API cost decision in 10 seconds

Kimi K2.5 vs Qwen3 235B A22B Thinking 2507

Pick Qwen3 235B A22B Thinking 2507 when budget is the priority.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3 235B A22B Thinking 2507 when budget is the priority.

On the standard 1M input plus 500K output workload, Qwen3 235B A22B Thinking 2507 is estimated at $0.9 vs $1.35 for Kimi K2.5, saving $0.45 (33.6% lower).

Cost-first pickQwen3 235B A22B Thinking 2507
Context-first pickBoth models
Sample savings$0.4533.6%
10x traffic gap$4.53

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $4.53. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3 235B A22B Thinking 2507 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickKimi K2.5Qwen3 235B A22B Thinking 2507
Input-heavy / RAG5M input + 500K outputQwen3 235B A22B Thinking 2507$2.95$1.5
Balanced workload1M input + 1M outputQwen3 235B A22B Thinking 2507$2.3$1.64
Output-heavy chatbot1M input + 5M outputQwen3 235B A22B Thinking 2507$9.9$7.62
Cheaper input Qwen3 235B A22B Thinking 2507 $0.4 vs $0.1495 / 1M

Qwen3 235B A22B Thinking 2507 is $0.25 cheaper per 1M input tokens (62.6% lower; 2.68x difference).

Cheaper output Qwen3 235B A22B Thinking 2507 $1.9 vs $1.495 / 1M

Qwen3 235B A22B Thinking 2507 is $0.4 cheaper per 1M output tokens (21.3% lower; 1.27x difference).

Larger context Tie 262.14K vs 262.14K

Both models report the same context window at 262.14K tokens.

Sample workload Qwen3 235B A22B Thinking 2507 $1.35 vs $0.9

Qwen3 235B A22B Thinking 2507 is $0.45 cheaper on the standard workload (33.6% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Kimi K2.5 Calculating… Estimated API cost
Qwen3 235B A22B Thinking 2507 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 235B A22B Thinking 2507 has the lower input price; Qwen3 235B A22B Thinking 2507 has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3 235B A22B Thinking 2507 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 $0.9 for Qwen3 235B A22B Thinking 2507.

Best Fit

Choose Kimi K2.5 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Qwen3 235B A22B Thinking 2507 when you care most about lower input-token price, and lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, Qwen3 235B A22B Thinking 2507 is estimated at $0.9 vs $1.35 for Kimi K2.5, saving $0.45 (33.6% lower).
  • Qwen3 235B A22B Thinking 2507 is $0.45 cheaper on the standard workload (33.6% lower).
  • Qwen3 235B A22B Thinking 2507 is $0.25 cheaper per 1M input tokens (62.6% lower; 2.68x difference).
  • Qwen3 235B A22B Thinking 2507 is $0.4 cheaper per 1M output tokens (21.3% lower; 1.27x difference).
  • Both models report the same context window at 262.14K tokens.
Head-to-Head Specs
FeatureKimi K2.5
(MoonshotAI)
Qwen3 235B A22B Thinking 2507
(Qwen)
Input Price
prompt tokens per 1M
$0.4$0.1495
Completion Price
per 1M tokens
$1.9$1.495
Sample Workload Cost
1M input + 500K output
$1.35$0.9
Context Window262.14K262.14K
Release Date
Popularity#36#133

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionQwen3 235B A22B Thinking 2507On the standard 1M input plus 500K output workload, Qwen3 235B A22B Thinking 2507 is estimated at $0.9 vs $1.35 for Kimi K2.5, saving $0.45 (33.6% lower).
High-volume input processingQwen3 235B A22B Thinking 2507Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsQwen3 235B A22B Thinking 2507Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workTieA 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 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.
  • Qwen3 Coder 480B A35B (free) can replace Qwen3 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.
  • Qwen2.5 7B Instruct can replace Qwen3 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.09.
  • Qwen3.5-9B can replace Qwen3 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.11.
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Kimi K2.5

Kimi 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 Thinking 2507

Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...