API cost decision in 10 seconds

Qwen3 VL 235B A22B Thinking vs Kimi K2 0711

Pick Qwen3 VL 235B A22B Thinking when budget is the priority.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-31T01:07:53Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3 VL 235B A22B Thinking when budget is the priority.

On the standard 1M input plus 500K output workload, Qwen3 VL 235B A22B Thinking is estimated at $1.56 vs $1.72 for Kimi K2 0711, saving $0.16 (9.3% lower).

Cost-first pickQwen3 VL 235B A22B Thinking

Context-first pickBoth models

Sample savings$0.169.3%

10x traffic gap$1.6

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $1.6. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Qwen3 VL 235B A22B Thinking, balanced workload favors Qwen3 VL 235B A22B Thinking, and output-heavy chatbot favors Kimi K2 0711.

Workload shape	Token mix	Better pick	Qwen3 VL 235B A22B Thinking	Kimi K2 0711
Input-heavy / RAG	5M input + 500K output	Qwen3 VL 235B A22B Thinking	$2.6	$4
Balanced workload	1M input + 1M output	Qwen3 VL 235B A22B Thinking	$2.86	$2.87
Output-heavy chatbot	1M input + 5M output	Kimi K2 0711	$13.26	$12.07

Cheaper input Qwen3 VL 235B A22B Thinking $0.26 vs $0.57 / 1M

Qwen3 VL 235B A22B Thinking is $0.31 cheaper per 1M input tokens (54.4% lower; 2.19x difference).

Cheaper output Kimi K2 0711 $2.6 vs $2.3 / 1M

Kimi K2 0711 is $0.3 cheaper per 1M output tokens (11.5% lower; 1.13x difference).

Larger context Tie 131.07K vs 131.07K

Both models report the same context window at 131.07K tokens.

Sample workload Qwen3 VL 235B A22B Thinking $1.56 vs $1.72

Qwen3 VL 235B A22B Thinking is $0.16 cheaper on the standard workload (9.3% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Qwen3 VL 235B A22B Thinking Calculating… Estimated API cost

Kimi K2 0711 Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

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

Verdict

Qwen3 VL 235B A22B Thinking has the lower input price; Kimi K2 0711 has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3 VL 235B A22B Thinking is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.56 for Qwen3 VL 235B A22B Thinking and $1.72 for Kimi K2 0711.

Best Fit

Choose Qwen3 VL 235B A22B Thinking when you care most about lower input-token price.

Choose Kimi K2 0711 when you care most about lower output-token price.

Decision Notes

On the standard 1M input plus 500K output workload, Qwen3 VL 235B A22B Thinking is estimated at $1.56 vs $1.72 for Kimi K2 0711, saving $0.16 (9.3% lower).
Qwen3 VL 235B A22B Thinking is $0.16 cheaper on the standard workload (9.3% lower).
Qwen3 VL 235B A22B Thinking is $0.31 cheaper per 1M input tokens (54.4% lower; 2.19x difference).
Kimi K2 0711 is $0.3 cheaper per 1M output tokens (11.5% lower; 1.13x difference).
Both models report the same context window at 131.07K tokens.

Head-to-Head Specs

Feature	Qwen3 VL 235B A22B Thinking (Qwen)	Kimi K2 0711 (MoonshotAI)
Input Price prompt tokens per 1M	$0.26	$0.57
Completion Price per 1M tokens	$2.6	$2.3
Sample Workload Cost 1M input + 500K output	$1.56	$1.72
Context Window	131.07K	131.07K
Release Date	2025-09-23	2025-07-11
Popularity	#103	#130

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Qwen3 VL 235B A22B Thinking	On the standard 1M input plus 500K output workload, Qwen3 VL 235B A22B Thinking is estimated at $1.56 vs $1.72 for Kimi K2 0711, saving $0.16 (9.3% lower).
High-volume input processing	Qwen3 VL 235B A22B Thinking	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Kimi K2 0711	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

Same-provider lower-cost swaps

Qwen3 Next 80B A3B Instruct (free) can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.
Qwen3 Coder 480B A35B (free) can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.
Qwen2.5 7B Instruct can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.09.
Qwen3.5-9B can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.11.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
MiMo-V2.5 offers 1.05M context with $0.28 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.

Popular competitors

Hy3 preview · Tencent · #1
MiMo-V2.5 · Xiaomi · #2
DeepSeek V4 Flash · DeepSeek · #3
Owl Alpha · OpenRouter · #4

Cheaper alternatives

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Larger context alternatives

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Provider catalogs

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Qwen catalog

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MoonshotAI catalog

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Qwen3 VL 235B A22B Thinking

Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math....

Kimi K2 0711

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...