Qwen3 235B A22B is $0.11 cheaper per 1M input tokens (20.2% lower; 1.25x difference).
API cost decision in 10 seconds
Qwen3 235B A22B vs Kimi K2 0711
Pick Qwen3 235B A22B 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 235B A22B when budget is the priority.
On the standard 1M input plus 500K output workload, Qwen3 235B A22B is estimated at $1.36 vs $1.72 for Kimi K2 0711, saving $0.35 (20.6% lower).
Cost-first pickQwen3 235B A22B
Context-first pickBoth models
Sample savings$0.3520.6%
10x traffic gap$3.55
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $3.55. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Qwen3 235B A22B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3 235B A22B | Kimi K2 0711 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen3 235B A22B | $3.19 | $4 |
| Balanced workload | 1M input + 1M output | Qwen3 235B A22B | $2.27 | $2.87 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3 235B A22B | $9.55 | $12.07 |
Qwen3 235B A22B is $0.48 cheaper per 1M output tokens (20.9% lower; 1.26x difference).
Both models report the same context window at 131.07K tokens.
Qwen3 235B A22B is $0.35 cheaper on the standard workload (20.6% 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 235B A22B has the lower input price; Qwen3 235B A22B has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3 235B A22B is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $1.36 for Qwen3 235B A22B and $1.72 for Kimi K2 0711.
Choose Qwen3 235B A22B when you care most about lower input-token price, and lower output-token price.
Choose Kimi K2 0711 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 235B A22B is estimated at $1.36 vs $1.72 for Kimi K2 0711, saving $0.35 (20.6% lower).
- Qwen3 235B A22B is $0.35 cheaper on the standard workload (20.6% lower).
- Qwen3 235B A22B is $0.11 cheaper per 1M input tokens (20.2% lower; 1.25x difference).
- Qwen3 235B A22B is $0.48 cheaper per 1M output tokens (20.9% lower; 1.26x difference).
- Both models report the same context window at 131.07K tokens.
| Feature | Qwen3 235B A22B (Qwen) | Kimi K2 0711 (MoonshotAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.455 | $0.57 |
| Completion Price per 1M tokens | $1.82 | $2.3 |
| Sample Workload Cost 1M input + 500K output | $1.36 | $1.72 |
| Context Window | 131.07K | 131.07K |
| Release Date | ||
| Popularity | #131 | #140 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen3 235B A22B | On the standard 1M input plus 500K output workload, Qwen3 235B A22B is estimated at $1.36 vs $1.72 for Kimi K2 0711, saving $0.35 (20.6% lower). |
| High-volume input processing | Qwen3 235B A22B | 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 | 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 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 MoonshotAI modelsQwen3-235B-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...
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...