API cost decision in 10 seconds
Laguna M.1 (free) vs Qwen3 VL 32B Instruct
Pick Laguna M.1 (free) for lower cost; pick Qwen3 VL 32B Instruct only if the larger context window matters more.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Laguna M.1 (free) for lower cost; pick Qwen3 VL 32B Instruct only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $0.31 for Qwen3 VL 32B Instruct, saving $0.31 (100% lower).
Cost-first pickLaguna M.1 (free)
Context-first pickQwen3 VL 32B Instruct
Sample savings$0.31100%
10x traffic gap$3.12
Qwen3 VL 32B Instruct has more context, but Laguna M.1 (free) saves $0.31 on the standard workload. At 10x that traffic, the same price gap is about $3.12. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Laguna M.1 (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Laguna M.1 (free) | Qwen3 VL 32B Instruct |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Laguna M.1 (free) | $0 | $0.73 |
| Balanced workload | 1M input + 1M output | Laguna M.1 (free) | $0 | $0.52 |
| Output-heavy chatbot | 1M input + 5M output | Laguna M.1 (free) | $0 | $2.18 |
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
Laguna M.1 (free) has the lower input price, Laguna M.1 (free) has the lower output price, and Qwen3 VL 32B Instruct offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Laguna M.1 (free) and $0.31 for Qwen3 VL 32B Instruct.
Choose Laguna M.1 (free) when you care most about lower input-token price, and lower output-token price.
Choose Qwen3 VL 32B Instruct when you care most about larger context window.
| Feature | Laguna M.1 (free) (Poolside) | Qwen3 VL 32B Instruct (Qwen) |
|---|---|---|
| Input Price prompt tokens per 1M | $0 | $0.1 |
| Completion Price per 1M tokens | $0 | $0.42 |
| Sample Workload Cost 1M input + 500K output | $0 | $0.31 |
| Context Window | 131.07K | 262.14K |
| Release Date | 2026-04-28 | 2025-10-23 |
Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 128K...
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...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Laguna M.1 (free) | On the standard 1M input plus 500K output workload, Laguna M.1 (free) is estimated at $0 vs $0.31 for Qwen3 VL 32B Instruct, saving $0.31 (100% lower). |
| High-volume input processing | Laguna M.1 (free) | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | Laguna M.1 (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Qwen3 VL 32B Instruct | A larger context window leaves more room for retrieved passages and source files. |