Kimi K2.5 is $0.05 cheaper per 1M input tokens (12.1% lower; 1.14x difference).
API cost decision in 10 seconds
Kimi K2.5 vs Qwen3 235B A22B
Pick Kimi K2.5 when budget and context both matter.
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Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick Kimi K2.5 when budget and context both matter.
On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.36 for Qwen3 235B A22B, saving $0.01 (1.1% lower).
Cost-first pickKimi K2.5
Context-first pickKimi K2.5
Sample savings$0.011.1%
10x traffic gap$0.15
Kimi K2.5 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $0.15. 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 Kimi K2.5, balanced workload favors Qwen3 235B A22B, and output-heavy chatbot favors Qwen3 235B A22B.
| Workload shape | Token mix | Better pick | Kimi K2.5 | Qwen3 235B A22B |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Kimi K2.5 | $2.95 | $3.19 |
| Balanced workload | 1M input + 1M output | Qwen3 235B A22B | $2.3 | $2.27 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3 235B A22B | $9.9 | $9.55 |
Qwen3 235B A22B is $0.08 cheaper per 1M output tokens (4.2% lower; 1.04x difference).
Kimi K2.5 has 131.07K more context (2x larger).
Kimi K2.5 is $0.01 cheaper on the standard workload (1.1% 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
Kimi K2.5 has the lower input price; Qwen3 235B A22B has the lower output price; Kimi K2.5 offers the larger context window. For the 1M input plus 500K output sample, Kimi K2.5 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.35 for Kimi K2.5 and $1.36 for Qwen3 235B A22B.
Choose Kimi K2.5 when you care most about lower input-token price, and larger context window.
Choose Qwen3 235B A22B when you care most about lower output-token price.
- On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.36 for Qwen3 235B A22B, saving $0.01 (1.1% lower).
- Kimi K2.5 is $0.01 cheaper on the standard workload (1.1% lower).
- Kimi K2.5 is $0.05 cheaper per 1M input tokens (12.1% lower; 1.14x difference).
- Qwen3 235B A22B is $0.08 cheaper per 1M output tokens (4.2% lower; 1.04x difference).
- Kimi K2.5 has 131.07K more context (2x larger).
| Feature | Kimi K2.5 (MoonshotAI) | Qwen3 235B A22B (Qwen) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.4 | $0.455 |
| Completion Price per 1M tokens | $1.9 | $1.82 |
| Sample Workload Cost 1M input + 500K output | $1.35 | $1.36 |
| Context Window | 262.14K | 131.07K |
| Release Date | ||
| Popularity | #36 | #131 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Kimi K2.5 | On the standard 1M input plus 500K output workload, Kimi K2.5 is estimated at $1.35 vs $1.36 for Qwen3 235B A22B, saving $0.01 (1.1% lower). |
| High-volume input processing | Kimi K2.5 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen3 235B A22B | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Kimi K2.5 | 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 235B A22B when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3 235B A22B when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3 235B A22B when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen3 235B A22B when lower sample workload cost matters most: $0.11.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
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- DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
- DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.
- DeepSeek V4 Flash · DeepSeek · #1
- Hy3 preview · Tencent · #2
- Claude Opus 4.7 · Anthropic · #3
- Claude Sonnet 4.6 · Anthropic · #4
Cheaper alternatives
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Open Qwen modelsKimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed...
Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...