API cost decision in 10 seconds
Qianfan-OCR-Fast vs 🔥MiniMax M2.7
Pick MiniMax M2.7 when budget and context both matter.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick MiniMax M2.7 when budget and context both matter.
On the standard 1M input plus 500K output workload, MiniMax M2.7 is estimated at $0.88 vs $2.08 for Qianfan-OCR-Fast, saving $1.21 (57.8% lower).
Cost-first pickMiniMax M2.7
Context-first pickMiniMax M2.7
Sample savings$1.2157.8%
10x traffic gap$12.06
MiniMax M2.7 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $12.06. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
MiniMax M2.7 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qianfan-OCR-Fast | MiniMax M2.7 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiniMax M2.7 | $4.81 | $2 |
| Balanced workload | 1M input + 1M output | MiniMax M2.7 | $3.49 | $1.48 |
| Output-heavy chatbot | 1M input + 5M output | MiniMax M2.7 | $14.73 | $6.28 |
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
MiniMax M2.7 has the lower input price, MiniMax M2.7 has the lower output price, and MiniMax M2.7 offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $2.08 for Qianfan-OCR-Fast and $0.88 for MiniMax M2.7.
Choose Qianfan-OCR-Fast when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose MiniMax M2.7 when you care most about lower input-token price, lower output-token price, and larger context window.
| Feature | Qianfan-OCR-Fast (Baidu) | 🔥MiniMax M2.7 (MiniMax) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.68 | $0.28 |
| Completion Price per 1M tokens | $2.81 | $1.2 |
| Sample Workload Cost 1M input + 500K output | $2.08 | $0.88 |
| Context Window | 65.54K | 204.8K |
| Release Date | 2026-04-20 | 2026-03-18 |
| Popularity | #14 |
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.
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | MiniMax M2.7 | On the standard 1M input plus 500K output workload, MiniMax M2.7 is estimated at $0.88 vs $2.08 for Qianfan-OCR-Fast, saving $1.21 (57.8% lower). |
| High-volume input processing | MiniMax M2.7 | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | MiniMax M2.7 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | MiniMax M2.7 | A larger context window leaves more room for retrieved passages and source files. |