Both models report the same input price at $2 per 1M tokens.
API cost decision in 10 seconds
NewQwen3.8 2.4T A95B vs GPT-5.6 Terra Pro
Pick Qwen3.8 2.4T A95B for lower cost; pick GPT-5.6 Terra Pro 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 Qwen3.8 2.4T A95B for lower cost; pick GPT-5.6 Terra Pro only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Qwen3.8 2.4T A95B is estimated at $5 vs $8 for GPT-5.6 Terra Pro, saving $3 (37.5% lower).
Cost-first pickQwen3.8 2.4T A95B
Context-first pickGPT-5.6 Terra Pro
Sample savings$337.5%
10x traffic gap$30
GPT-5.6 Terra Pro has more context, but Qwen3.8 2.4T A95B saves $3 on the standard workload. At 10x that traffic, the same price gap is about $30. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Qwen3.8 2.4T A95B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3.8 2.4T A95B | GPT-5.6 Terra Pro |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen3.8 2.4T A95B | $13 | $16 |
| Balanced workload | 1M input + 1M output | Qwen3.8 2.4T A95B | $8 | $14 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3.8 2.4T A95B | $32 | $62 |
Qwen3.8 2.4T A95B is $6 cheaper per 1M output tokens (50% lower; 2x difference).
GPT-5.6 Terra Pro has 1.42K more context (1x larger).
Qwen3.8 2.4T A95B is $3 cheaper on the standard workload (37.5% 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
both models tie on input price; Qwen3.8 2.4T A95B has the lower output price; GPT-5.6 Terra Pro offers the larger context window. For the 1M input plus 500K output sample, Qwen3.8 2.4T A95B 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 $8 for GPT-5.6 Terra Pro.
Choose Qwen3.8 2.4T A95B when you care most about lower output-token price.
Choose GPT-5.6 Terra Pro when you care most about larger context window.
- On the standard 1M input plus 500K output workload, Qwen3.8 2.4T A95B is estimated at $5 vs $8 for GPT-5.6 Terra Pro, saving $3 (37.5% lower).
- Qwen3.8 2.4T A95B is $3 cheaper on the standard workload (37.5% lower).
- Both models report the same input price at $2 per 1M tokens.
- Qwen3.8 2.4T A95B is $6 cheaper per 1M output tokens (50% lower; 2x difference).
- GPT-5.6 Terra Pro has 1.42K more context (1x larger).
| Feature | NewQwen3.8 2.4T A95B (Qwen) | GPT-5.6 Terra Pro (OpenAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $2 | $2 |
| Completion Price per 1M tokens | $6 | $12 |
| Sample Workload Cost 1M input + 500K output | $5 | $8 |
| Context Window | 1.05M | 1.05M |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen3.8 2.4T A95B | On the standard 1M input plus 500K output workload, Qwen3.8 2.4T A95B is estimated at $5 vs $8 for GPT-5.6 Terra Pro, saving $3 (37.5% lower). |
| High-volume input processing | Tie | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen3.8 2.4T A95B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | GPT-5.6 Terra Pro | 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
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 modelsOpenAI catalog
Check other OpenAI models with comparable pricing, context, or release timing.
Open OpenAI 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...
GPT-5.6 Terra Pro is the same underlying model as [GPT-5.6 Terra](https://openrouter.ai/openai/gpt-5.6-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode