Qwen3 VL 235B A22B Instruct is $0.2 cheaper per 1M input tokens (50% lower; 2x difference).
API cost decision in 10 seconds
Kimi K2.5 vs Qwen3 VL 235B A22B Instruct
Pick Qwen3 VL 235B A22B Instruct when budget is the priority.
Budget verdict
Pick Qwen3 VL 235B A22B Instruct when budget is the priority.
On the standard 1M input plus 500K output workload, Qwen3 VL 235B A22B Instruct is estimated at $0.64 vs $1.35 for Kimi K2.5, saving $0.71 (52.6% lower).
The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $7.1. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Qwen3 VL 235B A22B Instruct stays cheaper across input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Kimi K2.5 | Qwen3 VL 235B A22B Instruct |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Qwen3 VL 235B A22B Instruct | $2.95 | $1.44 |
| Balanced workload | 1M input + 1M output | Qwen3 VL 235B A22B Instruct | $2.3 | $1.08 |
| Output-heavy chatbot | 1M input + 5M output | Qwen3 VL 235B A22B Instruct | $9.9 | $4.6 |
Qwen3 VL 235B A22B Instruct is $1.02 cheaper per 1M output tokens (53.7% lower; 2.16x difference).
Both models report the same context window at 262.14K tokens.
Qwen3 VL 235B A22B Instruct is $0.71 cheaper on the standard workload (52.6% 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 VL 235B A22B Instruct has the lower input price; Qwen3 VL 235B A22B Instruct has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3 VL 235B A22B Instruct 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 $0.64 for Qwen3 VL 235B A22B Instruct.
Choose Kimi K2.5 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose Qwen3 VL 235B A22B Instruct when you care most about lower input-token price, and lower output-token price.
- On the standard 1M input plus 500K output workload, Qwen3 VL 235B A22B Instruct is estimated at $0.64 vs $1.35 for Kimi K2.5, saving $0.71 (52.6% lower).
- Qwen3 VL 235B A22B Instruct is $0.71 cheaper on the standard workload (52.6% lower).
- Qwen3 VL 235B A22B Instruct is $0.2 cheaper per 1M input tokens (50% lower; 2x difference).
- Qwen3 VL 235B A22B Instruct is $1.02 cheaper per 1M output tokens (53.7% lower; 2.16x difference).
- Both models report the same context window at 262.14K tokens.
| Feature | Kimi K2.5 (MoonshotAI) | Qwen3 VL 235B A22B Instruct (Qwen) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.4 | $0.2 |
| Completion Price per 1M tokens | $1.9 | $0.88 |
| Sample Workload Cost 1M input + 500K output | $1.35 | $0.64 |
| Context Window | 262.14K | 262.14K |
| Release Date | ||
| Popularity | #36 | #103 |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Qwen3 VL 235B A22B Instruct | On the standard 1M input plus 500K output workload, Qwen3 VL 235B A22B Instruct is estimated at $0.64 vs $1.35 for Kimi K2.5, saving $0.71 (52.6% lower). |
| High-volume input processing | Qwen3 VL 235B A22B Instruct | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Qwen3 VL 235B A22B Instruct | 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 VL 235B A22B Instruct when lower sample workload cost matters most: $0.
- Qwen3 Coder 480B A35B (free) can replace Qwen3 VL 235B A22B Instruct when lower sample workload cost matters most: $0.
- Qwen2.5 7B Instruct can replace Qwen3 VL 235B A22B Instruct when lower sample workload cost matters most: $0.09.
- Qwen3.5-9B can replace Qwen3 VL 235B A22B Instruct 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.
- 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
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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-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...