Ling 3.0 Flash Fin (free) is free for input tokens while Qwen3.8 Omni Flash costs $0.15 per 1M tokens.
API cost decision in 10 seconds
NewQwen3.8 Omni Flash vs Ling 3.0 Flash Fin (free)
Pick Ling 3.0 Flash Fin (free) for lower cost; pick Qwen3.8 Omni Flash only if the larger context window matters more.
Budget verdict
Pick Ling 3.0 Flash Fin (free) for lower cost; pick Qwen3.8 Omni Flash only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Ling 3.0 Flash Fin (free) is estimated at $0 vs $0.39 for Qwen3.8 Omni Flash, saving $0.39 (100% lower).
Qwen3.8 Omni Flash has more context, but Ling 3.0 Flash Fin (free) saves $0.39 on the standard workload. At 10x that traffic, the same price gap is about $3.85. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Ling 3.0 Flash Fin (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3.8 Omni Flash | Ling 3.0 Flash Fin (free) |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Ling 3.0 Flash Fin (free) | $0.98 | $0 |
| Balanced workload | 1M input + 1M output | Ling 3.0 Flash Fin (free) | $0.62 | $0 |
| Output-heavy chatbot | 1M input + 5M output | Ling 3.0 Flash Fin (free) | $2.5 | $0 |
Ling 3.0 Flash Fin (free) is free for output tokens while Qwen3.8 Omni Flash costs $0.47 per 1M tokens.
Qwen3.8 Omni Flash has 737.86K more context (3.81x larger).
Ling 3.0 Flash Fin (free) is free for the standard workload while the other model is estimated at $0.39.
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
Ling 3.0 Flash Fin (free) has the lower input price; Ling 3.0 Flash Fin (free) has the lower output price; Qwen3.8 Omni Flash offers the larger context window. For the 1M input plus 500K output sample, Ling 3.0 Flash Fin (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.39 for Qwen3.8 Omni Flash and $0 for Ling 3.0 Flash Fin (free).
Choose Qwen3.8 Omni Flash when you care most about larger context window.
Choose Ling 3.0 Flash Fin (free) when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Ling 3.0 Flash Fin (free) is estimated at $0 vs $0.39 for Qwen3.8 Omni Flash, saving $0.39 (100% lower).
- Ling 3.0 Flash Fin (free) is free for the standard workload while the other model is estimated at $0.39.
- Ling 3.0 Flash Fin (free) is free for input tokens while Qwen3.8 Omni Flash costs $0.15 per 1M tokens.
- Ling 3.0 Flash Fin (free) is free for output tokens while Qwen3.8 Omni Flash costs $0.47 per 1M tokens.
- Qwen3.8 Omni Flash has 737.86K more context (3.81x larger).
| Feature | NewQwen3.8 Omni Flash (Qwen) | Ling 3.0 Flash Fin (free) (inclusionAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.15 | $0 |
| Completion Price per 1M tokens | $0.47 | $0 |
| Sample Workload Cost 1M input + 500K output | $0.39 | $0 |
| Context Window | 1M | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Ling 3.0 Flash Fin (free) | On the standard 1M input plus 500K output workload, Ling 3.0 Flash Fin (free) is estimated at $0 vs $0.39 for Qwen3.8 Omni Flash, saving $0.39 (100% lower). |
| High-volume input processing | Ling 3.0 Flash Fin (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Ling 3.0 Flash Fin (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Qwen3.8 Omni Flash | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- Qwen3.8 27B (free) can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.
- Qwen3 Next 80B A3B Instruct (free) can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.
- Qwen3.7 Flash can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.1.
- GLM 5.3 Flash offers 1.31M context with $0.4 sample workload cost.
- DeepSeek V4 Flash 0731 offers 1.31M context with $0.36 sample workload cost.
- GLM Flash Latest offers 1.31M context with $0.2 sample workload cost.
- DeepSeek V4 Flash Latest offers 1.31M context with $0.43 sample workload cost.
- MiMo-V2.6-Pro · Xiaomi · #1
- Qwen3.8 Max (0902) · Qwen · #2
- DeepSeek V4.1 Flash · DeepSeek · #3
- GLM 5.3 Flash · Z.ai · #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 hubsQwen catalog
Review all tracked Qwen models before deciding whether this matchup is the right shortlist.
Open Qwen modelsinclusionAI catalog
Check other inclusionAI models with comparable pricing, context, or release timing.
Open inclusionAI modelsQwen3.8 Omni Flash is an omni-modal reasoning model from Alibaba, the first Qwen model built around agentic capabilities with native audio-video understanding. It is suited for audio-video analysis and summarization,...
Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment...