | KAT-Coder-Air V2.5 | $3.15 | $14.73 |
KAT-Coder-Air V2.5 is $2.21 cheaper per 1M output tokens (78.6% lower; 4.68x difference).
KAT-Coder-Air V2.5 has 190.46K more context (3.91x larger).
KAT-Coder-Air V2.5 is $1.64 cheaper on the standard workload (78.4% lower).
Estimate your workload cost
Your Workload Cost
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
KAT-Coder-Air V2.5 has the lower input price; KAT-Coder-Air V2.5 has the lower output price; KAT-Coder-Air V2.5 offers the larger context window. For the 1M input plus 500K output sample, KAT-Coder-Air V2.5 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.45 for KAT-Coder-Air V2.5 and $2.08 for Qianfan-OCR-Fast.
Choose KAT-Coder-Air V2.5 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.
- On the standard 1M input plus 500K output workload, KAT-Coder-Air V2.5 is estimated at $0.45 vs $2.08 for Qianfan-OCR-Fast, saving $1.64 (78.4% lower).
- KAT-Coder-Air V2.5 is $1.64 cheaper on the standard workload (78.4% lower).
- KAT-Coder-Air V2.5 is $0.53 cheaper per 1M input tokens (77.9% lower; 4.53x difference).
- KAT-Coder-Air V2.5 is $2.21 cheaper per 1M output tokens (78.6% lower; 4.68x difference).
- KAT-Coder-Air V2.5 has 190.46K more context (3.91x larger).
| Feature | KAT-Coder-Air V2.5 (Kwaipilot) | Qianfan-OCR-Fast (Baidu) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.15 | $0.68 |
| Completion Price per 1M tokens | $0.6 | $2.81 |
| Sample Workload Cost 1M input + 500K output | $0.45 | $2.08 |
| Context Window | 256K | 65.54K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | KAT-Coder-Air V2.5 | On the standard 1M input plus 500K output workload, KAT-Coder-Air V2.5 is estimated at $0.45 vs $2.08 for Qianfan-OCR-Fast, saving $1.64 (78.4% lower). |
| High-volume input processing | KAT-Coder-Air V2.5 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | KAT-Coder-Air V2.5 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | KAT-Coder-Air V2.5 | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
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Open Baidu modelsKAT-Coder-Air V2.5 is a flagship-level Agentic Coding model that can directly hand over an entire issue or an entire business workflow to it, allowing it to autonomously locate and make...
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.