Claude Mythos 5.1 vs Kimi K3
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Claude Mythos 5.1 by Anthropic against Kimi K3 by Moonshot AI across real-world coding, reasoning, token economics, and latency.
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Claude Mythos 5.1
Modelo Principal de FronteiraO Claude Mythos 5.1 da Anthropic é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 1M, velocidade de 60 tokens/s, índice de inteligência de 88/1
$15.00 / 1M
$75.00 / 1M
1M tokens
84.2%
Kimi K3
Raciocínio de Pesos AbertosO Kimi K3 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 1.0M, velocidade de 58 tokens/s, índice de inteligência de 93/100 e tarifa de
$0.00 / 1M
$0.00 / 1M
1.05M tokens
74.5%
Principais Diferenças em Resumo
- Kimi K3 is 1.0x cheaper for API usage (input + output tokens combined).
- Kimi K3 has a larger context window (1M vs 1M tokens).
- Claude Mythos 5.1 is faster at 60 tok/s vs 58 tok/s.
- Claude Mythos 5.1 leads on SWE-bench coding (84.2% vs 74.5%).
| Feature | Claude Mythos 5.1 | Kimi K3 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 88 | 93 |
Provider | Anthropic | Moonshot AI |
Input Price Cost per million input tokens | $15.00 / 1M | $0.00 / 1M |
Output Price Cost per million output tokens | $75.00 / 1M | $0.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $11.55 / 1M | $0.00 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 1.05M tokens~1,573 A4 pages of text |
Max Output Tokens Per single request | 128K | 131K |
Throughput Speed Tokens generated per second | 60 tok/s | 58 tok/s |
SWE-bench Verified Real-world software engineering | 84.2% | 74.5% |
GPQA Diamond Graduate-level reasoning | 82% | 79% |
Cached Input Price Prompt caching discount per 1M tokens | $1.50 / 1M | $0.00 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkPontuações de Benchmarks Verificadas
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.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Tokens emitted per second during active generation streaming.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude Mythos 5.1 · Strengths & Key Advantages
- Janela de contexto de 1M com limite máximo de saída de 128K tokens (SWE-bench Verified 84.2% · GPQA Diamond 82%)
- Taxa de transferência rápida de 60 tokens/segundo com latência inicial (TTFT) de 1600 ms
- Economia de API competitiva ($15/$75 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
- Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
- Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos
Kimi K3 · Strengths & Key Advantages
- Janela de contexto de 1.0M com limite máximo de saída de 131K tokens (SWE-bench Verified 74.5% · GPQA Diamond 79%)
- Taxa de transferência rápida de 58 tokens/segundo com latência inicial (TTFT) de 720 ms
- Pesos abertos (2.8T total (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 | Claude Mythos 5.1 | Kimi K3 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $16.46 | $2.00 |
Output Tokens / Task Tokens generated per task | 72K | 35K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 18K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Mythos 5.1 | Kimi K3 |
|---|---|---|
| Official API Model ID (SDK) | claude-mythos-5-1-20260901 | kimi-k3 |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-09 | 2026-07 |
| Knowledge Cutoff | June 2026 | March 2026 |
| Architecture | Restricted Frontier Autonomous Cognitive System | Colossus-Scale Multimodal Sparse Mixture-of-Experts |
| Parameters | Confidential | 2.8T total (MoE) |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Free across full context window (only KV-cache VRAM scales) |
| Prompt Cache Policy & TTL | $1.5/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 1736 GB VRAM (4-bit Quantized) · 6020 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text, vision | text, vision |
| Output Modalities | text | text |
Claude Mythos 5.1 vs Kimi K3: Respostas Rápidas (FAQ)
Which is more intelligent, Claude Mythos 5.1 or Kimi K3?
Kimi K3 is more intelligent. It scores 93 compared with 88 on the composite Intelligence Index.
Which model is faster?
Claude Mythos 5.1 is faster, generating 60 tokens per second compared with 58 tokens per second.
Which model is cheaper to run?
Kimi K3 is cheaper at $0.00 per 1M tokens blended, compared with $11.55 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Kimi K3 has lower latency, with a time to first token of 0.72s compared with 1.60s.
Which model has a larger context window?
Kimi K3 has a larger context window, supporting 1.05M tokens compared with 1M tokens.
Veredito
Choose Claude Mythos 5.1 for indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas rag corporativas e integração escalável via api., or choose Kimi K3 for indicado para raciocínio em cadeia de pensamento com pesos abertos e alta eficiência, arquiteturas rag corporativas e integração escalável via api..
Perguntas Frequentes (FAQ)
Which is cheaper: Claude Mythos 5.1 or Kimi K3?+
Claude Mythos 5.1 costs $15/1M input and $75/1M output tokens, while Kimi K3 costs $0/1M input and $0/1M output tokens.
Which model has a larger context window: Claude Mythos 5.1 or Kimi K3?+
Claude Mythos 5.1 supports 1M tokens whereas Kimi K3 supports 1.0M tokens.
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.
Fontes oficiais: Anthropic & Moonshot AI Official Documentation