40-70% cheaper LLM inference vs Fireworks AI
Fleek is 40-70% cheaper than Fireworks AI on most models. The gap is widest on Llama 3.1 70B (70% cheaper) and DeepSeek R1 (70% cheaper). Fireworks has strong features like grammar-constrained generation and speculative decoding, but if cost is king, Fleek wins.
Fireworks AI built their reputation on fast inference. They've invested heavily in optimization and can deliver impressive latency numbers. But fast doesn't always mean cheap—their per-token pricing can add up quickly at scale.
Fleek optimizes for both speed and cost. Our GPU-second pricing means when inference runs faster, your bill drops. We're not just competing on latency—we're competing on total cost of ownership.
This comparison digs into the pricing differences, explores where each platform excels, and helps you understand which one fits your production needs.
| Model | Fleek | Fireworks AI | Savings |
|---|---|---|---|
| DeepSeek R1 (671B) | ~$0.67/M tokens | $2.36/M tokens | 70% |
| Llama 3.1 70B | ~$0.20/M tokens | $0.90/M tokens | 70% |
| Mixtral 8x22B | ~$0.25/M tokens | $0.90/M tokens | 70% |
| Llama 3.1 8B | ~$0.03/M tokens | $0.10/M tokens | 70% |
| Qwen 2.5 Coder 32B | ~$0.10/M tokens | $0.20/M tokens | 50% |
Fireworks pricing from their serverless tier. They also offer on-demand dedicated deployments at different rates.
Fleek's pricing is straightforward: $0.0025 per GPU-second across all models. The faster we can run inference, the cheaper your per-token cost becomes. Our Blackwell GPUs with FP4 precision and continuous optimization work in your favor.
We don't charge differently for different models—a GPU-second costs the same whether you're running Mistral 7B or DeepSeek R1. This simplicity makes capacity planning predictable.
Fireworks uses per-token pricing with model-specific rates. They've invested in optimization features like speculative decoding (predicting multiple tokens at once) and grammar-constrained generation (forcing outputs to match a schema).
Their serverless tier handles bursty workloads, while on-demand dedicated deployments offer guaranteed capacity. Enterprise customers get additional features like private deployments.
Both support OpenAI-compatible APIs. The main adjustment is if you're using Fireworks-specific features like grammar constraints—you'll need to handle schema validation differently on Fleek.
Fireworks has invested heavily in latency optimization and may have lower time-to-first-token on some models. Fleek optimizes for throughput and cost, which often means competitive latency but significantly lower prices. For most applications, both are fast enough.
Fleek supports JSON output through prompt engineering and model capabilities, but doesn't have Fireworks' grammar-constrained generation that guarantees valid JSON. If strict schema validation is critical, Fireworks has the edge.
Yes, Fleek supports function calling through the OpenAI-compatible API. The models handle tool use natively. However, Fireworks' grammar constraints can provide stricter guarantees on output format.
Fireworks has more embedding model options and dedicated embedding APIs. Fleek focuses primarily on text generation. For embedding-heavy workloads, Fireworks likely has better tooling.
Coming soon. We're building support for any model—not just the open-source ones we showcase. Upload your fine-tuned weights or proprietary model, and we'll apply the same optimization. Same $0.0025/GPU-sec pricing, no custom model premium. Launching in the coming weeks.
Fleek beats Fireworks on price across the board—40-70% cheaper depending on model. That's significant for any team running inference at scale.
Fireworks wins on specialized features: grammar-constrained generation, speculative decoding, and embedding APIs. If those features are central to your workflow, the price difference might be worth it.
For straightforward LLM inference where cost matters, Fleek is the clear choice. For applications requiring strict output formatting or low-latency streaming, evaluate Fireworks' specialized features against the cost savings.
Note: Fleek is actively expanding model support with new models added regularly. Features where competitors currently have an edge may become available on Fleek over time. Our goal is universal model optimization—supporting any model from any source at the lowest possible cost.
Run your numbers in our calculator or get started with $5 free.