API cost decision in 10 seconds

KAT-Coder-Pro V2 vs Qwen3.5 397B A17B

Pick KAT-Coder-Pro V2 for lower cost; pick Qwen3.5 397B A17B only if the larger context window matters more.

Pricing data updated:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick KAT-Coder-Pro V2 for lower cost; pick Qwen3.5 397B A17B only if the larger context window matters more.

On the standard 1M input plus 500K output workload, KAT-Coder-Pro V2 is estimated at $0.9 vs $1.56 for Qwen3.5 397B A17B, saving $0.66 (42.3% lower).

Cost-first pickKAT-Coder-Pro V2
Context-first pickQwen3.5 397B A17B
Sample savings$0.6642.3%
10x traffic gap$6.6

Qwen3.5 397B A17B has more context, but KAT-Coder-Pro V2 saves $0.66 on the standard workload. At 10x that traffic, the same price gap is about $6.6. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

KAT-Coder-Pro V2 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickKAT-Coder-Pro V2Qwen3.5 397B A17B
Input-heavy / RAG5M input + 500K outputKAT-Coder-Pro V2$2.1$3.12
Balanced workload1M input + 1M outputKAT-Coder-Pro V2$1.5$2.73
Output-heavy chatbot1M input + 5M outputKAT-Coder-Pro V2$6.3$12.09
Cheaper input KAT-Coder-Pro V2 $0.3 vs $0.39 / 1M

KAT-Coder-Pro V2 is $0.09 cheaper per 1M input tokens (23.1% lower; 1.3x difference).

Cheaper output KAT-Coder-Pro V2 $1.2 vs $2.34 / 1M

KAT-Coder-Pro V2 is $1.14 cheaper per 1M output tokens (48.7% lower; 1.95x difference).

Larger context Qwen3.5 397B A17B 256K vs 262.14K

Qwen3.5 397B A17B has 6.14K more context (1.02x larger).

Sample workload KAT-Coder-Pro V2 $0.9 vs $1.56

KAT-Coder-Pro V2 is $0.66 cheaper on the standard workload (42.3% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
KAT-Coder-Pro V2 Calculating… Estimated API cost
Qwen3.5 397B A17B 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

KAT-Coder-Pro V2 has the lower input price; KAT-Coder-Pro V2 has the lower output price; Qwen3.5 397B A17B offers the larger context window. For the 1M input plus 500K output sample, KAT-Coder-Pro V2 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.9 for KAT-Coder-Pro V2 and $1.56 for Qwen3.5 397B A17B.

Best Fit

Choose KAT-Coder-Pro V2 when you care most about lower input-token price, and lower output-token price.

Choose Qwen3.5 397B A17B when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, KAT-Coder-Pro V2 is estimated at $0.9 vs $1.56 for Qwen3.5 397B A17B, saving $0.66 (42.3% lower).
  • KAT-Coder-Pro V2 is $0.66 cheaper on the standard workload (42.3% lower).
  • KAT-Coder-Pro V2 is $0.09 cheaper per 1M input tokens (23.1% lower; 1.3x difference).
  • KAT-Coder-Pro V2 is $1.14 cheaper per 1M output tokens (48.7% lower; 1.95x difference).
  • Qwen3.5 397B A17B has 6.14K more context (1.02x larger).
Head-to-Head Specs
FeatureKAT-Coder-Pro V2
(Kwaipilot)
Qwen3.5 397B A17B
(Qwen)
Input Price
prompt tokens per 1M
$0.3$0.39
Completion Price
per 1M tokens
$1.2$2.34
Sample Workload Cost
1M input + 500K output
$0.9$1.56
Context Window256K262.14K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionKAT-Coder-Pro V2On the standard 1M input plus 500K output workload, KAT-Coder-Pro V2 is estimated at $0.9 vs $1.56 for Qwen3.5 397B A17B, saving $0.66 (42.3% lower).
High-volume input processingKAT-Coder-Pro V2Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsKAT-Coder-Pro V2Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3.5 397B A17BA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

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Larger context alternatives

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Provider catalogs

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Kwaipilot catalog

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Qwen catalog

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