Head-to-Head Model Comparison

Muse Spark 1.1 vs Claude Opus 4.7

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Muse Spark 1.1 vs Claude Opus 4.7: Benchmarks, Pricing & Speed Comparison

Muse Spark 1.1 by Meta and Claude Opus 4.7 by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Muse Spark 1.1 holds a notable pricing advantage for token ingestion. On output generation, Muse Spark 1.1 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 1,000K tokens. In latency-sensitive production environments, Muse Spark 1.1 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.

Comparación Directa (VS)

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Meta

Muse Spark 1.1

Agente multimodal nativo

de Meta propietario cerrado multimodal agente modelo con visual cadena de pensamiento y multi-agente orchestration.

Intelligence Index90 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

76.5%

Anthropic

Claude Opus 4.7

Software avanzado

un enhanced ingeniería de software modelo construido specifically para de misión crítica industrial architectures, formal verificación, y alto-stakes razonamiento.

Intelligence Index66 / 100
Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

79.5%

Diferencias Clave de un Vistazo

  • Muse Spark 1.1 is 1.7x cheaper for API usage (input + output tokens combined).
  • Muse Spark 1.1 is faster at 105 tok/s vs 58 tok/s.
  • Claude Opus 4.7 leads on SWE-bench coding (79.5% vs 76.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaMuse Spark 1.1Claude Opus 4.7
Intelligence Index
Composite reasoning & knowledge score (0-100)
9066
Provider
MetaAnthropic
Input Price
Cost per million input tokens
$3.00 / 1M$5.00 / 1M
Output Price
Cost per million output tokens
$15.00 / 1M$25.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.31 / 1M$3.85 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
64K128K
Throughput Speed
Tokens generated per second
105 tok/s58 tok/s
SWE-bench Verified
Real-world software engineering
76.5%79.5%
GPQA Diamond
Graduate-level reasoning
83.5%77.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.30 / 1M$0.50 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
Claude Opus 4.7
+3.0% SWE-bench lead
Costo
Muse Spark 1.1
1.7x cheaper monthly runtime
Velocidad
Muse Spark 1.1
+81% faster generation
Contexto
Tied
1M tokens window

Puntuaciones de Benchmarks Verificadas

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

Muse Spark 1.1Claude Opus 4.7
SWE-bench Verified (Autonomous Coding)

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

76.5%vs79.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

83.5%vs77.8%
MMLU-Pro (Multi-task Language Understanding)

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

88%vs89%
LMSYS Chatbot Arena Elo

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

1495ptsvs1405pts
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

N/Avs52.8%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs58 tok/s

Latencia y Tiempo de Respuesta

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
Muse Spark 1.10.60s
Claude Opus 4.71.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
Muse Spark 1.15.36s
Claude Opus 4.710.47s

Simulador Interactivo de Costos de Tokens

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

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Muse Spark 1.1 Monthly API Bill
$18.45 / month
$3/1M in · $15/1M out
Claude Opus 4.7 Monthly API Bill
$30.75 / month
$5/1M in · $25/1M out
Muse Spark 1.1 saves approximately $12.30 / month (40%) under this workload.1.7x Savings

Muse Spark 1.1 · Strengths & Key Advantages

  • completo omni-modal nativo ingesta un través de texto, imagen, audio, y video
  • visual cadena de pensamiento razonamiento para complejo diagrams
  • 1M ventana de contexto con multi-agente orchestration
Considerations & Trade-offs
  • propietario cerrado-weights modelo (unlike Llama)
  • mayor empresarial token precios

Claude Opus 4.7 · Strengths & Key Advantages

  • Industry-leading 79.5% SWE-bench Verified rendimiento en early 2026
  • Enhanced formal verificación capacidades para de misión crítica aerospace y finance software
  • Resilient multiturno error recovery en autónomo codificación agentes
Considerations & Trade-offs
  • Premium salida token precios ($25/1M) requiere thoughtful costo gobernanza
  • extendido razonamiento overhead during complejo dependency resolución

Token Use & Task Economics

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

MetricMuse Spark 1.1Claude Opus 4.7
Cost per Task
Estimated USD to finish one task
$2.20$5.49
Output Tokens / Task
Tokens generated per task
45K72K
Reasoning Tokens / Task
Thinking tokens burned per task
22K37K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaMuse Spark 1.1Claude Opus 4.7
Official API Model ID (SDK)meta-llama/Muse-Spark-1.1claude-opus-4-7-20260401
API ProtocolMeta REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-042026-04
Knowledge CutoffJanuary 2026February 2026
ArchitectureOmni-modal native thinking agent architectureAdaptive Enterprise Reasoning Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($3/1M in) across full 1000K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.3/1M tokens$0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationCustom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText 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)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationMeta Production Safety & Alignment VerifiedAnthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, video, audiotext, vision
Output Modalitiestexttext

Muse Spark 1.1 vs Claude Opus 4.7: Respuestas Rápidas (FAQ)

Which is more intelligent, Muse Spark 1.1 or Claude Opus 4.7?

Muse Spark 1.1 is more intelligent. It scores 90 compared with 66 on the composite Intelligence Index.

Which model is faster?

Muse Spark 1.1 is faster, generating 105 tokens per second compared with 58 tokens per second.

Which model is cheaper to run?

Muse Spark 1.1 is cheaper at $2.31 per 1M tokens blended, compared with $3.85 (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 1.85s.

Veredicto

Verdict & Model Selection Recommendation: Choose Muse Spark 1.1 if your priority is Enterprise multimodal agent systems, UI analysis, and complex collaborative task execution. Its performance in demanding tasks justifies its operational token cost. Choose Claude Opus 4.7 if your workflow prioritizes Autonomous software testing suites, cybersecurity code analysis, and complex refactors. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Preguntas frecuentes

How does Muse Spark 1.1 compare to Claude Opus 4.7 in API token pricing and cost per token?+

Muse Spark 1.1 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas Claude Opus 4.7 costs $5.00 input and $25.00 output. Overall, Muse Spark 1.1 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.

Which model has a larger context window: Muse Spark 1.1 or Claude Opus 4.7?+

Both Muse Spark 1.1 and Claude Opus 4.7 offer an identical context window of 1,000K tokens (~750k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.

Which AI model is better for software engineering and coding: Muse Spark 1.1 or Claude Opus 4.7?+

Muse Spark 1.1 scores 76.5% on SWE-bench Verified while Claude Opus 4.7 scores 79.5%. For autonomous software engineering and multi-file debugging, Claude Opus 4.7 holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Muse Spark 1.1 and Claude Opus 4.7?+

Muse Spark 1.1 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Opus 4.7 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between Muse Spark 1.1 and Claude Opus 4.7?+

Muse Spark 1.1 generates approximately 105 tokens per second, while Claude Opus 4.7 delivers 58 tokens per second. In latency-sensitive production environments, Muse Spark 1.1 provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Muse Spark 1.1 and Claude Opus 4.7 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Muse Spark 1.1 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 4.7. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
Explore Glossary →

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

Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.

Fuentes: GetInfoUs Independent AI Benchmarks & Official API Specs