Muse Spark 1.1 vs Claude Opus 4.7
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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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.
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Muse Spark 1.1
Native Multimodal AgentMeta's proprietary closed multimodal agent model featuring visual chain-of-thought and multi-agent orchestration.
$3.00 / 1M
$15.00 / 1M
1M tokens
76.5%
Claude Opus 4.7
Advanced SoftwareAn enhanced software engineering model built specifically for mission-critical industrial architectures, formal verification, and high-stakes reasoning.
$5.00 / 1M
$25.00 / 1M
1M tokens
79.5%
Key Differences at a Glance
- 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%).
| Feature | Muse Spark 1.1 | Claude Opus 4.7 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 90 | 66 |
Provider | Meta | Anthropic |
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 text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 64K | 128K |
Throughput Speed Tokens generated per second | 105 tok/s | 58 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 |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
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.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Muse Spark 1.1 · Strengths & Key Advantages
- Full omni-modal native ingestion across text, image, audio, and video
- Visual Chain-of-Thought reasoning for complex diagrams
- 1M context window with multi-agent orchestration
Considerations & Trade-offs
- Proprietary closed-weights model (unlike Llama)
- Higher enterprise token pricing
Claude Opus 4.7 · Strengths & Key Advantages
- Industry-leading 79.5% SWE-bench Verified performance in early 2026
- Enhanced formal verification capabilities for mission-critical aerospace and finance software
- Resilient multi-turn error recovery in autonomous coding agents
Considerations & Trade-offs
- Premium output token pricing ($25/1M) requires thoughtful cost governance
- Extended reasoning overhead during complex dependency resolution
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Muse Spark 1.1 | Claude Opus 4.7 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.20 | $5.49 |
Output Tokens / Task Tokens generated per task | 45K | 72K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 37K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | Muse Spark 1.1 | Claude Opus 4.7 |
|---|---|---|
| Official API Model ID (SDK) | meta-llama/Muse-Spark-1.1 | claude-opus-4-7-20260401 |
| API Protocol | Meta REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-04 | 2026-04 |
| Knowledge Cutoff | January 2026 | February 2026 |
| Architecture | Omni-modal native thinking agent architecture | Adaptive Enterprise Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 4,000 – 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 window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Cached input at $0.3/1M tokens | $0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Custom Model Tuning via Amazon Bedrock & Prompt 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) |
| Quantization & Min GPU VRAM | Cloud-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 Classification | Meta Production Safety & Alignment Verified | Anthropic 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 Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision, video, audio | text, vision |
| Output Modalities | text | text |
Muse Spark 1.1 vs Claude Opus 4.7: Quick Answers
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.
Verdict
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.
Frequently asked questions
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%.
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.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs