un abierto-weight GPT modelo de razonamiento para autohospedado agentes y controllable implementaciones.
Technical Specifications
- Provider
- OpenAI
- Category
- open-source
- Release Date
- 2025-08
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- Free / Self-Hosted
- Reasoning Effort Control
- Configurable (Low / Med / High)
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- gpt-oss-20b
- Supported SDK & API Protocol
- OpenAI Responses API & Chat Completions v1
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2027+)
- Production Rate Limits (RPM & TPM)
- Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($0.1/1M in) across full 131K window
- Prompt Cache Write & TTL Policy
- Automatic prefix caching at $0.01/1M (no extra cache-write fee)
- Computer Use & Browser GUI Agent
- 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
- Web Search Grounding & Code Sandbox
- Native Web Search tool + Hosted Code Interpreter & File Search RAG
- Fine-Tuning & Distillation Support
- Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0)
- Minimum GPU VRAM Requirement
- 13 GB VRAM (4-bit Quantized) · 45 GB VRAM (Native BF16)
- Supported Inference Engines
- vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI
- System Card & Safety Framework
- OpenAI Preparedness Framework Audited & System Card Published
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
GPT-OSS 20B Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $9.20/mo vs $20 flat plan).
Break-even point: ~926 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to GPT-OSS 20B:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 32.5%
- GPQA Diamond
- 55%
- MMLU-Pro
- 72.5%
- HumanEval
- 84.5%
- Humanity's Last Exam
- 7.2%
- Terminal-Bench
- 22%
- SciCode
- 24.5%
- LiveCodeBench
- 46%
- AIME
- 72%
- Long-Context Reasoning
- 63%
- Chatbot Arena Elo
- 1288pts
Strengths
- de pesos abiertos — run ello fully en your own hardware
- pequeño enough para un laptop o único consumidor GPU
- Cheap en hosted providers y supports llamada un herramientas
- se ejecuta comfortably en consumidor hardware
- Apache-style abierto licence para comercial use
Limitations & Trade-offs
- Clearly weaker que de frontera modelos en hard razonamiento
- texto-solo — no visión o audio entrada
- Needs careful prompt tuning un reach su mejor salida
Editorial Assessment
el mejor abierto-weight option cuando you need un own el implementación.
Best for: autohospedado agentes, en-premise implementaciones y privacy-sensitive trabajo
Compare GPT-OSS 20B
Frequently Asked Questions about GPT-OSS 20B
How much does the GPT-OSS 20B API cost per 1M tokens?+
GPT-OSS 20B by OpenAI is priced at $0.1 per 1M input tokens and $0.5 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.01 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the GPT-OSS 20B pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in GPT-OSS 20B's context window?+
GPT-OSS 20B features a 131K tokens context window, which equals approximately 98,304 English words or ~262 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 32,768 tokens.
Can I run GPT-OSS 20B locally on my own GPU (Open Weights)?+
Yes, GPT-OSS 20B (21B (3.6B active MoE)) releases open weights that can be self-hosted locally or on private cloud GPUs using vLLM, Ollama, SGLang, or llama.cpp.
Does OpenAI train on data sent to the GPT-OSS 20B API, and is commercial use allowed?+
100% Isolated when self-hosted on private GPUs or VPC. License tier: Open-Weights Research & Commercial License. Full commercial ownership of generated outputs. Supported deployment channels include: Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API.
How does GPT-OSS 20B perform on coding and reasoning benchmarks?+
GPT-OSS 20B achieves a composite Intelligence Index of 46/100, scoring 32.5% on SWE-bench Verified, 55% on GPQA Diamond, 72.5% on MMLU-Pro, and 1288 pts on Chatbot Arena Elo.
What is GPT-OSS 20B best used for?+
GPT-OSS 20B is best suited for: autohospedado agentes, en-premise implementaciones y privacy-sensitive trabajo. Assessment: el mejor abierto-weight option cuando you need un own el implementación.
OpenAI Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to OpenAI's flagship reasoning tier:
GPT-6 Astra
GPT-6.1 Sol
GPT-6 Sol
GPT-6 Luna
GPT-5.6 Sol
GPT-5.6 Terra
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to GPT-OSS 20B:
La unidad básica de texto que procesa un modelo de lenguaje, que normalmente equivale a 3 o 4 caracteres o aproximadamente 0,75 palabras. Por ejemplo, una frase típica se divide en varios tokens.
Un conjunto estandarizado de pruebas para evaluar y comparar objetivamente las capacidades de distintos modelos de IA en tareas como programación (SWE-bench) o matemáticas avanzadas (AIME).
La cantidad máxima de tokens que un modelo puede considerar a la vez, incluyendo tanto la entrada que lee como la salida que genera. Una ventana de 1.000.000 de tokens puede procesar unas 750.000 palabras en una sola petición.
Un modelo de IA entrenado para invertir cómputo adicional en pensar y validar hipótesis lógicas antes de responder, diseñado para problemas complejos de ingeniería y matemáticas.
Una técnica de razonamiento paso a paso donde el modelo genera pensamientos intermedios antes de formular la respuesta final, mejorando radicalmente la resolución de problemas matemáticos y lógicos.
La capacidad de un modelo de detectar la necesidad de una función externa y emitir argumentos JSON estructurados para ejecutar API, búsquedas web o consultas a bases de datos.
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: OpenAI open-weight model card (Hugging Face) & official pricing↗