KAT-Coder-Pro V2.5 vs KAT-Coder-Air V2.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
KAT-Coder-Pro V2.5 by Kwaipilot and KAT-Coder-Air V2.5 by Kwaipilot represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, KAT-Coder-Air V2.5 holds a notable pricing advantage for token ingestion. On output generation, KAT-Coder-Air V2.5 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 256K tokens. In latency-sensitive production environments, KAT-Coder-Air V2.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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KAT-Coder-Pro V2.5
深度推理模型Kwaipilot 推出的 KAT-Coder-Pro V2.5 人工智能模型，具备 256K 上下文窗口，输入价格为 $0.5/百万 Token，输出价格为 $2/百万 Token，专为高质量生产环境、推理与自动化工作流打造。
$0.50 / 1M
$2.00 / 1M
256K tokens
58%
KAT-Coder-Air V2.5
深度推理模型Kwaipilot 推出的 KAT-Coder-Air V2.5 人工智能模型，具备 256K 上下文窗口，输入价格为 $0.1/百万 Token，输出价格为 $0.4/百万 Token，专为高质量生产环境、推理与自动化工作流打造。
$0.10 / 1M
$0.40 / 1M
256K tokens
N/A
核心差异一览
- KAT-Coder-Air V2.5 is 5.0x cheaper for API usage (input + output tokens combined).
- KAT-Coder-Air V2.5 is faster at 145 tok/s vs 80 tok/s.
| Feature | KAT-Coder-Pro V2.5 | KAT-Coder-Air V2.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 85 | 77 |
Provider | Kwaipilot | Kwaipilot |
Input Price Cost per million input tokens | $0.50 / 1M | $0.10 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $0.40 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.34 / 1M | $0.07 / 1M |
Context Window Maximum input + output tokens | 256K tokens~384 A4 pages of text | 256K tokens~384 A4 pages of text |
Max Output Tokens Per single request | 16K | 8K |
Throughput Speed Tokens generated per second | 80 tok/s | 145 tok/s |
SWE-bench Verified Real-world software engineering | 58% | N/A |
GPQA Diamond Graduate-level reasoning | 67% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.05 / 1M | $0.01 / 1M |
各项指标谁更胜一筹？
At-a-glance decision frameworkEvaluations ongoing
权威基准测试得分对比
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Tokens emitted per second during active generation streaming.
延迟与响应速度
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
实时 Token 成本模拟器
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
KAT-Coder-Pro V2.5 · Strengths & Key Advantages
- 由 Kwaipilot 研发的高精度 Agentic Code-Specialized Transformer 架构，支持 256K 上下文窗口
- 极具竞争力的 API 定价（输入 $0.5/1M，输出 $2/1M），支持高速推理与工具调用
- 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
- 超长上下文请求需要规划 Token 成本与并发配额
- 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果
KAT-Coder-Air V2.5 · Strengths & Key Advantages
- 由 Kwaipilot 研发的高精度 Lightweight Code-Generation Transformer 架构，支持 256K 上下文窗口
- 极具竞争力的 API 定价（输入 $0.1/1M，输出 $0.4/1M），支持高速推理与工具调用
- 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
- 超长上下文请求需要规划 Token 成本与并发配额
- 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | KAT-Coder-Pro V2.5 | KAT-Coder-Air V2.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.18 | $0.03 |
Output Tokens / Task Tokens generated per task | 22K | 14K |
Reasoning Tokens / Task Thinking tokens burned per task | 7K | 1K |
技术规格参数
Architecture, release timeline, capabilities, and modalities.
| Feature | KAT-Coder-Pro V2.5 | KAT-Coder-Air V2.5 |
|---|---|---|
| Official API Model ID (SDK) | kat-coder-pro-v2-5 | kat-coder-air-v2-5 |
| API Protocol | Kwaipilot REST API (OpenAI-Compatible) | Kwaipilot REST API (OpenAI-Compatible) |
| Release Date | 2026-07 | 2026-07 |
| Knowledge Cutoff | April 2026 | April 2026 |
| Architecture | Agentic Code-Specialized Transformer | Lightweight Code-Generation Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.5/1M in) across full 256K window | Flat rate ($0.1/1M in) across full 256K window |
| Prompt Cache Policy & TTL | Cached input at $0.05/1M tokens | Cached input at $0.01/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Kwaipilot Production Safety & Alignment Verified | Kwaipilot Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text |
| Output Modalities | text | text |
KAT-Coder-Pro V2.5 vs KAT-Coder-Air V2.5: 常见问题解答 (FAQ)
Which is more intelligent, KAT-Coder-Pro V2.5 or KAT-Coder-Air V2.5?
KAT-Coder-Pro V2.5 is more intelligent. It scores 85 compared with 77 on the composite Intelligence Index.
Which model is faster?
KAT-Coder-Air V2.5 is faster, generating 145 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
KAT-Coder-Air V2.5 is cheaper at $0.07 per 1M tokens blended, compared with $0.34 (7:2:1 cache:input:output ratio).
Which model has lower latency?
KAT-Coder-Air V2.5 has lower latency, with a time to first token of 0.29s compared with 0.51s.
综合结论
Verdict & Model Selection Recommendation: Choose KAT-Coder-Pro V2.5 if your priority is Autonomous coding agents, CI/CD automated repair, and large-scale code modernization. Its performance in demanding tasks justifies its operational token cost. Choose KAT-Coder-Air V2.5 if your workflow prioritizes IDE code completions, quick function generation, and automated documentation comments. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
常见问题 (FAQ)
How does KAT-Coder-Pro V2.5 compare to KAT-Coder-Air V2.5 in API token pricing and cost per token?+
KAT-Coder-Pro V2.5 costs $0.50 per 1M input tokens and $2.00 per 1M output tokens, whereas KAT-Coder-Air V2.5 costs $0.10 input and $0.40 output. Overall, KAT-Coder-Air V2.5 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: KAT-Coder-Pro V2.5 or KAT-Coder-Air V2.5?+
Both KAT-Coder-Pro V2.5 and KAT-Coder-Air V2.5 offer an identical context window of 256K tokens (~192k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: KAT-Coder-Pro V2.5 or KAT-Coder-Air V2.5?+
KAT-Coder-Pro V2.5 scores 58% on SWE-bench Verified, while KAT-Coder-Air V2.5 scores competitively for software generation. For complex autonomous debugging and agentic engineering, KAT-Coder-Pro V2.5 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between KAT-Coder-Pro V2.5 and KAT-Coder-Air V2.5?+
KAT-Coder-Pro V2.5 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, KAT-Coder-Air V2.5 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between KAT-Coder-Pro V2.5 and KAT-Coder-Air V2.5?+
KAT-Coder-Pro V2.5 generates approximately 80 tokens per second, while KAT-Coder-Air V2.5 delivers 145 tokens per second. In latency-sensitive production environments, KAT-Coder-Air V2.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining KAT-Coder-Pro V2.5 and KAT-Coder-Air V2.5 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to KAT-Coder-Air V2.5 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to KAT-Coder-Pro V2.5. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
数据来源: GetInfoUs Independent AI Benchmarks & Official API Specs