API cost decision in 10 seconds
GLM 4.7 Flash vs 🔥DeepSeek V3.2
Pick GLM 4.7 Flash when budget and context both matter.
Budget verdict
Pick GLM 4.7 Flash when budget and context both matter.
On the standard 1M input plus 500K output workload, GLM 4.7 Flash is estimated at $0.26 vs $0.44 for DeepSeek V3.2, saving $0.18 (41% lower).
GLM 4.7 Flash is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $1.81. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
GLM 4.7 Flash stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | GLM 4.7 Flash | DeepSeek V3.2 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | GLM 4.7 Flash | $0.5 | $1.45 |
| Balanced workload | 1M input + 1M output | GLM 4.7 Flash | $0.46 | $0.63 |
| Output-heavy chatbot | 1M input + 5M output | GLM 4.7 Flash | $2.06 | $2.14 |
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
GLM 4.7 Flash has the lower input price, DeepSeek V3.2 has the lower output price, and GLM 4.7 Flash offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.26 for GLM 4.7 Flash and $0.44 for DeepSeek V3.2.
Choose GLM 4.7 Flash when you care most about lower input-token price, and larger context window.
Choose DeepSeek V3.2 when you care most about lower output-token price.
| Feature | GLM 4.7 Flash (Z.ai) | 🔥DeepSeek V3.2 (DeepSeek) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.06 | $0.25 |
| Completion Price per 1M tokens | $0.4 | $0.38 |
| Sample Workload Cost 1M input + 500K output | $0.26 | $0.44 |
| Context Window | 202.75K | 131.07K |
| Release Date | 2026-01-19 | 2025-12-01 |
| Popularity | #8 |
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | GLM 4.7 Flash | On the standard 1M input plus 500K output workload, GLM 4.7 Flash is estimated at $0.26 vs $0.44 for DeepSeek V3.2, saving $0.18 (41% lower). |
| High-volume input processing | GLM 4.7 Flash | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | DeepSeek V3.2 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GLM 4.7 Flash | A larger context window leaves more room for retrieved passages and source files. |