DeepSeek V4 Pro vs Gemini 4 Argon
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare DeepSeek V4 Pro by DeepSeek against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.
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DeepSeek V4 Pro
Автономная агентная модельDeepSeek V4 Pro от DeepSeek — специализированная ИИ-модель для автономных агентных сценариев, вызова внешних инструментов и автоматизации, обеспечивающая контекстное окно 1M, скорость 80 ток/с и индекс интеллекта 53/100 (по цене $1.32/$3.96
$1.32 / 1M
$3.96 / 1M
1M tokens
68.5%
Gemini 4 Argon
Нативная мультимодальная ИИGemini 4 Argon от Google — специализированная ИИ-модель для нативной мультимодальной обработки текста и изображений, а также анализа документов, обеспечивающая контекстное окно 1M, скорость 115 ток/с и индекс интеллекта 97/100 (по цене $2/$
$2.00 / 1M
$10.00 / 1M
1M tokens
81.9%
Ключевые отличия кратко
- DeepSeek V4 Pro is 2.1x cheaper for API usage (input + output tokens combined).
- Gemini 4 Argon is faster at 115 tok/s vs 80 tok/s.
- Gemini 4 Argon leads on SWE-bench coding (81.9% vs 68.5%).
| Feature | DeepSeek V4 Pro | Gemini 4 Argon |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 53 | 97 |
Provider | DeepSeek | |
Input Price Cost per million input tokens | $1.32 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $3.96 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.76 / 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 | 128K | 1000K |
Throughput Speed Tokens generated per second | 80 tok/s | 115 tok/s |
SWE-bench Verified Real-world software engineering | 68.5% | 81.9% |
GPQA Diamond Graduate-level reasoning | 81.2% | 81.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.14 / 1M | $0.10 / 1M |
Кто лидирует в каждой категории?
At-a-glance decision frameworkРезультаты проверенных бенчмарков
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.
Задержка и скорость ответа
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Интерактивный калькулятор стоимости токенов
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
DeepSeek V4 Pro · Strengths & Key Advantages
- Контекстное окно 1M и генерация до 128K выходных токенов за ответ (SWE-bench Verified 68.5% · GPQA Diamond 81.2%)
- Высокая скорость генерации 80 токенов/сек при задержке до первого токена (TTFT) всего 580 мс
- Открытые веса модели (MoE (Colossal)) для локального хостинга и дообучения через vLLM, SGLang или Ollama
Considerations & Trade-offs
- Для локального запуска в полной точности требуются GPU-серверы с достаточным объемом видеопамяти (VRAM)
- В сверхсложных научных доказательствах специализированные тяжелые модели рассуждения могут показывать большую глубину
Gemini 4 Argon · Strengths & Key Advantages
- Контекстное окно 1M и генерация до 1M выходных токенов за ответ (SWE-bench Verified 81.9% · GPQA Diamond 81.5%)
- Высокая скорость генерации 115 токенов/сек при задержке до первого токена (TTFT) всего 850 мс
- Выгодная тарификация API (по цене $2/$10 за 1M токенов) с поддержкой кэширования промптов и строгих JSON-схем
Considerations & Trade-offs
- Проприетарная облачная модель без возможности скачивания весов для локального запуска в закрытом контуре
- При больших объемах трафика рекомендуется использовать кэширование промптов и Batch API для снижения затрат
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | DeepSeek V4 Pro | Gemini 4 Argon |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.67 | $2.45 |
Output Tokens / Task Tokens generated per task | 52K | 75K |
Reasoning Tokens / Task Thinking tokens burned per task | 25K | 36K |
Технические характеристики
Architecture, release timeline, capabilities, and modalities.
| Feature | DeepSeek V4 Pro | 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 | 2026-08 | 2026-09 |
| Knowledge Cutoff | May 2026 | June 2026 |
| Architecture | Next-Gen Sparse MoE with Agent RL Tuning | Pathways Multimodal Sparse Mixture-of-Experts |
| Parameters | MoE (Colossal) | 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 ($1.32/1M in) across full 1000K 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) · 43 GB VRAM (4-bit Quantized) · 151 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 V4 Pro vs Gemini 4 Argon: Быстрые ответы (FAQ)
Which is more intelligent, DeepSeek V4 Pro or Gemini 4 Argon?
Gemini 4 Argon is more intelligent. It scores 97 compared with 53 on the composite Intelligence Index.
Which model is faster?
Gemini 4 Argon is faster, generating 115 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
DeepSeek V4 Pro is cheaper at $0.76 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
DeepSeek V4 Pro has lower latency, with a time to first token of 0.58s compared with 0.85s.
Вердикт
Choose DeepSeek V4 Pro for оптимально для автономных агентных сценариев, вызова внешних инструментов и автоматизации, корпоративных rag-пайплайнов и масштабируемых api-сервисов., or choose Gemini 4 Argon for оптимально для нативной мультимодальной обработки текста и изображений, а также анализа документов, корпоративных rag-пайплайнов и масштабируемых api-сервисов..
Часто задаваемые вопросы (FAQ)
Which is cheaper: DeepSeek V4 Pro or Gemini 4 Argon?+
DeepSeek V4 Pro costs $1.32/1M input and $3.96/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: DeepSeek V4 Pro or Gemini 4 Argon?+
DeepSeek V4 Pro 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.
Официальные источники: DeepSeek & Google Official Documentation