Kimi K2 0905 is $1.9 cheaper per 1M input tokens (76% lower; 4.17x difference).
API cost decision in 10 seconds
NewQwen3.7 Max vs Kimi K2 0905
Pick Kimi K2 0905 for lower cost; pick Qwen3.7 Max 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 Kimi K2 0905 for lower cost; pick Qwen3.7 Max only if the larger context window matters more.
On the standard 1M input plus 500K output workload, Kimi K2 0905 is estimated at $1.85 vs $6.25 for Qwen3.7 Max, saving $4.4 (70.4% lower).
Cost-first pickKimi K2 0905
Context-first pickQwen3.7 Max
Sample savings$4.470.4%
10x traffic gap$44
Qwen3.7 Max has more context, but Kimi K2 0905 saves $4.4 on the standard workload. At 10x that traffic, the same price gap is about $44. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Kimi K2 0905 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Qwen3.7 Max | Kimi K2 0905 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Kimi K2 0905 | $16.25 | $4.25 |
| Balanced workload | 1M input + 1M output | Kimi K2 0905 | $10 | $3.1 |
| Output-heavy chatbot | 1M input + 5M output | Kimi K2 0905 | $40 | $13.1 |
Kimi K2 0905 is $5 cheaper per 1M output tokens (66.7% lower; 3x difference).
Qwen3.7 Max has 737.86K more context (3.81x larger).
Kimi K2 0905 is $4.4 cheaper on the standard workload (70.4% 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 0905 has the lower input price; Kimi K2 0905 has the lower output price; Qwen3.7 Max offers the larger context window. For the 1M input plus 500K output sample, Kimi K2 0905 is cheaper for the standard workload.
For a 1M input token plus 500K output token workload, the estimated API cost is $6.25 for Qwen3.7 Max and $1.85 for Kimi K2 0905.
Choose Qwen3.7 Max when you care most about larger context window.
Choose Kimi K2 0905 when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Kimi K2 0905 is estimated at $1.85 vs $6.25 for Qwen3.7 Max, saving $4.4 (70.4% lower).
- Kimi K2 0905 is $4.4 cheaper on the standard workload (70.4% lower).
- Kimi K2 0905 is $1.9 cheaper per 1M input tokens (76% lower; 4.17x difference).
- Kimi K2 0905 is $5 cheaper per 1M output tokens (66.7% lower; 3x difference).
- Qwen3.7 Max has 737.86K more context (3.81x larger).
| Feature | NewQwen3.7 Max (Qwen) | Kimi K2 0905 (MoonshotAI) |
|---|---|---|
| Input Price prompt tokens per 1M | $2.5 | $0.6 |
| Completion Price per 1M tokens | $7.5 | $2.5 |
| Sample Workload Cost 1M input + 500K output | $6.25 | $1.85 |
| Context Window | 1M | 262.14K |
| Release Date | ||
| Popularity | #48 | #70 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Kimi K2 0905 | On the standard 1M input plus 500K output workload, Kimi K2 0905 is estimated at $1.85 vs $6.25 for Qwen3.7 Max, saving $4.4 (70.4% lower). |
| High-volume input processing | Kimi K2 0905 | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Kimi K2 0905 | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Qwen3.7 Max | 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 Qwen3.7 Max when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3.7 Max when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3.7 Max when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen3.7 Max when lower sample workload cost matters most: $0.11.
- Llama 4 Scout offers 10M context with $0.23 sample workload cost.
- Grok 4.20 offers 2M context with $2.5 sample workload cost.
- Grok 4.20 Multi-Agent offers 2M context with $5 sample workload cost.
- Owl Alpha offers 1.05M context with $0 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
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 modelsMoonshotAI catalog
Check other MoonshotAI models with comparable pricing, context, or release timing.
Open MoonshotAI modelsQwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks,...
Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32...