Reka Flash

Model ID: reka/reka-flash
Provider: Reka - Reka AI
Canonical Slug: reka/reka-flash

Overview

Reka Flash is a fast, efficient multimodal model from Reka AI, designed for quick inference on both text and image understanding tasks. It offers good performance with reduced latency.

Specifications

Pricing

Capabilities

• Vision / Multimodal
• Text Generation

Supported Parameters

The model supports the following parameters in API requests:

• temperature: Controls randomness (0.0 - 2.0), default: 1.0
• top_p: Nucleus sampling (0.0 - 1.0), default: 1.0
• top_k: Top-k filtering
• frequency_penalty: Reduces repetition (-2.0 to 2.0)
• presence_penalty: Encourages new topics (-2.0 to 2.0)
• repetition_penalty: Alternative repetition control (0.5 - 2.0)
• stop: Stop sequences
• seed: Random seed for reproducibility
• max_tokens: Maximum output length

API Usage Example

curl -X POST https://api.langmart.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "reka/reka-flash",
    "messages": [
      {
        "role": "user",
        "content": "Explain quantum computing in simple terms"
      }
    ],
    "temperature": 1.0,
    "max_tokens": 8192,
    "top_p": 1.0
  }'

Performance Metrics

Speed & Quality Tradeoff

• Inference Speed: Fast
• Quality Tier: Advanced
• Cost Efficiency: Optimized for production

Recommended Use Cases

• Long-form text generation
• Code generation and analysis
• Conversational AI
• Complex reasoning tasks
• Information synthesis

Related & Alternative Models

From Same Provider

Comparable Models from Other Providers

• OpenAI: GPT-4 Turbo, GPT-4o
• Anthropic: Claude 3.5 Sonnet
• Google: Gemini 2.0 Flash
• DeepSeek: DeepSeek-R1

Python Integration

import anthropic

client = anthropic.Anthropic(
    api_key="YOUR_API_KEY",
    base_url="https://api.langmart.ai/v1"
)

message = client.messages.create(
    model="reka/reka-flash",
    max_tokens=8192,
    messages=[
        {
            "role": "user",
            "content": "Your prompt here"
        }
    ]
)

print(message.content[0].text)

JavaScript/Node.js Integration

import OpenAI from "openai";

const openai = new OpenAI({
  apiKey: process.env.LANGMART_API_KEY,
  baseURL: "https://api.langmart.ai/v1",
});

const completion = await openai.chat.completions.create({
  model: "reka/reka-flash",
  messages: [
    {
      role: "user",
      content: "Your prompt here",
    },
  ],
  max_tokens: 8192,
});

console.log(completion.choices[0].message.content);

Performance Notes

Strengths

• Efficient inference with good quality
• Well-suited for production workloads
• Strong instruction-following ability
• Balanced performance and cost

Considerations

• Context length may be limited for very long documents
• Specialized for specific tasks

Additional Information

• Hugging Face Model: Not available
• License: Open or Commercial (depends on provider)
• Streaming: Supported
• Function Calling: Depends on model configuration
• Vision Capabilities: Yes
• Web Search: No

Availability & Status

• LangMart Status: Available
• Rate Limits: Standard LangMart limits apply
• SLA: Subject to provider availability

Documentation Generated: 2025-12-24
Source: LangMart API & Public Documentation
Last Updated: December 2025