de frontera multimodal modelo fundacional natively procesamiento texto, alto-resolución imagery, video clips, y audio inputs.
Technical Specifications
- Provider
- Reka
- Category
- flagship
- Release Date
- 2024-04
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- API Pay-as-you-go
- Reasoning Effort Control
- Fixed
- 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)
- reka-core
- Supported SDK & API Protocol
- Reka REST API (OpenAI-Compatible)
- Lifecycle & Deprecation Status
- Legacy Stable (Upgrade path available in Reka lineup)
- Production Rate Limits (RPM & TPM)
- 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($3/1M in) across full 128K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.3/1M tokens
- 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
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- API Prompt Engineering & RAG Distillation
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed Reka Cloud API
- System Card & Safety Framework
- Reka Production Safety & Alignment Verified
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Reka Core Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~31 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 Reka Core:
Benchmark Scores & 6-Axis Capability Radar
- MMLU-Pro
- 75%
- HumanEval
- 80%
- Chatbot Arena Elo
- 1270pts
Strengths
- nativo omnimodal procesamiento spanning texto, video, voz, y imagery
- alto precisión en multi-frame video scene comprensión y audio transcription
- construido por former Google DeepMind, FAIR, y Baidu de frontera AI researchers
Limitations & Trade-offs
- Premium comercial precios ($3.00 entrada / $15.00 salida por 1M)
- Smaller empresarial ecosistema que major cloud hyper-scalers
Editorial Assessment
un versatile de frontera omnimodal modelo construido del ground up para rich media procesamiento.
Best for: multimodal video búsqueda, audio-visual QA, y cross-format media inteligencia
Compare Reka Core
Frequently Asked Questions about Reka Core
How much does the Reka Core API cost per 1M tokens?+
Reka Core by Reka is priced at $3 per 1M input tokens and $15 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.3 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Reka Core 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 Reka Core's context window?+
Reka Core features a 128K tokens context window, which equals approximately 96,000 English words or ~256 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.
Can I run Reka Core locally on my own GPU (Open Weights)?+
No, Reka Core is a proprietary closed-weights model hosted by Reka. It cannot be downloaded for local GPU execution and must be accessed via Reka's official API or cloud platform.
Does Reka train on data sent to the Reka Core API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Reka Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Reka Cloud API & Enterprise Endpoints.
How does Reka Core perform on coding and reasoning benchmarks?+
Reka Core achieves a composite Intelligence Index of 77/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 75% on MMLU-Pro, and 1270 pts on Chatbot Arena Elo.
What is Reka Core best used for?+
Reka Core is best suited for: multimodal video búsqueda, audio-visual QA, y cross-format media inteligencia. Assessment: un versatile de frontera omnimodal modelo construido del ground up para rich media procesamiento.
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Reka Core:
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.