Qwen3.5-122B-A10B is $0.14 cheaper per 1M input tokens (35% lower; 1.54x difference).
API cost decision in 10 seconds
Qwen3.5-122B-A10B vs Kimi K2.5
Pick Qwen3.5-122B-A10B when budget is the priority.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Qwen3.5-122B-A10B when budget is the priority.
On the standard 1M input plus 500K output workload, Qwen3.5-122B-A10B is estimated at $1.3 vs $1.35 for Kimi K2.5, saving $0.05 (3.7% lower).
Cost-first pickQwen3.5-122B-A10B
Context-first pickBoth models
Sample savings$0.053.7%
10x traffic gap$0.5
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $0.5. 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 Qwen3.5-122B-A10B, balanced workload favors Kimi K2.5, and output-heavy chatbot favors Kimi K2.5.
| Workload shape | Token mix | Better pick | Qwen3.5-122B-A10B | Kimi K2.5 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen3.5-122B-A10B | $2.34 | $2.95 |
| Balanced workload | 1M input + 1M output | Kimi K2.5 | $2.34 | $2.3 |
| Output-heavy chatbot | 1M input + 5M output | Kimi K2.5 | $10.66 | $9.9 |
Kimi K2.5 is $0.18 cheaper per 1M output tokens (8.7% lower; 1.09x difference).
Both models report the same context window at 262.14K tokens.
Qwen3.5-122B-A10B is $0.05 cheaper on the standard workload (3.7% 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
Qwen3.5-122B-A10B has the lower input price; Kimi K2.5 has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3.5-122B-A10B is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.3 for Qwen3.5-122B-A10B and $1.35 for Kimi K2.5.
Choose Qwen3.5-122B-A10B when you care most about lower input-token price.
Choose Kimi K2.5 when you care most about lower output-token price.
- On the standard 1M input plus 500K output workload, Qwen3.5-122B-A10B is estimated at $1.3 vs $1.35 for Kimi K2.5, saving $0.05 (3.7% lower).
- Qwen3.5-122B-A10B is $0.05 cheaper on the standard workload (3.7% lower).
- Qwen3.5-122B-A10B is $0.14 cheaper per 1M input tokens (35% lower; 1.54x difference).
- Kimi K2.5 is $0.18 cheaper per 1M output tokens (8.7% lower; 1.09x difference).
- Both models report the same context window at 262.14K tokens.
| Feature | Qwen3.5-122B-A10B (Qwen) | Kimi K2.5 (MoonshotAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.26 | $0.4 |
| Completion Price per 1M tokens | $2.08 | $1.9 |
| Sample Workload Cost 1M input + 500K output | $1.3 | $1.35 |
| Context Window | 262.14K | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen3.5-122B-A10B | On the standard 1M input plus 500K output workload, Qwen3.5-122B-A10B is estimated at $1.3 vs $1.35 for Kimi K2.5, saving $0.05 (3.7% lower). |
| High-volume input processing | Qwen3.5-122B-A10B | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Kimi K2.5 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | 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 Qwen3.5-122B-A10B when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3.5-122B-A10B when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3.5-122B-A10B when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen3.5-122B-A10B when lower sample workload cost matters most: $0.11.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Owl Alpha offers 1.05M context with $0 sample workload cost.
- Gemini 3.1 Flash Lite offers 1.05M context with $1 sample workload cost.
- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
- No popular competitor is currently available.
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
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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 modelsMoonshotAI catalog
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