Head-to-Head Model Comparison

Kimi K2 Thinking vs Kimi K2

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial

Partilhar

Troque e Compare Qualquer Modelo

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

Kimi K2 ThinkingProfile

Kimi K2Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Moonshot AI

Kimi K2 Thinking

Raciocínio de Pesos Abertos

O Kimi K2 Thinking da Moonshot AI é um modelo de IA projetado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, oferecendo janela de contexto de 262K, velocidade de 55 tokens/s, índice de inteligência de 85/100 e

Intelligence Index85 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

262.1K tokens

SWE-bench Verified:

50%

Moonshot AI

Kimi K2

IA Agêntica e Uso de Ferramentas

O Kimi K2 da Moonshot AI é um modelo de IA projetado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, oferecendo janela de contexto de 131K, velocidade de 62 tokens/s, índice de inteligência de 83/100 e tarif

Intelligence Index83 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

46%

Principais Diferenças em Resumo

Both models cost the same under this workload — choose on capability, not price.
Kimi K2 Thinking has a larger context window (262K vs 131K tokens).
Kimi K2 is faster at 62 tok/s vs 55 tok/s.
Kimi K2 Thinking leads on SWE-bench coding (50.0% vs 46.0%).

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

Feature	Kimi K2 Thinking	Kimi K2
Intelligence Index Composite reasoning & knowledge score (0-100)	85	83
Provider	Moonshot 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	262.1K tokens~393 A4 pages of text	131.1K tokens~197 A4 pages of text
Max Output Tokens Per single request	32K	16K
Throughput Speed Tokens generated per second	55 tok/s	62 tok/s
SWE-bench Verified Real-world software engineering	50%	46%
GPQA Diamond Graduate-level reasoning	70%	66.5%

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Kimi K2 Thinking

+4.0% SWE-bench lead

Cost

Tied

Identical monthly runtime cost

Speed

Kimi K2

+13% faster generation

Context

Kimi K2 Thinking

262.1K tokens window

Pontuações de Benchmarks Verificadas

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

Kimi K2 ThinkingKimi K2

SWE-bench Verified (Autonomous Coding)

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

50%vs46%

GPQA Diamond (Doctorate-Level Science & Math)

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

70%vs66.5%

MMLU-Pro (Multi-task Language Understanding)

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

82.5%vs80.5%

LMSYS Chatbot Arena Elo

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

1375ptsvs1360pts

AIME (Advanced Math Competition)

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

82.5%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

55 tok/s vs62 tok/s

Latência e Tempo de Resposta

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

Kimi K2 Thinking0.95s

Kimi K20.64s

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

Kimi K2 Thinking10.04s

Kimi K28.70s

Simulador Interativo de Custo de Tokens

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)

Kimi K2 Thinking 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

Kimi K2 Thinking · Strengths & Key Advantages

Janela de contexto de 262K com limite máximo de saída de 32K tokens (SWE-bench Verified 50% · GPQA Diamond 70%)
Taxa de transferência rápida de 55 tokens/segundo com latência inicial (TTFT) de 950 ms
Pesos abertos (1T total (32B MoE)) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama

Considerations & Trade-offs

Requer servidores GPU com memória VRAM adequada para execução local em precisão total
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Kimi K2 · Strengths & Key Advantages

Janela de contexto de 131K com limite máximo de saída de 16K tokens (SWE-bench Verified 46% · GPQA Diamond 66.5%)
Taxa de transferência rápida de 62 tokens/segundo com latência inicial (TTFT) de 640 ms
Pesos abertos (1T total (32B MoE)) para auto-hospedagem local ou em nuvem privada via vLLM, SGLang ou Ollama

Considerations & Trade-offs

Requer servidores GPU com memória VRAM adequada para execução local em precisão total
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Token Use & Task Economics

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

Metric	Kimi K2 Thinking	Kimi K2
Cost per Task Estimated USD to finish one task	$0.00	$0.00
Output Tokens / Task Tokens generated per task	28K	22K
Reasoning Tokens / Task Thinking tokens burned per task	16K	8K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	Kimi K2 Thinking	Kimi K2
Official API Model ID (SDK)	kimi-k2-thinking	kimi-k2
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date	2025-11	2025-07
Knowledge Cutoff	September 2025	May 2025
Architecture	Deliberate Reasoning Open Sparse Mixture-of-Experts	Trillion-Scale Sparse Mixture-of-Experts Transformer
Parameters	1T total (32B active 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) · 620 GB VRAM (4-bit Quantized) · 2150 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

Kimi K2 Thinking vs Kimi K2: Respostas Rápidas (FAQ)

Which is more intelligent, Kimi K2 Thinking or Kimi K2?

Kimi K2 Thinking is more intelligent. It scores 85 compared with 83 on the composite Intelligence Index.

Which model is faster?

Kimi K2 is faster, generating 62 tokens per second compared with 55 tokens per second.

Which model has lower latency?

Kimi K2 has lower latency, with a time to first token of 0.64s compared with 0.95s.

Which model has a larger context window?

Kimi K2 Thinking has a larger context window, supporting 262.1K tokens compared with 131.1K tokens.

Veredito

Tanto Kimi K2 Thinking (Indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas RAG corporativas e integração escalável via API.) quanto Kimi K2 (Indicado para fluxos de trabalho agênticos autônomos, chamada de ferramentas e automação, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Kimi K2 Thinking lidera em inteligência geral e programação, Kimi K2 oferece geração mais rápida e Kimi K2 Thinking apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Kimi K2 Thinking ou Kimi K2?+

Nas avaliações de inteligência e código, Kimi K2 Thinking leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Kimi K2 Thinking ou Kimi K2?+

O Kimi K2 Thinking custa $0.00 / $0.00 por 1M de tokens (entrada/saída) e o Kimi K2 custa $0.00 / $0.00. No custo combinado, Kimi K2 Thinking é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Kimi K2 Thinking suporta 262.1K tokens de contexto contra 131.1K tokens do Kimi K2, enquanto Kimi K2 entrega maior velocidade de geração.

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)

Kimi K2 Thinking vs Kimi K2

Troque e Compare Qualquer Modelo

Kimi K2 Thinking

Kimi K2

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Kimi K2 Thinking · Strengths & Key Advantages

Considerations & Trade-offs

Kimi K2 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Kimi K2 Thinking vs Kimi K2: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

Related reading