Qwen3.5 397B A17B vs KAT-Coder-Pro V2
Head-to-head specifications
| Metric | Qwen3.5 397B A17B | KAT-Coder-Pro V2 | Difference |
|---|---|---|---|
| Intelligence Index | 33.0 | 34.0 | -2.9% |
| Coding Index | 48.2 | 59.5 | -19.0% |
| Agentic Index | 19.8 | 15.5 | — |
| Context window | 512K tokens | 262K tokens | — |
| Blended price ($/1M tokens) | $0.65 | $0.22 | +195.5% |
| Access | Open weights | Open weights | — |
- KAT-Coder-Pro V2 leads overall capability (Intelligence Index 34.0 vs 33.0).
- KAT-Coder-Pro V2 is the cheaper model to run at $0.22/1M blended tokens — about 3.0× cheaper.
- Qwen3.5 397B A17B offers the larger context window (512K tokens), useful for long documents and codebases.
Verdict: Qwen3.5 397B A17B or KAT-Coder-Pro V2?
Qwen3.5 397B A17B advantages
- Agentic task performance (+22%)
- Context window (+49%)
KAT-Coder-Pro V2 advantages
- Coding ability (+19%)
- Affordability (+66%)
Which should you choose?
- Choose the Qwen3.5 397B A17B if you build agents or multi-step tool-use workflows.
- Choose the KAT-Coder-Pro V2 if coding and software development are your main workload.
- Choose the Qwen3.5 397B A17B if you work with long documents or large codebases.
Value for money
KAT-Coder-Pro V2 offers more intelligence per dollar (3.0× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Qwen3.5 397B A17B vs KAT-Coder-Pro V2: which should you choose?
Qwen3.5 397B A17B — Alibaba text model with an Intelligence Index of 33, a 512K-token context window and a blended price of $0.65/1M tokens (open weights).
KAT-Coder-Pro V2 — KAT text model with an Intelligence Index of 34, a 262K-token context window and a blended price of $0.22/1M tokens (open weights).
Qwen3.5 397B A17B vs KAT-Coder-Pro V2: KAT-Coder-Pro V2 scores higher on the Intelligence Index. KAT-Coder-Pro V2 leads overall capability (Intelligence Index 34.0 vs 33.0). KAT-Coder-Pro V2 is the cheaper model to run at $0.22/1M blended tokens — about 3.0× cheaper.
Capability: intelligence, coding and agentic work
On the composite Intelligence Index the KAT-Coder-Pro V2 scores 34.0 versus 33.0. For software development, the Coding Index puts KAT-Coder-Pro V2 ahead (59.5 vs 48.2). On agentic, multi-step tool-use tasks, Qwen3.5 397B A17B measures stronger. Composite indices summarize many evaluations, but always test on your own workload before committing.
Context window and speed
The Qwen3.5 397B A17B accepts up to 512K tokens per request, which sets how much documentation, transcript or code it can reason over at once.
Pricing and access
At blended per-token rates, KAT-Coder-Pro V2 is the cheaper model to run ($0.22 vs $0.65 per 1M tokens). Qwen3.5 397B A17B is open weights and KAT-Coder-Pro V2 is open weights. Open-weight models can be self-hosted, trading per-call cost for infrastructure you manage; for production also weigh rate limits, throughput and data-residency requirements.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Qwen3.5 397B A17B better than the KAT-Coder-Pro V2?
These two are closely matched — the right pick comes down to which specific strengths you value and the price you actually pay. KAT-Coder-Pro V2 leads overall capability (Intelligence Index 34.0 vs 33.0).
What is the main difference between the Qwen3.5 397B A17B and the KAT-Coder-Pro V2?
KAT-Coder-Pro V2 leads overall capability (Intelligence Index 34.0 vs 33.0). KAT-Coder-Pro V2 is the cheaper model to run at $0.22/1M blended tokens — about 3.0× cheaper.
Which is better value?
KAT-Coder-Pro V2 offers more intelligence per dollar (3.0× the Intelligence-Index-per-cost of the alternative), making it the stronger value for high-volume use. It is also open-weight, so self-hosting can reduce costs further at scale.
Which should I choose?
Choose the Qwen3.5 397B A17B if you build agents or multi-step tool-use workflows. Choose the KAT-Coder-Pro V2 if coding and software development are your main workload.
Methodology
Large language models are compared on independent leaderboard metrics: an Intelligence Index (a composite of reasoning and knowledge evaluations), Coding and Agentic indices where measured, community arena Elo, maximum context window, a blended API price per million tokens (weighted across cache-hit, input and output rates), and measured output speed in tokens per second. Where a model ships multiple reasoning-effort variants, we report its strongest variant. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit — and this space moves quickly, so figures reflect the leaderboard snapshot on the page date.