Claude Mythos 5.1 vs Llama 5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Claude Mythos 5.1 by Anthropic against Llama 5 by Meta across real-world coding, reasoning, token economics, and latency.
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Claude Mythos 5.1
Model Penalaran MendalamClaude Mythos 5.1 dari Anthropic adalah model AI canggih dengan jendela konteks 1M token serta harga API $15/1M token input dan $75/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$15.00 / 1M
$75.00 / 1M
1M tokens
84.2%
Llama 5
Model Open-WeightsLlama 5 dari Meta adalah model AI canggih dengan jendela konteks 5M token serta harga API $0/1M token input dan $0/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$0.00 / 1M
$0.00 / 1M
5M tokens
74%
Perbedaan Utama Sekilas
- Llama 5 is 1.0x cheaper for API usage (input + output tokens combined).
- Llama 5 has a larger context window (5M vs 1M tokens).
- Llama 5 is faster at 65 tok/s vs 60 tok/s.
- Claude Mythos 5.1 leads on SWE-bench coding (84.2% vs 74.0%).
| Feature | Claude Mythos 5.1 | Llama 5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 88 | 94 |
Provider | Anthropic | Meta |
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 | 5M tokens~7,500 A4 pages of text |
Max Output Tokens Per single request | 128K | 128K |
Throughput Speed Tokens generated per second | 60 tok/s | 65 tok/s |
SWE-bench Verified Real-world software engineering | 84.2% | 74% |
GPQA Diamond Graduate-level reasoning | 82% | 84% |
Cached Input Price Prompt caching discount per 1M tokens | $1.50 / 1M | $0.00 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
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.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude Mythos 5.1 · Strengths & Key Advantages
- Arsitektur Restricted Frontier Autonomous Cognitive System mutakhir dari Anthropic dengan dukungan konteks 1M token
- Efisiensi biaya API yang kompetitif ($15/1M input, $75/1M 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
Llama 5 · Strengths & Key Advantages
- Arsitektur Mixture-of-Experts with recursive self-improvement (~600B total, 40-80B active) mutakhir dari Meta dengan dukungan konteks 5M token
- Efisiensi biaya API yang kompetitif ($0/1M input, $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.
| Metric | Claude Mythos 5.1 | Llama 5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $16.46 | $0.00 |
Output Tokens / Task Tokens generated per task | 72K | 40K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 20K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Mythos 5.1 | Llama 5 |
|---|---|---|
| Official API Model ID (SDK) | claude-mythos-5-1-20260901 | meta-llama/Llama-5 |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2026-09 | 2026-04 |
| Knowledge Cutoff | June 2026 | January 2026 |
| Architecture | Restricted Frontier Autonomous Cognitive System | Mixture-of-Experts with recursive self-improvement (~600B total, 40-80B active) |
| Parameters | Confidential | 600B+ total (~40-80B active) |
| 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) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec) |
| 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) · 372 GB VRAM (4-bit Quantized) · 1290 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, video, audio |
| Output Modalities | text | text |
Claude Mythos 5.1 vs Llama 5: Jawaban Cepat (FAQ)
Which is more intelligent, Claude Mythos 5.1 or Llama 5?
Llama 5 is more intelligent. It scores 94 compared with 88 on the composite Intelligence Index.
Which model is faster?
Llama 5 is faster, generating 65 tokens per second compared with 60 tokens per second.
Which model is cheaper to run?
Llama 5 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?
Llama 5 has lower latency, with a time to first token of 0.85s compared with 1.60s.
Which model has a larger context window?
Llama 5 has a larger context window, supporting 5M tokens compared with 1M tokens.
Kesimpulan
Choose Claude Mythos 5.1 for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis anthropic, or choose Llama 5 for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis meta.
Pertanyaan Umum (FAQ)
Which is cheaper: Claude Mythos 5.1 or Llama 5?+
Claude Mythos 5.1 costs $15/1M input and $75/1M output tokens, while Llama 5 costs $0/1M input and $0/1M output tokens.
Which model has a larger context window: Claude Mythos 5.1 or Llama 5?+
Claude Mythos 5.1 supports 1M tokens whereas Llama 5 supports 5M 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.
Sumber resmi: Anthropic & Meta Official Documentation