DeepSeek V4 vs GPT-6.1 Sol
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare DeepSeek V4 by DeepSeek against GPT-6.1 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.
بدّل وقارن بين أي نموذجين
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Live comparison: no in-depth editorial review has been published for this pair yet.
DeepSeek V4
نموذج مفتوح الأوزاننموذج DeepSeek V4 المقدم من DeepSeek يوفر نافذة سياق تصل إلى 1M رمز، بتكلفة $0.3 لكل مليون رمز إدخال و$1.2 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.
$0.30 / 1M
$1.20 / 1M
1M tokens
62.8%
GPT-6.1 Sol
نموذج استدلال عميقنموذج GPT-6.1 Sol المقدم من OpenAI يوفر نافذة سياق تصل إلى 1M رمز، بتكلفة $2.0 لكل مليون رمز إدخال و$10.0 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.
$2.00 / 1M
$10.00 / 1M
1M tokens
82.3%
أهم الفروقات في لمحة
- DeepSeek V4 is 7.7x cheaper for API usage (input + output tokens combined).
- GPT-6.1 Sol is faster at 120 tok/s vs 78 tok/s.
- GPT-6.1 Sol leads on SWE-bench coding (82.3% vs 62.8%).
| Feature | DeepSeek V4 | GPT-6.1 Sol |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 56 | 94 |
Provider | DeepSeek | OpenAI |
Input Price Cost per million input tokens | $0.30 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $1.20 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.20 / 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 | 66K | 128K |
Throughput Speed Tokens generated per second | 78 tok/s | 120 tok/s |
SWE-bench Verified Real-world software engineering | 62.8% | 82.3% |
GPQA Diamond Graduate-level reasoning | 78.4% | 80.8% |
Cached Input Price Prompt caching discount per 1M tokens | $0.03 / 1M | $0.10 / 1M |
من يتفوق في كل مجال؟
At-a-glance decision frameworkنتائج الاختبارات المعيارية الموثقة
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.
زمن الاستجابة والسرعة
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
محاكي تكلفة الرموز التفاعلي
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
DeepSeek V4 · Strengths & Key Advantages
- بنية Next-Gen Sparse MoE with MLA متطورة من DeepSeek مع سعة سياق تبلغ 1M رمز
- كفاءة عالية في التكلفة ($0.3/1M إدخال و$1.2/1M إخراج) وسرعة استجابة ممتازة
- أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
- يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
- قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة
GPT-6.1 Sol · Strengths & Key Advantages
- بنية Near-Astra unified reasoning model متطورة من OpenAI مع سعة سياق تبلغ 1M رمز
- كفاءة عالية في التكلفة ($2.0/1M إدخال و$10.0/1M إخراج) وسرعة استجابة ممتازة
- أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
- يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
- قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | DeepSeek V4 | GPT-6.1 Sol |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.38 | $2.05 |
Output Tokens / Task Tokens generated per task | 48K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 36K |
المواصفات التقنية
Architecture, release timeline, capabilities, and modalities.
| Feature | DeepSeek V4 | GPT-6.1 Sol |
|---|---|---|
| Official API Model ID (SDK) | deepseek-reasoner | gpt-6-1-sol |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-07 | 2026-09 |
| Knowledge Cutoff | April 2026 | April 2026 |
| Architecture | Next-Gen Sparse MoE with MLA | Near-Astra unified reasoning model |
| 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 ($0.3/1M in) across full 1000K window | Flat rate ($2/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.03/1M (no extra cache-write fee) | Automatic prefix caching at $0.1/1M (no extra cache-write fee) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| 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) | OpenAI Preparedness Framework Audited & System Card Published |
| 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 |
| Output Modalities | text | text |
DeepSeek V4 vs GPT-6.1 Sol: إجابات سريعة (FAQ)
Which is more intelligent, DeepSeek V4 or GPT-6.1 Sol?
GPT-6.1 Sol is more intelligent. It scores 94 compared with 56 on the composite Intelligence Index.
Which model is faster?
GPT-6.1 Sol is faster, generating 120 tokens per second compared with 78 tokens per second.
Which model is cheaper to run?
DeepSeek V4 is cheaper at $0.20 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).
Which model has lower latency?
DeepSeek V4 has lower latency, with a time to first token of 0.60s compared with 1.12s.
الحكم النهائي
Choose DeepSeek V4 for أتمتة الأعمال، تطوير البرمجيات، الوكلاء الأذكياء (ai agents)، وتطبيقات deepseek الإنتاجية, or choose GPT-6.1 Sol for أتمتة الأعمال، تطوير البرمجيات، الوكلاء الأذكياء (ai agents)، وتطبيقات openai الإنتاجية.
الأسئلة الشائعة (FAQ)
Which is cheaper: DeepSeek V4 or GPT-6.1 Sol?+
DeepSeek V4 costs $0.3/1M input and $1.2/1M output tokens, while GPT-6.1 Sol costs $2/1M input and $10/1M output tokens.
Which model has a larger context window: DeepSeek V4 or GPT-6.1 Sol?+
DeepSeek V4 supports 1M tokens whereas GPT-6.1 Sol 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.
المصادر الرسمية: DeepSeek & OpenAI Official Documentation