Qwen3.5 397B A17B is $0.11 cheaper per 1M input tokens (23% lower; 1.3x difference).
API cost decision in 10 seconds
Qwen3.5 397B A17B vs R1 0528
Pick R1 0528 for lower cost; pick Qwen3.5 397B A17B only if the larger context window matters more.
Budget verdict
Pick R1 0528 for lower cost; pick Qwen3.5 397B A17B only if the larger context window matters more.
On the standard 1M input plus 500K output workload, R1 0528 is estimated at $1.57 vs $1.61 for Qwen3.5 397B A17B, saving $0.04 (2.2% lower).
Qwen3.5 397B A17B has more context, but R1 0528 saves $0.04 on the standard workload. At 10x that traffic, the same price gap is about $0.35. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Cost winner changes by workload shape: input-heavy / RAG favors Qwen3.5 397B A17B, balanced workload favors R1 0528, and output-heavy chatbot favors R1 0528.
| Workload shape | Token mix | Better pick | Qwen3.5 397B A17B | R1 0528 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen3.5 397B A17B | $3.15 | $3.58 |
| Balanced workload | 1M input + 1M output | R1 0528 | $2.83 | $2.65 |
| Output-heavy chatbot | 1M input + 5M output | R1 0528 | $12.63 | $11.25 |
R1 0528 is $0.3 cheaper per 1M output tokens (12.2% lower; 1.14x difference).
Qwen3.5 397B A17B has 92.16K more context (1.56x larger).
R1 0528 is $0.04 cheaper on the standard workload (2.2% 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
Qwen3.5 397B A17B has the lower input price; R1 0528 has the lower output price; Qwen3.5 397B A17B offers the larger context window. For the 1M input plus 500K output sample, R1 0528 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.61 for Qwen3.5 397B A17B and $1.57 for R1 0528.
Choose Qwen3.5 397B A17B when you care most about lower input-token price, and larger context window.
Choose R1 0528 when you care most about lower output-token price.
- On the standard 1M input plus 500K output workload, R1 0528 is estimated at $1.57 vs $1.61 for Qwen3.5 397B A17B, saving $0.04 (2.2% lower).
- R1 0528 is $0.04 cheaper on the standard workload (2.2% lower).
- Qwen3.5 397B A17B is $0.11 cheaper per 1M input tokens (23% lower; 1.3x difference).
- R1 0528 is $0.3 cheaper per 1M output tokens (12.2% lower; 1.14x difference).
- Qwen3.5 397B A17B has 92.16K more context (1.56x larger).
| Feature | Qwen3.5 397B A17B (Qwen) | R1 0528 (DeepSeek) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.385 | $0.5 |
| Completion Price per 1M tokens | $2.45 | $2.15 |
| Sample Workload Cost 1M input + 500K output | $1.61 | $1.57 |
| Context Window | 256K | 163.84K |
| Release Date | ||
| Popularity | #49 | #98 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | R1 0528 | On the standard 1M input plus 500K output workload, R1 0528 is estimated at $1.57 vs $1.61 for Qwen3.5 397B A17B, saving $0.04 (2.2% lower). |
| High-volume input processing | Qwen3.5 397B A17B | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | R1 0528 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Qwen3.5 397B A17B | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Qwen3 Next 80B A3B Instruct (free) can replace Qwen3.5 397B A17B when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3.5 397B A17B when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3.5 397B A17B when lower sample workload cost matters most: $0.09.
- Qwen3 235B A22B Instruct 2507 can replace Qwen3.5 397B A17B when lower sample workload cost matters most: $0.14.
- Llama 4 Scout offers 10M context with $0.25 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash offers 1.05M context with $0.17 sample workload cost.
- MiMo-V2.5 offers 1.05M context with $0.24 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- MiMo-V2.5 · Xiaomi · #3
- MiniMax M3 · MiniMax · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsQwen catalog
Review all tracked Qwen models before deciding whether this matchup is the right shortlist.
Open Qwen modelsDeepSeek catalog
Check other DeepSeek models with comparable pricing, context, or release timing.
Open DeepSeek modelsThe Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...