Head-to-Head Model Comparison

GLM-4.5-Air vs Kimi K2

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

Ganti & Bandingkan Model Apa Saja

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

GLM-4.5-AirProfile

Kimi K2Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Zhipu AI

GLM-4.5-Air

Model Ringan & Hemat Biaya

GLM-4.5-Air dari Zhipu AI adalah model AI yang dirancang untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, menghadirkan jendela konteks 131K, kecepatan 120 token/detik, indeks kecerdasan 74/100, serta akses g

Intelligence Index74 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

N/A

Moonshot AI

Kimi K2

Model Agen Otonom & Alat

Kimi K2 dari Moonshot AI adalah model AI yang dirancang untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, menghadirkan jendela konteks 131K, kecepatan 62 token/detik, indeks kecerdasan 83/100, ser

Intelligence Index83 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

46%

Perbedaan Utama Sekilas

Both models cost the same under this workload — choose on capability, not price.
GLM-4.5-Air is faster at 120 tok/s vs 62 tok/s.

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	GLM-4.5-Air	Kimi K2
Intelligence Index Composite reasoning & knowledge score (0-100)	74	83
Provider	Zhipu AI	Moonshot AI
Input Price Cost per million input tokens	$0.00 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$0.00 / 1M
Context Window Maximum input + output tokens	131.1K tokens~197 A4 pages of text	131.1K tokens~197 A4 pages of text
Max Output Tokens Per single request	8K	16K
Throughput Speed Tokens generated per second	120 tok/s	62 tok/s
SWE-bench Verified Real-world software engineering	N/A	46%
GPQA Diamond Graduate-level reasoning	52%	66.5%

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Tied

Identical monthly runtime cost

Speed

GLM-4.5-Air

+94% faster generation

Context

Tied

131.1K tokens window

Skor Benchmark Terverifikasi

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

GLM-4.5-AirKimi K2

SWE-bench Verified (Autonomous Coding)

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

N/Avs46%

GPQA Diamond (Doctorate-Level Science & Math)

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

52%vs66.5%

MMLU-Pro (Multi-task Language Understanding)

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

70%vs80.5%

LMSYS Chatbot Arena Elo

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

1255ptsvs1360pts

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs62 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

GLM-4.5-Air0.36s

Kimi K20.64s

Est. End-to-End Response (500 tokens)TTFT + generation time

GLM-4.5-Air4.53s

Kimi K28.70s

Simulator Biaya Token Interaktif

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

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

GLM-4.5-Air Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Kimi K2 Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

These models cost the same under this workload — no savings either way.Break-even

GLM-4.5-Air · Strengths & Key Advantages

Jendela konteks 131K dengan kapasitas output maksimum hingga 8K token (GPQA Diamond 52% · MMLU-Pro 70%)
Kecepatan generasi tinggi 120 token/detik dengan latensi token pertama (TTFT) hanya 360 ms
Bobot terbuka (30B MoE) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama

Considerations & Trade-offs

Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Kimi K2 · Strengths & Key Advantages

Jendela konteks 131K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 46% · GPQA Diamond 66.5%)
Kecepatan generasi tinggi 62 token/detik dengan latensi token pertama (TTFT) hanya 640 ms
Bobot terbuka (1T total (32B MoE)) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama

Considerations & Trade-offs

Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Token Use & Task Economics

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

Metric	GLM-4.5-Air	Kimi K2
Cost per Task Estimated USD to finish one task	$0.00	$0.00
Output Tokens / Task Tokens generated per task	12K	22K
Reasoning Tokens / Task Thinking tokens burned per task	2K	8K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	GLM-4.5-Air	Kimi K2
Official API Model ID (SDK)	glm-4-5-air	kimi-k2
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-07	2025-07
Knowledge Cutoff	May 2025	May 2025
Architecture	Lightweight Sparse Mixture-of-Experts Transformer	Trillion-Scale Sparse Mixture-of-Experts Transformer
Parameters	30B MoE	1T total (32B active MoE)
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)	Free across full context window (only KV-cache VRAM scales)	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Automatic prefix KV-caching in vLLM / SGLang (0 cost)
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	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)	Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token Billing	Text BPE (~4 chars/token)	Text BPE (~4 chars/token)
Quantization & Min GPU VRAM	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 19 GB VRAM (4-bit Quantized) · 65 GB VRAM (Native BF16)	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 620 GB VRAM (4-bit Quantized) · 2150 GB VRAM (Native BF16)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalities	text	text
Output Modalities	text	text

GLM-4.5-Air vs Kimi K2: Jawaban Cepat (FAQ)

Which is more intelligent, GLM-4.5-Air or Kimi K2?

Kimi K2 is more intelligent. It scores 83 compared with 74 on the composite Intelligence Index.

Which model is faster?

GLM-4.5-Air is faster, generating 120 tokens per second compared with 62 tokens per second.

Which model has lower latency?

GLM-4.5-Air has lower latency, with a time to first token of 0.36s compared with 0.64s.

Kesimpulan

Baik GLM-4.5-Air (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Kimi K2 (Sangat cocok untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Kimi K2 unggul dalam penalaran dan pemrograman, GLM-4.5-Air memberikan kecepatan generasi token lebih tinggi, dan GLM-4.5-Air lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, GLM-4.5-Air atau Kimi K2?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Kimi K2 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API GLM-4.5-Air vs Kimi K2?+

GLM-4.5-Air mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan Kimi K2 sebesar $0.00 / $0.00. Secara keseluruhan, GLM-4.5-Air lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

GLM-4.5-Air mendukung konteks 131.1K token dibandingkan 131.1K token pada Kimi K2, sementara GLM-4.5-Air unggul dalam kecepatan output token per detik.

AI Terminology & Guide

Explore Glossary →

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

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

GLM-4.5-Air vs Kimi K2

Ganti & Bandingkan Model Apa Saja

GLM-4.5-Air

Kimi K2

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

GLM-4.5-Air · Strengths & Key Advantages

Considerations & Trade-offs

Kimi K2 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

GLM-4.5-Air vs Kimi K2: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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