Ling-3.0-flash (free) is free for input tokens while Qwen3.8 2.4T A95B costs $2 per 1M tokens.
API cost decision in 10 seconds
NewQwen3.8 2.4T A95B vs Ling-3.0-flash (free)
Pick Ling-3.0-flash (free) for lower cost; pick Qwen3.8 2.4T A95B only if the larger context window matters more.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Ling-3.0-flash (free) for lower cost; pick Qwen3.8 2.4T A95B only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Ling-3.0-flash (free) is estimated at $0 vs $5 for Qwen3.8 2.4T A95B, saving $5 (100% lower).
Cost-first pickLing-3.0-flash (free)
Context-first pickQwen3.8 2.4T A95B
Sample savings$5100%
10x traffic gap$50
Qwen3.8 2.4T A95B has more context, but Ling-3.0-flash (free) saves $5 on the standard workload. At 10x that traffic, the same price gap is about $50. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Ling-3.0-flash (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3.8 2.4T A95B | Ling-3.0-flash (free) |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Ling-3.0-flash (free) | $13 | $0 |
| Balanced workload | 1M input + 1M output | Ling-3.0-flash (free) | $8 | $0 |
| Output-heavy chatbot | 1M input + 5M output | Ling-3.0-flash (free) | $32 | $0 |
Ling-3.0-flash (free) is free for output tokens while Qwen3.8 2.4T A95B costs $6 per 1M tokens.
Qwen3.8 2.4T A95B has 786.43K more context (4x larger).
Ling-3.0-flash (free) is free for the standard workload while the other model is estimated at $5.
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 (free) has the lower input price; Ling-3.0-flash (free) has the lower output price; Qwen3.8 2.4T A95B offers the larger context window. For the 1M input plus 500K output sample, Ling-3.0-flash (free) is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $5 for Qwen3.8 2.4T A95B and $0 for Ling-3.0-flash (free).
Choose Qwen3.8 2.4T A95B when you care most about larger context window.
Choose Ling-3.0-flash (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 (free) is estimated at $0 vs $5 for Qwen3.8 2.4T A95B, saving $5 (100% lower).
- Ling-3.0-flash (free) is free for the standard workload while the other model is estimated at $5.
- Ling-3.0-flash (free) is free for input tokens while Qwen3.8 2.4T A95B costs $2 per 1M tokens.
- Ling-3.0-flash (free) is free for output tokens while Qwen3.8 2.4T A95B costs $6 per 1M tokens.
- Qwen3.8 2.4T A95B has 786.43K more context (4x larger).
| Feature | NewQwen3.8 2.4T A95B (Qwen) | Ling-3.0-flash (free) (inclusionAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $2 | $0 |
| Completion Price per 1M tokens | $6 | $0 |
| Sample Workload Cost 1M input + 500K output | $5 | $0 |
| Context Window | 1.05M | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Ling-3.0-flash (free) | On the standard 1M input plus 500K output workload, Ling-3.0-flash (free) is estimated at $0 vs $5 for Qwen3.8 2.4T A95B, saving $5 (100% lower). |
| High-volume input processing | Ling-3.0-flash (free) | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Ling-3.0-flash (free) | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Qwen3.8 2.4T A95B | 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 Qwen3.8 2.4T A95B when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3.8 2.4T A95B when lower sample workload cost matters most: $0.
- Qwen3.7 Flash can replace Qwen3.8 2.4T A95B when lower sample workload cost matters most: $0.1.
- Qwen3 30B A3B Instruct 2507 can replace Qwen3.8 2.4T A95B when lower sample workload cost matters most: $0.14.
- Grok 4.20 Multi-Agent offers 2M context with $2.5 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- DeepSeek V4 Flash 0731 offers 1.31M context with $0.17 sample workload cost.
- DeepSeek V4 Flash Latest offers 1.31M context with $0.11 sample workload cost.
- DeepSeek V4 Flash 0731 · DeepSeek · #1
- MiMo-V2.5 · Xiaomi · #2
- Hy3 · Tencent · #3
- Ox Alpha · stealth · #4
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Open inclusionAI modelsQwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total. It is...
*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and production-scale agentic inference* as key priorities, enabling developers...