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OpenAI vs Fireworks AI
OpenAI's closed GPT stack against Fireworks, a fast open-model host built for post-training. The contest is frontier convenience versus tuned open weights you control.
By The Subconscious Team · Updated
OpenAI vs Fireworks AI: key differences
Fireworks aims part of its pitch squarely at teams that would otherwise default to OpenAI: reinforcement fine-tune an open model until it beats a closed API on a narrow task, then serve it at the base model's per-token price. Its SFT, DPO and RFT options come in LoRA or full-parameter form, and the Training API lets researchers run their own RL loop on Fireworks-managed trainers. GPT weights stay closed, though OpenAI does publish open-weight gpt-oss under Apache 2.0. For a general assistant with broad skills, GPT-6 Astra and the GPT-5.6 tiers remain the easier path.
Speed and compliance are closer than they first look. Fireworks has posted 167 to 174 tokens per second on DeepSeek V4 Pro in third-party measurements and serves that model's full 1M context. OpenAI sells speed through Fast mode, up to 2.5x at double the price. Both sell into enterprises: Fireworks holds SOC 2, HIPAA and ISO certifications and bills through AWS and GCP marketplaces, while OpenAI reaches buyers through Azure OpenAI and Bedrock. OpenAI's long-context surcharge past 272K tokens has no counterpart in Fireworks' listing.
What OpenAI and Fireworks AI do
OpenAI
OpenAI runs the most widely adopted closed-model API. Its September 2026 lineup has GPT-6 Astra at the top for computer use, coding and long agentic runs, priced at $10 in and $50 out per million tokens. Below it sits the GPT-5.6 family: Sol for hard professional work, Terra as the balanced default, and Luna for high-volume jobs at $0.20 in and $1.20 out. All of them carry a 1.05M token context window with up to 128K output.
Example models: GPT-6 Astra, GPT-5.6 Terra
Full OpenAI profileFireworks 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 profileShould you choose OpenAI or Fireworks AI?
OpenAI
Choose OpenAI for
- General assistants that need frontier quality across many skills
- Computer use and browser automation on GPT-6 Astra
- Teams that want hosted tools and the Agents SDK
Fireworks AI
Choose Fireworks AI for
- Reinforcement fine-tuning an open model for one narrow task
- Latency-sensitive tool calling on DeepSeek V4 Pro
- Serving fine-tunes with no per-token markup
OpenAI vs Fireworks AI at a glance
| Attribute | OpenAI | Fireworks AI |
|---|---|---|
| Model access | Closed, plus open gpt-oss | Open weights |
| Flagship models | GPT-6 Astra, GPT-5.6 Sol, Terra, Luna | DeepSeek V4 Pro, Kimi K3 |
| Speed | Fast mode: up to 2.5x at 2x price | 167–174 tok/s on DeepSeek V4 Pro |
| Price | $0.20–$10 in, $1.20–$50 out per 1M | Fine-tunes served at base price |
| Customization | N/A | SFT, DPO, RFT; Training API |
| Deployment | API, Azure OpenAI, Bedrock | Serverless, dedicated GPUs |
| Long context | 1.05M; 2x input past 272K | Full 1M on DeepSeek V4 Pro |
Frequently asked questions
What is the difference between OpenAI and Fireworks AI?
OpenAI's closed GPT stack against Fireworks, a fast open-model host built for post-training. The contest is frontier convenience versus tuned open weights you control.
When should I choose OpenAI over Fireworks AI?
General assistants that need frontier quality across many skills; Computer use and browser automation on GPT-6 Astra; Teams that want hosted tools and the Agents SDK.
When should I choose Fireworks AI over OpenAI?
Reinforcement fine-tuning an open model for one narrow task; Latency-sensitive tool calling on DeepSeek V4 Pro; Serving fine-tunes with no per-token markup.
Is OpenAI or Fireworks AI cheaper?
OpenAI: $0.20–$10 in, $1.20–$50 out per 1M. Fireworks AI: Fine-tunes served at base price. The cheaper choice depends on the model and workload.
Which has more context, OpenAI or Fireworks AI?
OpenAI: 1.05M; 2x input past 272K. 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.