Fireworks AI vs LiteLLM
Fireworks AI vs LiteLLM: side-by-side comparison of two inference platforms & gateways systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
How they relate
- Fireworks AI integrates with LiteLLM — Fireworks AI docs integration: LiteLLM (LLM Gateways; native fireworks_ai provider).
- LiteLLM integrates with Fireworks AI — LiteLLM docs have a Fireworks AI provider page.
Cost & capability
| Fireworks AI | LiteLLM | |
|---|---|---|
| Cost tier | searched not found | searched not found |
| $/Mtok input | searched not found | searched not found |
| $/Mtok output | searched not found | searched not found |
Where they differ (10)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Fireworks AI | LiteLLM | |
|---|---|---|
| Type | Fast OSS LLM inference cloud | Universal LLM API + Proxy |
| Created | 2022 | 2023 |
| Latest release | v1.2.30 (2026-10-21) — fireworks-ai | v1.106.4 (2026-10-25) |
| License | proprietary; Python SDK Apache-2.0 | MIT (except enterprise/ directory, commercial license) |
| GitHub | searched not found | BerriAI/litellm — ~62.1k stars, last commit 2026-10 |
| Pricing | Serverless pay-per-token; on-demand GPUs $8/hr (H100/H200), $13/hr (B200), $15/hr (B300); fine-tuning from $0.50 per 1M training tokens (LoRA SFT up to 16B) | OSS free; Enterprise custom pricing (30-day self-hosted trial key) |
| Funding | $77M total raised through Series B 2024-07 ($52M, Sequoia led; $552M valuation). | BerriAI raised $1.6M seed 2023 (Y Combinator W23); commercial steward of LiteLLM OSS. |
| Deployment | searched not found | Self-hosted only — SDK and proxy; Enterprise self-hosted or air-gapped |
| API surface | OpenAI-compatible REST API, Python SDK (fireworks-ai) | Python SDK, OpenAI-compatible proxy REST API |
| MCP | searched not found | yes — MCP Gateway in LiteLLM Proxy (Streamable HTTP, SSE, stdio) with per-key/team access control |
At a glance
| Fireworks AI | LiteLLM | |
|---|---|---|
| Section | Inference platforms & gateways | Inference platforms & gateways |
| Tier | T1 | T1 |
| Type | Fast OSS LLM inference cloud | Universal LLM API + Proxy |
| Created | 2022 | 2023 |
| Latest release | v1.2.30 (2026-10-21) — fireworks-ai | v1.106.4 (2026-10-25) |
| License | proprietary; Python SDK Apache-2.0 | MIT (except enterprise/ directory, commercial license) |
| GitHub | searched not found | BerriAI/litellm — ~62.1k stars, last commit 2026-10 |
| Pricing | Serverless pay-per-token; on-demand GPUs $8/hr (H100/H200), $13/hr (B200), $15/hr (B300); fine-tuning from $0.50 per 1M training tokens (LoRA SFT up to 16B) | OSS free; Enterprise custom pricing (30-day self-hosted trial key) |
| Funding | $77M total raised through Series B 2024-07 ($52M, Sequoia led; $552M valuation). | BerriAI raised $1.6M seed 2023 (Y Combinator W23); commercial steward of LiteLLM OSS. |
| Deployment | searched not found | Self-hosted only — SDK and proxy; Enterprise self-hosted or air-gapped |
| API surface | OpenAI-compatible REST API, Python SDK (fireworks-ai) | Python SDK, OpenAI-compatible proxy REST API |
| Multi-tenancy | searched not found | searched not found |
| MCP | searched not found | yes — MCP Gateway in LiteLLM Proxy (Streamable HTTP, SSE, stdio) with per-key/team access control |
| A2A | searched not found | searched not found |
| OpenTelemetry | searched not found | searched not found |
| Optimised for | searched not found | searched not found |
| Anti-fit | searched not found | searched not found |
Pros & cons
Fireworks AI
Pros: searched not found
Cons: searched not found
LiteLLM
Pros: searched not found
Cons: searched not found