DeepSeek R1 vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare DeepSeek R1 by DeepSeek against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.
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DeepSeek R1
Model Open-WeightsDeepSeek R1 dari DeepSeek adalah model AI canggih dengan jendela konteks 128K token serta harga API $0.55/1M token input dan $2.19/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$0.55 / 1M
$2.19 / 1M
128K tokens
49.2%
Gemini 4 Argon
Model Penalaran MendalamGemini 4 Argon dari Google adalah model AI canggih dengan jendela konteks 1M token serta harga API $2/1M token input dan $10/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Perbedaan Utama Sekilas
- DeepSeek R1 is 4.0x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon has a larger context window (1M vs 128K tokens).
- Gemini 4 Argon is faster at 115 tok/s vs 45 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 49.2%).
| Feature | DeepSeek R1 | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 49 | 97 |
Provider | DeepSeek | |
Input Price Cost per million input tokens | $0.55 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $2.19 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.43 / 1M | $1.47 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 8K | 1000K |
Throughput Speed Tokens generated per second | 45 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 49.2% | 81.9% |
GPQA Diamond Graduate-level reasoning | 71.5% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.14 / 1M | $0.10 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
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.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
DeepSeek R1 · Strengths & Key Advantages
- Arsitektur Open-Weights Reasoning MoE mutakhir dari DeepSeek dengan dukungan konteks 128K token
- Efisiensi biaya API yang kompetitif ($0.55/1M input, $2.19/1M output) dan respons cepat
- Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
- Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
- Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik
Gemini 4 Argon · Strengths & Key Advantages
- Arsitektur Pathways Multimodal Sparse Mixture-of-Experts mutakhir dari Google dengan dukungan konteks 1M token
- Efisiensi biaya API yang kompetitif ($2/1M input, $10/1M output) dan respons cepat
- Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
- Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
- Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | DeepSeek R1 | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.65 | $2.45 |
Output Tokens / Task Tokens generated per task | 45K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 25K | 36K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | DeepSeek R1 | Gemini 4 Argon |
|---|---|---|
| Official API Model ID (SDK) | deepseek-reasoner | models/gemini-4-argon |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2025-01 | 2026-09 |
| Knowledge Cutoff | July 2024 | June 2026 |
| Architecture | Open-Weights Reasoning MoE | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | 671B Total (37B 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 | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.55/1M in) across full 128K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.14/1M (no extra cache-write fee) | Implicit + Explicit Context Caching at $0.1/1M with configurable TTL |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | 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 | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Vertex AI Supervised Adapter Tuning & Context Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | 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) · 416 GB VRAM (4-bit Quantized) · 1443 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) | Google DeepMind Frontier Safety Framework 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 | text, vision, audio, video |
| Output Modalities | text | text |
DeepSeek R1 vs Gemini 4 Argon: Jawaban Cepat (FAQ)
Which is more intelligent, DeepSeek R1 or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 49 on the composite Intelligence Index.
Which model is faster?
Gemini 4 Argon is faster, generating 115 tokens per second compared with 45 tokens per second.
Which model is cheaper to run?
DeepSeek R1 is cheaper at $0.43 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 4 Argon has lower latency, with a time to first token of 0.85s compared with 0.95s.
Which model has a larger context window?
Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 128K tokens.
Kesimpulan
Choose DeepSeek R1 for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis deepseek, or choose Gemini 4 Argon for otomasi perusahaan, pengembangan perangkat lunak, agen ai, dan alur kerja produksi berbasis google.
Pertanyaan Umum (FAQ)
Which is cheaper: DeepSeek R1 or Gemini 4 Argon?+
DeepSeek R1 costs $0.55/1M input and $2.19/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: DeepSeek R1 or Gemini 4 Argon?+
DeepSeek R1 supports 128K 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.
Sumber resmi: DeepSeek & Google Official Documentation