Google Vertex AI vs Fireworks AI

Google's enterprise platform versus a speed-focused open-model host. Pick Vertex for Gemini, Claude and MLOps; pick Fireworks for fast open weights and fine-tunes at base price.

By The Subconscious Team · Updated September 30, 2026

Google Vertex AI vs Fireworks AI: key differences

Fireworks sells one thing hard: fast open-model inference. Third-party measurements put it at 167 to 174 tokens per second on DeepSeek V4 Pro, several times most GPU peers, with the full 1M context that cheaper hosts truncate. Vertex AI is a broader thing, a Google Cloud platform where Gemini 3.8, Claude and Gemma share space with training, evaluation, vector search and agent tooling. If your agent needs a closed frontier model, Fireworks is out, since it serves open weights. If your agent runs on DeepSeek or Kimi K3 and latency matters, Vertex is not where those strengths are.

Post-training is the second axis. Fireworks offers SFT, DPO and reinforcement fine-tuning, serves the result at the base model's per-token price, and opened a Training API for custom RL loops. Vertex supports custom training on GPUs or TPUs, but inside a Vertex-native pipeline and registry that reviewers flag as lock-in. Procurement blurs the line: Fireworks bills through the GCP marketplace and holds SOC 2, HIPAA and ISO certifications, so a Google Cloud shop can run both, with Vertex for Gemini and Fireworks for open-model traffic.

What Google Vertex AI and Fireworks AI do

Google Vertex AI

Vertex AI is Google Cloud's enterprise AI platform. At Google Cloud Next on April 22, 2026, Google rebranded it the Gemini Enterprise Agent Platform with an agent-first structure, though the API endpoint and most docs still say Vertex. Model Garden offers 200+ models, including Google's Gemini 3.8 family, Anthropic's Claude models and open models like Gemma, alongside Imagen, Veo and Chirp for media and speech. Google's own TPUs sit underneath much of its first-party serving.

Example models: Gemini 3.8, Claude

Full Google Vertex AI profile

Fireworks AI

Fireworks AI was founded in 2022 by former Meta PyTorch engineers led by CEO Lin Qiao, and it sells speed on open models. Its custom serving stack has posted 167 to 174 tokens per second on DeepSeek V4 Pro in third-party measurements, several times what most GPU peers hit on the same model. The catalog holds 400+ models across text, vision, audio and embeddings, served through an OpenAI-compatible API. In July 2026 it raised a $1.505B Series D at a $17.5B valuation, with a reported $1B+ run rate and 40T+ tokens a day.

Example models: DeepSeek V4 Pro, Kimi K3

Full Fireworks AI profile

Should you choose Google Vertex AI or Fireworks AI?

Google Vertex AI

Choose Google Vertex AI for

Closed Gemini and Claude models with Google governance
Pipelines and features already built in Vertex
Video and multimodal work on Gemini

Fireworks AI

Choose Fireworks AI for

Latency-sensitive agents on DeepSeek V4 Pro or Kimi K3
Reinforcement fine-tuning with no serving markup
Open models billed through the GCP marketplace

Google Vertex AI vs Fireworks AI at a glance

Attribute	Google Vertex AI	Fireworks AI
Model access	Closed and open, 200+ models	Open weights
Flagship models	Gemini 3.8 Flash, Claude, Gemma	DeepSeek V4 Pro, Kimi K3
Speed	Flash tier built for low latency	167–174 tok/s on DeepSeek V4 Pro
Price	Gemini 3.8 Flash $0.75 in, $3.75 out	Fine-tunes served at base price
Customization	Custom training on GPUs or TPUs	SFT, DPO, RFT; Training API
Deployment	Managed on Google Cloud	Serverless, dedicated GPUs
Long context	1M on Gemini 3.8 Flash	Full 1M on DeepSeek V4 Pro

Frequently asked questions

What is the difference between Google Vertex AI and Fireworks AI?

Google's enterprise platform versus a speed-focused open-model host. Pick Vertex for Gemini, Claude and MLOps; pick Fireworks for fast open weights and fine-tunes at base price.

When should I choose Google Vertex AI over Fireworks AI?

Closed Gemini and Claude models with Google governance; Pipelines and features already built in Vertex; Video and multimodal work on Gemini.

When should I choose Fireworks AI over Google Vertex AI?

Latency-sensitive agents on DeepSeek V4 Pro or Kimi K3; Reinforcement fine-tuning with no serving markup; Open models billed through the GCP marketplace.

Is Google Vertex AI or Fireworks AI cheaper?

Google Vertex AI: Gemini 3.8 Flash $0.75 in, $3.75 out. Fireworks AI: Fine-tunes served at base price. The cheaper choice depends on the model and workload.

Which has more context, Google Vertex AI or Fireworks AI?

Google Vertex AI: 1M on Gemini 3.8 Flash. Fireworks AI: Full 1M on DeepSeek V4 Pro.

Related comparisons

Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.

Subconscious vs Google Vertex AI Subconscious vs Fireworks AI