Qwen3.5-27B is $0.4 cheaper per 1M input tokens (67.5% lower; 3.08x difference).
API cost decision in 10 seconds
Qwen3.5-27B vs Kimi K2 Thinking
Pick Qwen3.5-27B when budget is the priority.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Qwen3.5-27B when budget is the priority.
On the standard 1M input plus 500K output workload, Qwen3.5-27B is estimated at $0.98 vs $1.85 for Kimi K2 Thinking, saving $0.88 (47.3% lower).
Cost-first pickQwen3.5-27B
Context-first pickBoth models
Sample savings$0.8847.3%
10x traffic gap$8.75
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $8.75. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Qwen3.5-27B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3.5-27B | Kimi K2 Thinking |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen3.5-27B | $1.75 | $4.25 |
| Balanced workload | 1M input + 1M output | Qwen3.5-27B | $1.76 | $3.1 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3.5-27B | $8 | $13.1 |
Qwen3.5-27B is $0.94 cheaper per 1M output tokens (37.6% lower; 1.6x difference).
Both models report the same context window at 262.14K tokens.
Qwen3.5-27B is $0.88 cheaper on the standard workload (47.3% 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
Qwen3.5-27B has the lower input price; Qwen3.5-27B has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3.5-27B is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.98 for Qwen3.5-27B and $1.85 for Kimi K2 Thinking.
Choose Qwen3.5-27B when you care most about lower input-token price, and lower output-token price.
Choose Kimi K2 Thinking when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
- On the standard 1M input plus 500K output workload, Qwen3.5-27B is estimated at $0.98 vs $1.85 for Kimi K2 Thinking, saving $0.88 (47.3% lower).
- Qwen3.5-27B is $0.88 cheaper on the standard workload (47.3% lower).
- Qwen3.5-27B is $0.4 cheaper per 1M input tokens (67.5% lower; 3.08x difference).
- Qwen3.5-27B is $0.94 cheaper per 1M output tokens (37.6% lower; 1.6x difference).
- Both models report the same context window at 262.14K tokens.
| Feature | Qwen3.5-27B (Qwen) | Kimi K2 Thinking (MoonshotAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.195 | $0.6 |
| Completion Price per 1M tokens | $1.56 | $2.5 |
| Sample Workload Cost 1M input + 500K output | $0.98 | $1.85 |
| Context Window | 262.14K | 262.14K |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen3.5-27B | On the standard 1M input plus 500K output workload, Qwen3.5-27B is estimated at $0.98 vs $1.85 for Kimi K2 Thinking, saving $0.88 (47.3% lower). |
| High-volume input processing | Qwen3.5-27B | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen3.5-27B | 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 Qwen3.5-27B when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3.5-27B when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3.5-27B when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen3.5-27B when lower sample workload cost matters most: $0.11.
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- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
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Cheaper alternatives
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