Fireworks AI

Fireworks AI’s proprietary inference engine is built from the ground up for speed. It consistently delivers first token latency under 100 milliseconds across a wide range of model sizes. For any application that demands real time responsiveness, such as customer facing chatbots or agentic coding assistants, this performance advantage is measurable and significant. Companies like Sourcegraph and Notion have publicly noted throughput gains after migrating to the platform.

The platform provides instant access to more than 100 open source models, including Llama, Qwen, DeepSeek, Kimi K2.5, GLM 5, Mixtral, and FLUX image generators. Developers can test and swap between models through a single API endpoint with no configuration changes. This makes rapid prototyping and A/B testing across model families extremely efficient.

Fireworks AI supports the full range of fine tuning methods including LoRA, full parameter supervised fine tuning, DPO (preference alignment), and reinforcement fine tuning. Critically, fine tuned models are served at the same price as base models, removing the cost penalty that many competitors impose. Vision language model fine tuning is also supported, allowing teams to customise multimodal models with their own image and text datasets.

For workloads that need dedicated resources, Fireworks AI offers on demand GPU deployments billed per second. The hardware lineup now includes NVIDIA A100, H100, H200, B200, and B300 GPUs. This gives engineering teams the flexibility to run private, isolated model instances with guaranteed capacity and no noisy neighbour issues.

A recent addition, Fire Pass is a $7 per week subscription that provides unlimited token access to the Kimi K2.5 Turbo model at speeds around 200 to 250 tokens per second. It is designed specifically for developers using agentic coding tools like Claude Code and OpenCode, offering a flat rate alternative to unpredictable per token billing.