Neureus vs Fireworks AI

Inference API vs.
Full AI Backend

Fireworks AI delivers fast, low-latency inference on open-source models. Neureus delivers that plus GPT-4o, Claude, and Gemini — with RAG, agents, and workflows built in. One API key for your entire AI stack.

Try Neureus free See AI Gateway

Proprietary model access

Fireworks routes exclusively to open-source models. Neureus adds GPT-4o, Claude (all variants), and Gemini — same API, same response format, same streaming interface. Switch models by changing a string.

Free open-source tier

Fireworks has no free tier — every token costs money. Neureus routes Llama, Qwen, Mistral, and DeepSeek variants through Cloudflare Workers AI at $0/call on all plans, forever.

Application layer built in

Fireworks is inference-only. Neureus adds RAG (ingest + query), agents (ReAct loop), workflows (HITL, branching), and batch inference (40% off) — no additional services to provision.

Pricing comparison

Fireworks charges per token for every model including open-source. Neureus offers Workers AI models free and prices paid models 10% below OpenRouter.

Model	Fireworks AI	Neureus
Llama 3.1 70B	$0.90/1M	Free (Workers AI)
Llama 3.1 8B	$0.20/1M	Free (Workers AI)
Mixtral 8x7B	$0.50/1M	Free (Workers AI)
DeepSeek R1	$0.55/1M	$0.50/1M
Qwen 2.5 72B	$0.90/1M	Free (Workers AI)
GPT-4o	Not available	$4.50/1M
Claude Sonnet 4.6	Not available	$2.70/1M

Feature comparison

Feature	Fireworks AI	Neureus
Open-source model inference	✓	✓
Function calling (tool use)	✓	✓
JSON mode / structured output	✓	✓
SSE streaming	✓	✓
Proprietary models (GPT-4o, Claude, Gemini)	—	✓
Prompt preprocessor (10–30% token savings)	—	✓
Managed RAG pipeline	—	✓
Batch inference (40% off)	—	✓
AI agents (ReAct, tool use)	—	✓
Workflow engine (HITL, branching)	—	✓
MCP server (AI assistant tooling)	—	✓
Composite AI patterns (ensemble, routing)	—	✓
BYOK encrypted key storage	—	✓
TypeScript SDK	—	✓
Free tier	—	✓

Migrate from Fireworks in one line

The Neureus API is OpenAI-compatible. Swap the base URL and key — no other changes needed.

Before (Fireworks)

const response = await fetch(
  'https://api.fireworks.ai/inference/v1/chat/completions',
  {
    headers: {
      'Authorization': 'Bearer fw_your_key',
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: 'accounts/fireworks/models/llama-v3p1-70b-instruct',
      messages: [{ role: 'user', content: prompt }],
    }),
  }
);

After (Neureus)

const response = await fetch(
  'https://app.neureus.ai/ai/chat',
  {
    headers: {
      'Authorization': 'Bearer nr_your_key',
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      model: '@wai/llama-3.3-70b',  // free via Workers AI
      // or: 'claude-sonnet-4-6', 'gpt-4o', 'deepseek-r1'
      messages: [{ role: 'user', content: prompt }],
    }),
  }
);

When Fireworks AI wins

Fireworks built a reputation for extremely low-latency inference — sub-100ms time-to-first-token on many models. If raw inference speed on open-source models is your primary constraint, Fireworks's specialized hardware optimization may deliver better p50/p99 latency than Neureus.

Fireworks also has a dedicated function-calling fine-tuned model (FireFunction) and custom model deployment for teams that want to serve proprietary weights. Neureus doesn't offer custom model hosting.

Inference API vs.Full AI Backend