Head-to-Head Model Comparison

KAT-Coder-Air V2.5 vs GPT-6.1 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
Bagikan
Related topics (4)
KwaipilotOpenAIlightweightflagship

Compare KAT-Coder-Air V2.5 by Kwaipilot against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Perbandingan Langsung (VS)

Ganti & Bandingkan Model Apa Saja

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Profile
Profile
Multi-Model Arena Stack:
5-Model Matrix Workbench

Live comparison: no in-depth editorial review has been published for this pair yet.

Popular Matchups:
Kwaipilot

KAT-Coder-Air V2.5

Model Penalaran Mendalam

KAT-Coder-Air V2.5 dari Kwaipilot adalah model AI canggih dengan jendela konteks 256K token serta harga API $0.1/1M token input dan $0.4/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

Intelligence Index77 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

256K tokens

SWE-bench Verified:

N/A

OpenAI

GPT-6.1 Sol

Model Penalaran Mendalam

GPT-6.1 Sol dari OpenAI adalah model AI canggih dengan jendela konteks 1M token serta harga API $2.0/1M token input dan $10.0/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.

Intelligence Index94 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.3%

Perbedaan Utama Sekilas

  • KAT-Coder-Air V2.5 is 23.1x cheaper for API usage (input + output tokens combined).
  • GPT-6.1 Sol has a larger context window (1M vs 256K tokens).
  • KAT-Coder-Air V2.5 is faster at 145 tok/s vs 120 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureKAT-Coder-Air V2.5GPT-6.1 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
7794
Provider
KwaipilotOpenAI
Input Price
Cost per million input tokens
$0.10 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$0.40 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.07 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
8K128K
Throughput Speed
Tokens generated per second
145 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
N/A82.3%
GPQA Diamond
Graduate-level reasoning
N/A80.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.01 / 1M$0.10 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
KAT-Coder-Air V2.5
23.1x cheaper monthly runtime
Speed
KAT-Coder-Air V2.5
+21% faster generation
Context
GPT-6.1 Sol
1M tokens window

Skor Benchmark Terverifikasi

Official evaluation metrics verified by independent third-party research labs.

KAT-Coder-Air V2.5GPT-6.1 Sol
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

N/Avs82.3%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

N/Avs80.8%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

74%vs89.9%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1285ptsvs1519pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs18.1%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs63.6%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs54.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs79.7%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

N/Avs93.5%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs91%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

145 tok/s vs120 tok/s

Latensi & Waktu Respons

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
KAT-Coder-Air V2.50.29s
GPT-6.1 Sol1.12s
Est. End-to-End Response (500 tokens)TTFT + generation time
KAT-Coder-Air V2.53.74s
GPT-6.1 Sol5.29s

Simulator Biaya Token Interaktif

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
KAT-Coder-Air V2.5 Monthly API Bill
$0.53 / month
$0.1/1M in · $0.4/1M out
GPT-6.1 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
KAT-Coder-Air V2.5 saves approximately $11.63 / month (96%) under this workload.23.1x Savings

KAT-Coder-Air V2.5 · Strengths & Key Advantages

  • Arsitektur Lightweight Code-Generation Transformer mutakhir dari Kwaipilot dengan dukungan konteks 256K token
  • Efisiensi biaya API yang kompetitif ($0.1/1M input, $0.4/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

GPT-6.1 Sol · Strengths & Key Advantages

  • Arsitektur Near-Astra unified reasoning model mutakhir dari OpenAI dengan dukungan konteks 1M token
  • Efisiensi biaya API yang kompetitif ($2.0/1M input, $10.0/1M output) dan respons cepat
  • Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
  • Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
  • Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricKAT-Coder-Air V2.5GPT-6.1 Sol
Cost per Task
Estimated USD to finish one task
$0.03$2.05
Output Tokens / Task
Tokens generated per task
14K62K
Reasoning Tokens / Task
Thinking tokens burned per task
1K36K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureKAT-Coder-Air V2.5GPT-6.1 Sol
Official API Model ID (SDK)kat-coder-air-v2-5gpt-6-1-sol
API ProtocolKwaipilot REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2026-072026-09
Knowledge CutoffApril 2026April 2026
ArchitectureLightweight Code-Generation TransformerNear-Astra unified reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.1/1M in) across full 256K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.01/1M tokensAutomatic prefix caching at $0.1/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-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 ClassificationKwaipilot Production Safety & Alignment VerifiedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext, vision
Output Modalitiestexttext

KAT-Coder-Air V2.5 vs GPT-6.1 Sol: Jawaban Cepat (FAQ)

Which is more intelligent, KAT-Coder-Air V2.5 or GPT-6.1 Sol?

GPT-6.1 Sol is more intelligent. It scores 94 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 120 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 $1.47 (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 1.12s.

Which model has a larger context window?

GPT-6.1 Sol has a larger context window, supporting 1M tokens compared with 256K tokens.

Kesimpulan

Choose KAT-Coder-Air V2.5 for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis kwaipilot, or choose GPT-6.1 Sol for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis openai.

Pertanyaan Umum (FAQ)

Which is cheaper: KAT-Coder-Air V2.5 or GPT-6.1 Sol?+

KAT-Coder-Air V2.5 costs $0.1/1M input and $0.4/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: KAT-Coder-Air V2.5 or GPT-6.1 Sol?+

KAT-Coder-Air V2.5 supports 256K tokens whereas GPT-6.1 Sol supports 1M tokens.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

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.

Sumber resmi: Kwaipilot & OpenAI Official Documentation