GPT-5 Nano is $0.05 cheaper per 1M input tokens (51.9% lower; 2.08x difference).
API cost decision in 10 seconds
GPT-5 Nano vs Qwen3 VL 32B Instruct
Pick GPT-5 Nano when budget and context both matter.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick GPT-5 Nano when budget and context both matter.
On the standard 1M input plus 500K output workload, GPT-5 Nano is estimated at $0.25 vs $0.31 for Qwen3 VL 32B Instruct, saving $0.06 (19.9% lower).
Cost-first pickGPT-5 Nano
Context-first pickGPT-5 Nano
Sample savings$0.0619.9%
10x traffic gap$0.62
GPT-5 Nano is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $0.62. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
GPT-5 Nano stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | GPT-5 Nano | Qwen3 VL 32B Instruct |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | GPT-5 Nano | $0.45 | $0.73 |
| Balanced workload | 1M input + 1M output | GPT-5 Nano | $0.45 | $0.52 |
| Output-heavy chatbot | 1M input + 5M output | GPT-5 Nano | $2.05 | $2.18 |
GPT-5 Nano is $0.02 cheaper per 1M output tokens (3.8% lower; 1.04x difference).
GPT-5 Nano has 137.86K more context (1.53x larger).
GPT-5 Nano is $0.06 cheaper on the standard workload (19.9% 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
GPT-5 Nano has the lower input price; GPT-5 Nano has the lower output price; GPT-5 Nano offers the larger context window. For the 1M input plus 500K output sample, GPT-5 Nano is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.25 for GPT-5 Nano and $0.31 for Qwen3 VL 32B Instruct.
Choose GPT-5 Nano when you care most about lower input-token price, lower output-token price, and larger context window.
Choose Qwen3 VL 32B Instruct 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, GPT-5 Nano is estimated at $0.25 vs $0.31 for Qwen3 VL 32B Instruct, saving $0.06 (19.9% lower).
- GPT-5 Nano is $0.06 cheaper on the standard workload (19.9% lower).
- GPT-5 Nano is $0.05 cheaper per 1M input tokens (51.9% lower; 2.08x difference).
- GPT-5 Nano is $0.02 cheaper per 1M output tokens (3.8% lower; 1.04x difference).
- GPT-5 Nano has 137.86K more context (1.53x larger).
| Feature | GPT-5 Nano (OpenAI) | Qwen3 VL 32B Instruct (Qwen) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.05 | $0.104 |
| Completion Price per 1M tokens | $0.4 | $0.416 |
| Sample Workload Cost 1M input + 500K output | $0.25 | $0.31 |
| Context Window | 400K | 262.14K |
| Release Date | ||
| Popularity | #68 | #126 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | GPT-5 Nano | On the standard 1M input plus 500K output workload, GPT-5 Nano is estimated at $0.25 vs $0.31 for Qwen3 VL 32B Instruct, saving $0.06 (19.9% lower). |
| High-volume input processing | GPT-5 Nano | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | GPT-5 Nano | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-5 Nano | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- gpt-oss-120b (free) can replace GPT-5 Nano when lower sample workload cost matters most: $0.
- gpt-oss-20b (free) can replace GPT-5 Nano when lower sample workload cost matters most: $0.
- gpt-oss-20b can replace GPT-5 Nano when lower sample workload cost matters most: $0.1.
- gpt-oss-120b can replace GPT-5 Nano when lower sample workload cost matters most: $0.13.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
- Gemini 2.5 Flash Lite offers 1.05M context with $0.3 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #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 hubsOpenAI catalog
Review all tracked OpenAI models before deciding whether this matchup is the right shortlist.
Open OpenAI modelsQwen catalog
Check other Qwen models with comparable pricing, context, or release timing.
Open Qwen modelsGPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text...