GPT-OSS 120B vs DeepSeek V4 Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-OSS 120B dari OpenAI dan DeepSeek V4 Pro dari DeepSeek adalah dua model AI unggulan. GPT-OSS 120B menawarkan jendela konteks 131.1K token dengan harga $0.15/$0.60 per 1 juta token, sedangkan DeepSeek V4 Pro menyediakan konteks 1M token seharga $1.32/$3.96 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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GPT-OSS 120B
Model Dasar Bobot TerbukaGPT-OSS 120B dari OpenAI adalah model AI yang dirancang untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, menghadirkan jendela konteks 131K, kecepatan 95 token/detik, indeks kecerdasan 56/100, serta tarif $0.15/$
$0.15 / 1M
$0.60 / 1M
131.1K tokens
45.5%
DeepSeek V4 Pro
Model Agen Otonom & AlatDeepSeek V4 Pro dari DeepSeek adalah model AI yang dirancang untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, menghadirkan jendela konteks 1M, kecepatan 80 token/detik, indeks kecerdasan 53/100,
$1.32 / 1M
$3.96 / 1M
1M tokens
68.5%
Perbedaan Utama Sekilas
- GPT-OSS 120B is 7.3x cheaper for API usage (input + output tokens combined).
- DeepSeek V4 Pro has a larger context window (1M vs 131K tokens).
- GPT-OSS 120B is faster at 95 tok/s vs 80 tok/s.
- DeepSeek V4 Pro leads on SWE-bench coding (68.5% vs 45.5%).
| Feature | GPT-OSS 120B | DeepSeek V4 Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 56 | 53 |
Provider | OpenAI | DeepSeek |
Input Price Cost per million input tokens | $0.15 / 1M | $1.32 / 1M |
Output Price Cost per million output tokens | $0.60 / 1M | $3.96 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.10 / 1M | $0.76 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 33K | 128K |
Throughput Speed Tokens generated per second | 95 tok/s | 80 tok/s |
SWE-bench Verified Real-world software engineering | 45.5% | 68.5% |
GPQA Diamond Graduate-level reasoning | 68.5% | 81.2% |
Cached Input Price Prompt caching discount per 1M tokens | $0.01 / 1M | $0.14 / 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.
GPT-OSS 120B · Strengths & Key Advantages
- Jendela konteks 131K dengan kapasitas output maksimum hingga 33K token (SWE-bench Verified 45.5% · GPQA Diamond 68.5%)
- Kecepatan generasi tinggi 95 token/detik dengan latensi token pertama (TTFT) hanya 480 ms
- Bobot terbuka (117B (5.1B MoE)) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
DeepSeek V4 Pro · Strengths & Key Advantages
- Jendela konteks 1M dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 68.5% · GPQA Diamond 81.2%)
- Kecepatan generasi tinggi 80 token/detik dengan latensi token pertama (TTFT) hanya 580 ms
- Bobot terbuka (MoE (Colossal)) yang siap di-hosting mandiri di GPU lokal atau cloud privat melalui vLLM dan Ollama
Considerations & Trade-offs
- Membutuhkan infrastruktur GPU dengan kapasitas VRAM yang memadai untuk eksekusi lokal presisi penuh
- Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-OSS 120B | DeepSeek V4 Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.14 | $0.67 |
Output Tokens / Task Tokens generated per task | 45K | 52K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 25K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-OSS 120B | DeepSeek V4 Pro |
|---|---|---|
| Official API Model ID (SDK) | gpt-oss-120b | deepseek-reasoner |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-08 | 2026-08 |
| Knowledge Cutoff | June 2024 | May 2026 |
| Architecture | Sparse MoE transformer with reasoning | Next-Gen Sparse MoE with Agent RL Tuning |
| Parameters | 117B (5.1B active MoE) | MoE (Colossal) |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.15/1M in) across full 131K window | Flat rate ($1.32/1M in) across full 1000K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.015/1M (no extra cache-write fee) | Automatic prefix caching at $0.14/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 73 GB VRAM (4-bit Quantized) · 252 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16) |
| Safety & Frontier Classification | OpenAI Preparedness Framework Audited & System Card Published | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text | text |
| Output Modalities | text | text |
GPT-OSS 120B vs DeepSeek V4 Pro: Jawaban Cepat (FAQ)
Which is more intelligent, GPT-OSS 120B or DeepSeek V4 Pro?
GPT-OSS 120B is more intelligent. It scores 56 compared with 53 on the composite Intelligence Index.
Which model is faster?
GPT-OSS 120B is faster, generating 95 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
GPT-OSS 120B is cheaper at $0.10 per 1M tokens blended, compared with $0.76 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-OSS 120B has lower latency, with a time to first token of 0.48s compared with 0.58s.
Which model has a larger context window?
DeepSeek V4 Pro has a larger context window, supporting 1M tokens compared with 131.1K tokens.
Kesimpulan
Baik GPT-OSS 120B (Sangat cocok untuk self-hosting di server pribadi, fine-tuning, dan kedaulatan data penuh, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun DeepSeek V4 Pro (Sangat cocok untuk alur kerja agen otonom, pemanggilan alat (tool calling), dan otomatisasi multi-langkah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: GPT-OSS 120B unggul dalam penalaran dan pemrograman, GPT-OSS 120B memberikan kecepatan generasi token lebih tinggi, dan GPT-OSS 120B lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, GPT-OSS 120B atau DeepSeek V4 Pro?+
Dalam indeks kecerdasan gabungan dan benchmark coding, GPT-OSS 120B memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API GPT-OSS 120B vs DeepSeek V4 Pro?+
GPT-OSS 120B mengenakan biaya $0.15 / $0.60 per 1M token input/output, sedangkan DeepSeek V4 Pro sebesar $1.32 / $3.96. Secara keseluruhan, GPT-OSS 120B lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
GPT-OSS 120B mendukung konteks 131.1K token dibandingkan 1M token pada DeepSeek V4 Pro, sementara GPT-OSS 120B unggul dalam kecepatan output token per detik.
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: Dokumentasi API resmi OpenAI & DeepSeek serta evaluasi benchmark independen (2026).