By Fikra DevRel • 4 min read

Together AI vs Fikra API: Integration Comparison

Together AI vs Fikra API: Integration Comparison

Introduction

Together AI is an external AI infrastructure provider that offers access to various open-source and proprietary models. Fikra API is a separate service that provides access to its own set of models (such as fikra-flash and fikra-pro-20b) through an OpenAI-compatible interface. This page compares the integration approaches of these two distinct services to help developers understand how to connect to each.

Comparison

Feature Together AI Fikra API
Integration Style External provider with its own SDK and API structure. OpenAI-style chat-completions endpoint.
Authentication Uses Together AI API keys. Uses Authorization: Bearer fk_live_... headers.
Endpoint Compatibility Together AI specific endpoints. Compatible with OpenAI SDKs via https://api.fikraapi.co.ke/v1.
Payment/Access Managed through Together AI's billing system. Managed via Fikra dashboard with Paystack integration (M-Pesa and cards accepted).
Model Naming Uses Together AI's model identifiers. Uses Fikra aliases like fikra-flash, fikra-fast-8b, fikra-pro-20b.

Python Example: Using Fikra API with OpenAI SDK

Because Fikra API supports OpenAI-style requests, you can use the standard OpenAI Python SDK by pointing it to the Fikra base URL. Note that you must use a valid Fikra model alias.

import os
from openai import OpenAI

# Initialize the client with Fikra's base URL and API key
client = OpenAI(
    base_url="https://api.fikraapi.co.ke/v1",
    api_key=os.getenv("FIKRA_API_KEY")
)

# Make a request using a Fikra model alias
response = client.chat.completions.create(
    model="fikra-flash",
    messages=[
        {"role": "user", "content": "Hello, Fikra!"}
    ]
)

print(response.choices[0].message.content)

When Fikra API is a Fit

Fikra API is a suitable choice for developers who:

  • Prefer an OpenAI-compatible interface for easier integration with existing tools.
  • Are based in or have access to payment methods supported by Paystack (such as M-Pesa).
  • Want to use Fikra's specific model lineup, such as fikra-flash for speed or fikra-pro-20b for higher capability.
  • Need a straightforward API key authentication flow without complex enterprise onboarding.

Verify Before Production

Before deploying Fikra API in a production environment, please:

  1. Check the Model Registry: Confirm that the specific model alias you intend to use is currently available and enabled for your account.
  2. Review Rate Limits: Be aware that unverified accounts are limited to 30 RPM, while trusted accounts are limited to 100 RPM. Ensure your application's traffic patterns fit within these limits.
  3. Test Streaming: If you plan to use stream: true, verify that your client correctly handles Server-Sent Events (SSE).
  4. Confirm Billing: Ensure your Fikra dashboard wallet has sufficient credits and that your payment method is correctly linked via Paystack.

Note: Fikra API does not host or resell models from Together AI or other external providers. Always verify model availability and specific terms directly with the provider.


JM
// The Founder

James Miano

CTO & ML Engineer at Lacesse Ventures. James specializes in low-overhead LLM quantization processes, custom ternary weights architectures, and localized server optimization.

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