API cost decision in 10 seconds
NewGPT-6 Astra vs Laguna M.1
Pick Laguna M.1 for lower cost; pick GPT-6 Astra only if the larger context window matters more.
Budget verdict
Pick Laguna M.1 for lower cost; pick GPT-6 Astra only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Laguna M.1 is estimated at $0.4 vs $35 for GPT-6 Astra, saving $34.6 (98.9% lower).
GPT-6 Astra has more context, but Laguna M.1 saves $34.6 on the standard workload. At 10x that traffic, the same price gap is about $346. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Laguna M.1 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | GPT-6 Astra | Laguna M.1 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Laguna M.1 | $75 | $1.2 |
| Balanced workload | 1M input + 1M output | Laguna M.1 | $60 | $0.6 |
| Output-heavy chatbot | 1M input + 5M output | Laguna M.1 | $260 | $2.2 |
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 has the lower input price, Laguna M.1 has the lower output price, and GPT-6 Astra offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $35 for GPT-6 Astra and $0.4 for Laguna M.1.
Choose GPT-6 Astra when you care most about larger context window.
Choose Laguna M.1 when you care most about lower input-token price, and lower output-token price.
| Feature | NewGPT-6 Astra (OpenAI) | Laguna M.1 (Poolside) |
|---|---|---|
| Input Price prompt tokens per 1M | $10 | $0.2 |
| Completion Price per 1M tokens | $50 | $0.4 |
| Sample Workload Cost 1M input + 500K output | $35 | $0.4 |
| Context Window | 1.05M | 262.14K |
| Release Date | 2026-09-04 | 2026-04-28 |
GPT-6 Astra is OpenAI's flagship model for demanding end-to-end work. It is suited for advanced analysis, software engineering, deep research, scientific work, and document creation, with particular strengths in long-horizon...
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 256K...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Laguna M.1 | On the standard 1M input plus 500K output workload, Laguna M.1 is estimated at $0.4 vs $35 for GPT-6 Astra, saving $34.6 (98.9% lower). |
| High-volume input processing | Laguna M.1 | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | Laguna M.1 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-6 Astra | A larger context window leaves more room for retrieved passages and source files. |