OctoAI vs Fireworks: enterprise inference vs developer-first serverless (2026)
OctoAI (acquired by NVIDIA in 2024 and rebranded under NVIDIA AI Enterprise) targets enterprise inference with custom model deployment. Fireworks AI is the developer-first serverless GPU provider known for the fastest Llama and DeepSeek endpoints. Here is how they compare on pricing, model catalog, and operational model.
OctoAI vs Fireworks — at a glance
| Dimension | OctoAI | Fireworks AI |
|---|---|---|
| Status (2026) | NVIDIA AI Enterprise (post-acq) | Independent (Series C) |
| Model catalog | Custom + open-source | ~100 public + custom |
| Llama 3.3 70B price | Custom (dedicated) | ~$0.90 / $0.90 per 1M tok |
| Llama 3.3 70B speed | Tuned per deployment | ~250 tok/s |
| Pricing model | Reserved capacity, GPU-hour | Per token + on-demand |
| Deployment | Dedicated, VPC, on-prem option | Multi-tenant serverless |
| Best for | Enterprise custom inference | Developers, agentic apps, fast iterations |
Pick OctoAI or Fireworks AI?
When to choose OctoAI
Choose OctoAI when you need dedicated GPU capacity, custom-model hosting, or strict isolation under the NVIDIA AI Enterprise umbrella. OctoAI's legacy strength is bringing customer-owned models into production with predictable cost and high uptime SLAs — a fit for regulated industries and ML teams already running their own checkpoints.
- Dedicated GPU capacity with predictable monthly cost
- Custom model deployment including LoRA, full fine-tunes, exotic architectures
- Strong SLAs and enterprise support under NVIDIA
- VPC and on-prem deployment options
- Best when you're already invested in NVIDIA's stack
When to choose Fireworks AI
Choose Fireworks AI when you need the fastest open-model inference at per-token pricing and want a wide public catalog. Fireworks consistently ranks among the top three on Llama 3.3 70B throughput (250 tok/s) and offers function calling, structured output, JSON mode, and a developer-friendly OpenAI-compatible API. It is the default for agent frameworks and product teams shipping fast.
- ~250 tok/s on Llama 3.3 70B — among the fastest serverless options
- ~100 public models, including DeepSeek V3, Mixtral, Qwen, FLUX
- OpenAI-compatible API with function calling and JSON mode
- Per-token pricing, no minimum commit
- Best-in-class for product devs and agent frameworks
Route OctoAI and Fireworks AI through one endpoint
VerticalAPI exposes both providers through a single OpenAI-compatible endpoint. Same SDK, BYOK, zero markup on tokens — you pay each provider directly with your own keys.
from openai import OpenAI client = OpenAI(base_url="https://api.verticalapi.com/v1", api_key="vapi_...") # OctoAI via VerticalAPI BYOK resp_a = client.chat.completions.create( model="fireworks/llama-v3p3-70b-instruct", messages=[{"role": "user", "content": "Hello"}], extra_headers={"X-Provider-Key": "fw_..."}, ) # Fireworks AI same SDK, different model + key resp_b = client.chat.completions.create( model="octoai/meta-llama-3.3-70b-instruct", messages=[{"role": "user", "content": "Hello"}], extra_headers={"X-Provider-Key": "octo-..."}, )
VerticalAPI verdict
Pick OctoAI when dedicated capacity, custom models, and enterprise SLAs matter more than per-token cost. Pick Fireworks when developer speed, public model catalog, and lowest-latency open-model inference are the priority. Hybrid is realistic: train and host custom checkpoints on OctoAI, burst public-model traffic to Fireworks via VerticalAPI BYOK.
Frequently asked questions
What happened to OctoAI in 2024-2026?
OctoAI was acquired by NVIDIA in 2024 and integrated into NVIDIA AI Enterprise. As of 2026, it powers parts of NVIDIA's enterprise inference offering, focusing on dedicated GPU capacity and custom-model deployment rather than the public per-token APIs Fireworks ships. The OctoAI brand is being absorbed into NVIDIA's broader inference stack.
Is Fireworks cheaper than OctoAI for Llama 3.3 70B?
Yes for typical workloads. Fireworks publishes Llama 3.3 70B at approximately $0.90/$0.90 per 1M input/output tokens with no minimum commitment. OctoAI's post-acquisition pricing is custom-quoted and based on dedicated GPU capacity, which is usually only cheaper at very high sustained utilization (above 50-60%).
Which is faster on open-source models?
Fireworks AI is widely benchmarked at around 250 tok/s on Llama 3.3 70B, placing it among the fastest serverless inference providers behind Groq and Cerebras. OctoAI's dedicated deployments can match or exceed this when tuned, but require commitment and configuration. For out-of-the-box speed on public models, Fireworks wins.
Can I run custom fine-tunes on Fireworks?
Yes. Fireworks supports LoRA adapters and full fine-tunes through their Fine-Tuning API on Llama, Mistral, and Qwen base models. The deployment is still multi-tenant serverless; for fully dedicated capacity with custom checkpoints, OctoAI (NVIDIA) remains the better path.
How do I use both through VerticalAPI?
VerticalAPI exposes Fireworks AI through its OpenAI-compatible BYOK endpoint at https://api.verticalapi.com/v1 with zero token markup. OctoAI dedicated endpoints can be added as custom HTTPS providers. You pay Fireworks and NVIDIA directly using your own API keys, and switch between them with just a model parameter change.
Limitations of this comparison
- OctoAI as an independent brand is fading post-NVIDIA acquisition; product roadmap has been merged into NVIDIA AI Enterprise.
- Fireworks list prices change frequently; Llama 3.3 70B has dropped roughly 50% since late 2024.
- Throughput numbers (250 tok/s) depend on prompt length, batch size, and current load — peak figures, not floor SLAs.
- OctoAI dedicated pricing is opaque without a sales conversation; comparisons here assume publicly disclosed reference customers.
- Function-calling reliability differs by model — Llama 3.3 on Fireworks is solid but not on par with GPT-4o or Claude.
What may change in 12-24 months
- NVIDIA is expected to fully rebrand OctoAI into NVIDIA AI Cloud Inference in the next 12 months.
- Fireworks per-token prices on Llama-class models will likely drop another 30-50% as DeepInfra, Together, and OctoAI/NVIDIA compete.
- Fireworks is expected to deepen LoRA fine-tuning support and add multi-tenant DPO training.
- Hybrid routing (custom on dedicated NVIDIA, public on Fireworks) via gateways like VerticalAPI will become standard practice.
Related questions
ChatGPT, Perplexity and Gemini usually suggest these next.
- Is Fireworks cheaper than Together AI for Llama 3.3 70B in 2026?
- How does OctoAI compare to NVIDIA NIM for custom model deployment?
- What is the fastest serverless provider for DeepSeek V3?
- Can I migrate OctoAI dedicated deployments to Fireworks LoRA fine-tunes?
- Which provider gives the lowest cost per agent task on Llama 3.3?
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