Muse Spark 1.1 vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare Muse Spark 1.1 by Meta against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.
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Muse Spark 1.1
Yerel Çok Modlu Yapay ZekaMeta 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.
$3.00 / 1M
$15.00 / 1M
1M tokens
76.5%
Gemini 4 Argon
Yerel Çok Modlu Yapay ZekaGoogle tarafından geliştirilen Gemini 4 Argon; yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi için tasarlanmış olup 1M bağlam penceresi, 115 token/sn hız, 97/100 zeka indeksi ve 1M token başına $2/$10 fiyatlandırma sunar.
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Bir Bakışta Temel Farklar
- Gemini 4 Argon is 1.5x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon is faster at 115 tok/s vs 105 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 76.5%).
| Feature | Muse Spark 1.1 | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 90 | 97 |
Provider | Meta | |
Input Price Cost per million input tokens | $3.00 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.31 / 1M | $1.47 / 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 | 1000K |
Throughput Speed Tokens generated per second | 105 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 76.5% | 81.9% |
GPQA Diamond Graduate-level reasoning | 83.5% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.30 / 1M | $0.10 / 1M |
Hangi Alanda Kim Kazanıyor?
At-a-glance decision frameworkDoğrulanmış Benchmark Puanları
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.
Gecikme Süresi ve Yanıt Hızı
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Gerçek Zamanlı Token Maliyet Simülatörü
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
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
Gemini 4 Argon · Strengths & Key Advantages
- 1M bağlam penceresi ve yanıt başına maksimum 1M çıktı tokenı kapasitesi (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
- Sadece 850 ms ilk token gecikmesi (TTFT) ile saniyede 115 token yüksek üretim hızı
- İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $2/$10 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 | Muse Spark 1.1 | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.20 | $2.45 |
Output Tokens / Task Tokens generated per task | 45K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 36K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | Muse Spark 1.1 | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | meta-llama/Muse-Spark-1.1 | models/gemini-4-argon |
| API Protocol | Meta REST API (OpenAI-Compatible) | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2026-04 | 2026-09 |
| Knowledge Cutoff | January 2026 | June 2026 |
| Architecture | Omni-modal native thinking agent architecture | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 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 | Implicit + Explicit Context Caching at $0.1/1M with configurable 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 | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | Vertex AI Supervised Adapter Tuning & Context 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 | 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 | Google DeepMind Frontier Safety Framework Verified |
| 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, audio, video |
| Output Modalities | text | text |
Muse Spark 1.1 vs Gemini 4 Argon: Hızlı Yanıtlar (SSS)
Which is more intelligent, Muse Spark 1.1 or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 90 on the composite Intelligence Index.
Which model is faster?
Gemini 4 Argon is faster, generating 115 tokens per second compared with 105 tokens per second.
Which model is cheaper to run?
Gemini 4 Argon is cheaper at $1.47 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.
Sonuç
Choose Muse Spark 1.1 for yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir., or choose Gemini 4 Argon for yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi, kurumsal rag mimarileri ve ölçeklenebilir üretim api entegrasyonları için idealdir..
Sıkça Sorulan Sorular (SSS)
Which is cheaper: Muse Spark 1.1 or Gemini 4 Argon?+
Muse Spark 1.1 costs $3/1M input and $15/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: Muse Spark 1.1 or Gemini 4 Argon?+
Muse Spark 1.1 supports 1M tokens whereas Gemini 4 Argon 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.
Resmi kaynaklar: Meta & Google Official Documentation