Muse Spark 1.1 vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Muse Spark 1.1 by Meta against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.
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Muse Spark 1.1
Nativ Multimodale KIMuse Spark 1.1 von Meta ist ein KI-Modell für nativ multimodale Verarbeitung von Text und Bild sowie visuelle Dokumentenanalyse mit 1M Kontextfenster, 105 Token/s Durchsatz, einem Intelligenz-Index von 90/100 und $3/$15 pro 1M Token.
$3.00 / 1M
$15.00 / 1M
1M tokens
76.5%
Claude Opus 5.5
Frontier-Flaggschiff-ModellClaude Opus 5.5 von Anthropic ist ein KI-Modell für anspruchsvolles Enterprise-Reasoning, Softwareentwicklung und produktive KI-Workflows mit 1M Kontextfenster, 78 Token/s Durchsatz, einem Intelligenz-Index von 94/100 und $4/$20 pro 1M Toke
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Wichtigste Unterschiede auf einen Blick
- Muse Spark 1.1 is 1.3x cheaper for API usage (input + output tokens combined).
- Muse Spark 1.1 is faster at 105 tok/s vs 78 tok/s.
- Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 76.5%).
| Feature | Muse Spark 1.1 | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 90 | 94 |
Provider | Meta | Anthropic |
Input Price Cost per million input tokens | $3.00 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.31 / 1M | $3.08 / 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 | 78 tok/s |
SWE-bench Verified Real-world software engineering | 76.5% | 84.6% |
GPQA Diamond Graduate-level reasoning | 83.5% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.30 / 1M | $0.40 / 1M |
Wer gewinnt in welcher Disziplin?
At-a-glance decision frameworkGeprüfte Benchmark-Ergebnisse im Vergleich
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.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latenz & Antwortzeit
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Interaktiver Token-Kosten-Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Muse Spark 1.1 · Strengths & Key Advantages
- 1M Kontextfenster und bis zu 64K maximale Output-Token (SWE-bench Verified 76.5% · GPQA Diamond 83.5%)
- Hohe Generierungsgeschwindigkeit von 105 Token/Sekunde bei nur 600 ms Erstlatenz (TTFT)
- Effiziente API-Struktur ($3/$15 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
- Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
- Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung
Claude Opus 5.5 · Strengths & Key Advantages
- 1M Kontextfenster und bis zu 128K maximale Output-Token (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
- Hohe Generierungsgeschwindigkeit von 78 Token/Sekunde bei nur 1400 ms Erstlatenz (TTFT)
- Effiziente API-Struktur ($4/$20 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe
Considerations & Trade-offs
- Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
- Bei hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Muse Spark 1.1 | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.20 | $3.85 |
Output Tokens / Task Tokens generated per task | 45K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 42K |
Technische Spezifikationen
Architecture, release timeline, capabilities, and modalities.
| Feature | Muse Spark 1.1 | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | meta-llama/Muse-Spark-1.1 | claude-opus-5-5-20260901 |
| API Protocol | Meta REST API (OpenAI-Compatible) | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-04 | 2026-09 |
| Knowledge Cutoff | January 2026 | June 2026 |
| Architecture | Omni-modal native thinking agent architecture | Extended Autonomous Hybrid 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 | $0.4/1M 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 5.5: Schnelle Antworten (FAQ)
Which is more intelligent, Muse Spark 1.1 or Claude Opus 5.5?
Claude Opus 5.5 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 78 tokens per second.
Which model is cheaper to run?
Muse Spark 1.1 is cheaper at $2.31 per 1M tokens blended, compared with $3.08 (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 1.40s.
Fazit
Choose Muse Spark 1.1 for optimal für nativ multimodale verarbeitung von text und bild sowie visuelle dokumentenanalyse, enterprise-rag-systeme und skalierbare api-pipelines., or choose Claude Opus 5.5 for optimal für anspruchsvolles enterprise-reasoning, softwareentwicklung und produktive ki-workflows, enterprise-rag-systeme und skalierbare api-pipelines..
Häufig gestellte Fragen (FAQ)
Which is cheaper: Muse Spark 1.1 or Claude Opus 5.5?+
Muse Spark 1.1 costs $3/1M input and $15/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.
Which model has a larger context window: Muse Spark 1.1 or Claude Opus 5.5?+
Muse Spark 1.1 supports 1M tokens whereas Claude Opus 5.5 supports 1M 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.
Offizielle Quellen: Meta & Anthropic Official Documentation