GLM 4.5 Air (free) is free for input tokens while Qwen2.5 VL 72B Instruct costs $0.25 per 1M tokens.
API cost decision in 10 seconds
GLM 4.5 Air (free) vs Qwen2.5 VL 72B Instruct
Pick GLM 4.5 Air (free) 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 GLM 4.5 Air (free) when budget is the priority.
On the standard 1M input plus 500K output workload, GLM 4.5 Air (free) is estimated at $0 vs $0.62 for Qwen2.5 VL 72B Instruct, saving $0.62 (100% lower).
Cost-first pickGLM 4.5 Air (free)
Context-first pickBoth models
Sample savings$0.62100%
10x traffic gap$6.25
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $6.25. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
GLM 4.5 Air (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | GLM 4.5 Air (free) | Qwen2.5 VL 72B Instruct |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | GLM 4.5 Air (free) | $0 | $1.62 |
| Balanced workload | 1M input + 1M output | GLM 4.5 Air (free) | $0 | $1 |
| Output-heavy chatbot | 1M input + 5M output | GLM 4.5 Air (free) | $0 | $4 |
GLM 4.5 Air (free) is free for output tokens while Qwen2.5 VL 72B Instruct costs $0.75 per 1M tokens.
Both models report the same context window at 131.07K tokens.
GLM 4.5 Air (free) is free for the standard workload while the other model is estimated at $0.62.
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 4.5 Air (free) has the lower input price; GLM 4.5 Air (free) has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, GLM 4.5 Air (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for GLM 4.5 Air (free) and $0.62 for Qwen2.5 VL 72B Instruct.
Choose GLM 4.5 Air (free) when you care most about lower input-token price, and lower output-token price.
Choose Qwen2.5 VL 72B 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, GLM 4.5 Air (free) is estimated at $0 vs $0.62 for Qwen2.5 VL 72B Instruct, saving $0.62 (100% lower).
- GLM 4.5 Air (free) is free for the standard workload while the other model is estimated at $0.62.
- GLM 4.5 Air (free) is free for input tokens while Qwen2.5 VL 72B Instruct costs $0.25 per 1M tokens.
- GLM 4.5 Air (free) is free for output tokens while Qwen2.5 VL 72B Instruct costs $0.75 per 1M tokens.
- Both models report the same context window at 131.07K tokens.
| Feature | GLM 4.5 Air (free) (Z.ai) | Qwen2.5 VL 72B Instruct (Qwen) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $0.25 |
| Completion Price per 1M tokens | $0 | $0.75 |
| Sample Workload Cost 1M input + 500K output | $0 | $0.62 |
| Context Window | 131.07K | 131.07K |
| Release Date | ||
| Popularity | #41 | #150 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | GLM 4.5 Air (free) | On the standard 1M input plus 500K output workload, GLM 4.5 Air (free) is estimated at $0 vs $0.62 for Qwen2.5 VL 72B Instruct, saving $0.62 (100% lower). |
| High-volume input processing | GLM 4.5 Air (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | GLM 4.5 Air (free) | 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 Qwen2.5 VL 72B Instruct when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen2.5 VL 72B Instruct when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen2.5 VL 72B Instruct when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen2.5 VL 72B Instruct when lower sample workload cost matters most: $0.11.
- 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 hubsZ.ai catalog
Review all tracked Z.ai models before deciding whether this matchup is the right shortlist.
Open Z.ai modelsQwen catalog
Check other Qwen models with comparable pricing, context, or release timing.
Open Qwen modelsGLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter...
Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.