Qwen3 30B A3B Instruct 2507 is $0.03 cheaper per 1M input tokens (39.9% lower; 1.66x difference).
API cost decision in 10 seconds
Qwen3 32B vs Qwen3 30B A3B Instruct 2507
Pick Qwen3 30B A3B Instruct 2507 when budget is the priority.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Qwen3 30B A3B Instruct 2507 when budget is the priority.
On the standard 1M input plus 500K output workload, Qwen3 30B A3B Instruct 2507 is estimated at $0.14 vs $0.22 for Qwen3 32B, saving $0.08 (34.3% lower).
Cost-first pickQwen3 30B A3B Instruct 2507
Context-first pickBoth models
Sample savings$0.0834.3%
10x traffic gap$0.75
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $0.75. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Qwen3 30B A3B Instruct 2507 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3 32B | Qwen3 30B A3B Instruct 2507 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen3 30B A3B Instruct 2507 | $0.54 | $0.34 |
| Balanced workload | 1M input + 1M output | Qwen3 30B A3B Instruct 2507 | $0.36 | $0.24 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3 30B A3B Instruct 2507 | $1.48 | $1.01 |
Qwen3 30B A3B Instruct 2507 is $0.09 cheaper per 1M output tokens (31.1% lower; 1.45x difference).
Both models report the same context window at 131.07K tokens.
Qwen3 30B A3B Instruct 2507 is $0.08 cheaper on the standard workload (34.3% 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 30B A3B Instruct 2507 has the lower input price; Qwen3 30B A3B Instruct 2507 has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3 30B A3B Instruct 2507 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.22 for Qwen3 32B and $0.14 for Qwen3 30B A3B Instruct 2507.
Choose Qwen3 32B when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose Qwen3 30B A3B Instruct 2507 when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Qwen3 30B A3B Instruct 2507 is estimated at $0.14 vs $0.22 for Qwen3 32B, saving $0.08 (34.3% lower).
- Qwen3 30B A3B Instruct 2507 is $0.08 cheaper on the standard workload (34.3% lower).
- Qwen3 30B A3B Instruct 2507 is $0.03 cheaper per 1M input tokens (39.9% lower; 1.66x difference).
- Qwen3 30B A3B Instruct 2507 is $0.09 cheaper per 1M output tokens (31.1% lower; 1.45x difference).
- Both models report the same context window at 131.07K tokens.
| Feature | Qwen3 32B (Qwen) | Qwen3 30B A3B Instruct 2507 (Qwen) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.08 | $0.0481 |
| Completion Price per 1M tokens | $0.28 | $0.193 |
| Sample Workload Cost 1M input + 500K output | $0.22 | $0.14 |
| Context Window | 131.07K | 131.07K |
| Release Date | ||
| Popularity | #76 | #90 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen3 30B A3B Instruct 2507 | On the standard 1M input plus 500K output workload, Qwen3 30B A3B Instruct 2507 is estimated at $0.14 vs $0.22 for Qwen3 32B, saving $0.08 (34.3% lower). |
| High-volume input processing | Qwen3 30B A3B Instruct 2507 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen3 30B A3B Instruct 2507 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | 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 32B when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3 32B when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3 32B when lower sample workload cost matters most: $0.09.
- Qwen3 235B A22B Instruct 2507 can replace Qwen3 32B 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 modelsQwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...