Head-to-Head Model Comparison

Llama 5 vs Muse Spark 1.1

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri

Paylaş

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Llama 5Profile

Muse Spark 1.1Profile

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Llama 5

Açık Ağırlıklı Temel Model

Meta tarafından geliştirilen Llama 5; özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği için tasarlanmış olup 5M bağlam penceresi, 65 token/sn hız, 94/100 zeka indeksi ve ücretsiz açık ağırlık erişimi s

Intelligence Index94 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

5M tokens

SWE-bench Verified:

74%

Muse Spark 1.1

Yerel Çok Modlu Yapay Zeka

Meta tarafından geliştirilen Muse Spark 1.1; yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi için tasarlanmış olup 1M bağlam penceresi, 105 token/sn hız, 90/100 zeka indeksi ve 1M token başına $3/$15 fiyatlandırma sunar.

Intelligence Index90 / 100

Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

76.5%

Bir Bakışta Temel Farklar

Llama 5 is 1.0x cheaper for API usage (input + output tokens combined).
Llama 5 has a larger context window (5M vs 1M tokens).
Muse Spark 1.1 is faster at 105 tok/s vs 65 tok/s.
Muse Spark 1.1 leads on SWE-bench coding (76.5% vs 74.0%).

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

Feature	Llama 5	Muse Spark 1.1
Intelligence Index Composite reasoning & knowledge score (0-100)	94	90
Provider	Meta	Meta
Input Price Cost per million input tokens	$0.00 / 1M	$3.00 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$15.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$2.31 / 1M
Context Window Maximum input + output tokens	5M tokens~7,500 A4 pages of text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	128K	64K
Throughput Speed Tokens generated per second	65 tok/s	105 tok/s
SWE-bench Verified Real-world software engineering	74%	76.5%
GPQA Diamond Graduate-level reasoning	84%	83.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.00 / 1M	$0.30 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework

Coding

Muse Spark 1.1

+2.5% SWE-bench lead

Cost

Llama 5

1.0x cheaper monthly runtime

Speed

Muse Spark 1.1

+62% faster generation

Context

Llama 5

5M tokens window

Doğrulanmış Benchmark Puanları

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

Llama 5Muse Spark 1.1

SWE-bench Verified (Autonomous Coding)

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

74%vs76.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

84%vs83.5%

MMLU-Pro (Multi-task Language Understanding)

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

87%vs88%

LMSYS Chatbot Arena Elo

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

1485ptsvs1495pts

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

68%vsN/A

AIME (Advanced Math Competition)

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

88%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

65 tok/s vs105 tok/s

Gecikme Süresi ve Yanıt Hızı

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

Llama 50.85s

Muse Spark 1.10.60s

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

Llama 58.54s

Muse Spark 1.15.36s

Gerçek Zamanlı Token Maliyet Simülatörü

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)

Llama 5 Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

Muse Spark 1.1 Monthly API Bill

$18.45 / month

$3/1M in · $15/1M out

Llama 5 saves approximately $18.45 / month (100%) under this workload.1.0x Savings

Llama 5 · Strengths & Key Advantages

5M bağlam penceresi ve yanıt başına maksimum 128K çıktı tokenı kapasitesi (SWE-bench Verified 74% · GPQA Diamond 84%)
Sadece 850 ms ilk token gecikmesi (TTFT) ile saniyede 65 token yüksek üretim hızı
vLLM, SGLang veya Ollama üzerinden yerel GPU sunucularında barındırılabilen açık ağırlıklı mimari (600B+ total (~40-80B ))

Considerations & Trade-offs

Tam hassasiyette yerel GPU çıkarımı için yeterli VRAM kapasitesine sahip donanım altyapısı gerektirir
Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Muse Spark 1.1 · Strengths & Key Advantages

1M bağlam penceresi ve yanıt başına maksimum 64K çıktı tokenı kapasitesi (SWE-bench Verified 76.5% · GPQA Diamond 83.5%)
Sadece 600 ms ilk token gecikmesi (TTFT) ile saniyede 105 token yüksek üretim hızı
İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $3/$15 fiyatlandırma)

Considerations & Trade-offs

Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
Yüksek hacimli üretim trafiğinde maliyetleri optimize etmek için Prompt Caching ve Batch API kullanımı önerilir

Token Use & Task Economics

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

Metric	Llama 5	Muse Spark 1.1
Cost per Task Estimated USD to finish one task	$0.00	$2.20
Output Tokens / Task Tokens generated per task	40K	45K
Reasoning Tokens / Task Thinking tokens burned per task	20K	22K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

Feature	Llama 5	Muse Spark 1.1
Official API Model ID (SDK)	meta-llama/Llama-5	meta-llama/Muse-Spark-1.1
API Protocol	OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI	Meta REST API (OpenAI-Compatible)
Release Date	2026-04	2026-04
Knowledge Cutoff	January 2026	January 2026
Architecture	Mixture-of-Experts with recursive self-improvement (~600B total, 40-80B active)	Omni-modal native thinking agent architecture
Parameters	600B+ total (~40-80B active)	Confidential
Enterprise Rate Limits (RPM / TPM)	Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud	5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)	Free across full context window (only KV-cache VRAM scales)	Flat rate ($3/1M in) across full 1000K window
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Cached input at $0.3/1M tokens
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	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)	API Prompt Engineering & RAG Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)	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	BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 372 GB VRAM (4-bit Quantized) · 1290 GB VRAM (Native BF16)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)	Meta Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision, video, audio	text, vision, video, audio
Output Modalities	text	text

Llama 5 vs Muse Spark 1.1: Hızlı Yanıtlar (SSS)

Which is more intelligent, Llama 5 or Muse Spark 1.1?

Llama 5 is more intelligent. It scores 94 compared with 90 on the composite Intelligence Index.

Which model is faster?

Muse Spark 1.1 is faster, generating 105 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

Llama 5 is cheaper at $0.00 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Muse Spark 1.1 has lower latency, with a time to first token of 0.60s compared with 0.85s.

Which model has a larger context window?

Llama 5 has a larger context window, supporting 5M tokens compared with 1M tokens.

Sonuç

Hem Llama 5 (özel sunucuda kendi kendine barındırma (self-hosting), ince ayar ve tam veri egemenliği, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Muse Spark 1.1 (yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Llama 5 karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Muse Spark 1.1 daha yüksek üretim hızı sağlar; Llama 5 ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Llama 5 mi yoksa Muse Spark 1.1 mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Llama 5 önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Llama 5 ve Muse Spark 1.1 API fiyatları nasıl karşılaştırılır?+

Llama 5 1M giriş/çıkış tokeni başına $0.00 / $0.00 ücretlendirilirken, Muse Spark 1.1 $3.00 / $15.00 seviyesindedir. Karma maliyette Llama 5 daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Llama 5 5M token bağlam penceresi sunarken Muse Spark 1.1 1M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Muse Spark 1.1 öndedir.

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)

Llama 5 vs Muse Spark 1.1

İstediğiniz Modelleri Seçin ve Karşılaştırın

Llama 5

Muse Spark 1.1

Hangi Alanda Kim Kazanıyor?

Doğrulanmış Benchmark Puanları

Gecikme Süresi ve Yanıt Hızı

Gerçek Zamanlı Token Maliyet Simülatörü

Llama 5 · Strengths & Key Advantages

Considerations & Trade-offs

Muse Spark 1.1 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Teknik Özellikler

Llama 5 vs Muse Spark 1.1: Hızlı Yanıtlar (SSS)

Sonuç

Sıkça Sorulan Sorular (SSS)

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