GPT-6 Luna (batch) is $0.02 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
API cost decision in 10 seconds
NewLing 3.1 Flash vs GPT-6 Luna (batch)
Pick GPT-6 Luna (batch) 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-6 Luna (batch) when budget and context both matter.
On the standard 1M input plus 500K output workload, GPT-6 Luna (batch) is estimated at $0.17 vs $0.19 for Ling 3.1 Flash, saving $0.01 (6.7% lower).
Cost-first pickGPT-6 Luna (batch)
Context-first pickGPT-6 Luna (batch)
Sample savings$0.016.7%
10x traffic gap$0.13
GPT-6 Luna (batch) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $0.13. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Cost winner changes by workload shape: input-heavy / RAG favors GPT-6 Luna (batch), balanced workload favors Tie, and output-heavy chatbot favors Ling 3.1 Flash.
| Workload shape | Token mix | Better pick | Ling 3.1 Flash | GPT-6 Luna (batch) |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | GPT-6 Luna (batch) | $0.49 | $0.38 |
| Balanced workload | 1M input + 1M output | Tie | $0.3 | $0.3 |
| Output-heavy chatbot | 1M input + 5M output | Ling 3.1 Flash | $1.2 | $1.3 |
Ling 3.1 Flash is $0.02 cheaper per 1M output tokens (10% lower; 1.11x difference).
GPT-6 Luna (batch) has 787.86K more context (4.01x larger).
GPT-6 Luna (batch) is $0.01 cheaper on the standard workload (6.7% 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-6 Luna (batch) has the lower input price; Ling 3.1 Flash has the lower output price; GPT-6 Luna (batch) offers the larger context window. For the 1M input plus 500K output sample, GPT-6 Luna (batch) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.19 for Ling 3.1 Flash and $0.17 for GPT-6 Luna (batch).
Choose Ling 3.1 Flash when you care most about lower output-token price.
Choose GPT-6 Luna (batch) when you care most about lower input-token price, and larger context window.
- On the standard 1M input plus 500K output workload, GPT-6 Luna (batch) is estimated at $0.17 vs $0.19 for Ling 3.1 Flash, saving $0.01 (6.7% lower).
- GPT-6 Luna (batch) is $0.01 cheaper on the standard workload (6.7% lower).
- GPT-6 Luna (batch) is $0.02 cheaper per 1M input tokens (33.3% lower; 1.5x difference).
- Ling 3.1 Flash is $0.02 cheaper per 1M output tokens (10% lower; 1.11x difference).
- GPT-6 Luna (batch) has 787.86K more context (4.01x larger).
| Feature | NewLing 3.1 Flash (inclusionAI) | GPT-6 Luna (batch) (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.075 | $0.05 |
| Completion Price per 1M tokens | $0.225 | $0.25 |
| Sample Workload Cost 1M input + 500K output | $0.19 | $0.17 |
| Context Window | 262.14K | 1.05M |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | GPT-6 Luna (batch) | On the standard 1M input plus 500K output workload, GPT-6 Luna (batch) is estimated at $0.17 vs $0.19 for Ling 3.1 Flash, saving $0.01 (6.7% lower). |
| High-volume input processing | GPT-6 Luna (batch) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Ling 3.1 Flash | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-6 Luna (batch) | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Ling 3.0 Flash VL (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- Ling 3.0 Flash Sante (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- Ling 3.0 Flash Fin (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- Ling 3.0 Tiny (free) can replace Ling 3.1 Flash when lower sample workload cost matters most: $0.
- No larger-context model is currently tracked within a close sample-cost band.
- DeepSeek V4.1 Flash · DeepSeek · #1
- Step 5 Preview · StepFun · #2
- GLM 5.3 Flash · Z.ai · #3
- MiMo-V2.6-Flash · Xiaomi · #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 hubsinclusionAI catalog
Review all tracked inclusionAI models before deciding whether this matchup is the right shortlist.
Open inclusionAI modelsOpenAI catalog
Check other OpenAI models with comparable pricing, context, or release timing.
Open OpenAI modelsLing 3.1 Flash is a hybrid reasoning mixture-of-experts model from inclusionAI, with 25B active parameters out of 560B total.
GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic...