Fireworks AI vs Together AI
Fireworks AI vs Together AI: side-by-side comparison of two inference platforms & gateways systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| Fireworks AI | Together AI | |
|---|---|---|
| Cost tier | searched not found | mid |
| $/Mtok input | searched not found | — |
| $/Mtok output | searched not found | — |
Where they differ (7)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Fireworks AI | Together AI | |
|---|---|---|
| Cost tier | searched not found | mid |
| Type | Fast OSS LLM inference cloud | Inference + fine-tuning cloud |
| Latest release | v1.2.30 (2026-10-21) — fireworks-ai | v3.0.0 (2026-10-22) — together (Python SDK) |
| 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) | Serverless pay-per-token (e.g. $0.15–$3.00 per 1M input tokens); dedicated endpoints per GPU-hour (H100 $5.49/hr); fine-tuning per 1M training tokens; GPU clusters from $3.19–$3.99 per H100-hour |
| Funding | $77M total raised through Series B 2024-07 ($52M, Sequoia led; $552M valuation). | $800M Series C 2026-07-01 (Aramco Ventures, NVIDIA, Vista Equity, General Catalyst, Salesforce Ventures and others); earlier rounds: $20M seed, $102.5M Series A, $305M Series B at $3.3B valuation |
| Deployment | searched not found | Managed-only — serverless and dedicated inference, fine-tuning, GPU clusters |
| API surface | OpenAI-compatible REST API, Python SDK (fireworks-ai) | searched not found |
At a glance
| Fireworks AI | Together AI | |
|---|---|---|
| Section | Inference platforms & gateways | Inference platforms & gateways |
| Tier | T1 | T1 |
| Type | Fast OSS LLM inference cloud | Inference + fine-tuning cloud |
| Created | 2022 | 2022 |
| Latest release | v1.2.30 (2026-10-21) — fireworks-ai | v3.0.0 (2026-10-22) — together (Python SDK) |
| License | proprietary; Python SDK Apache-2.0 | proprietary; Python SDK Apache-2.0 |
| GitHub | searched not found | searched not found |
| 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) | Serverless pay-per-token (e.g. $0.15–$3.00 per 1M input tokens); dedicated endpoints per GPU-hour (H100 $5.49/hr); fine-tuning per 1M training tokens; GPU clusters from $3.19–$3.99 per H100-hour |
| Funding | $77M total raised through Series B 2024-07 ($52M, Sequoia led; $552M valuation). | $800M Series C 2026-07-01 (Aramco Ventures, NVIDIA, Vista Equity, General Catalyst, Salesforce Ventures and others); earlier rounds: $20M seed, $102.5M Series A, $305M Series B at $3.3B valuation |
| Deployment | searched not found | Managed-only — serverless and dedicated inference, fine-tuning, GPU clusters |
| API surface | OpenAI-compatible REST API, Python SDK (fireworks-ai) | searched not found |
| Multi-tenancy | searched not found | searched not found |
| MCP | searched not found | searched not found |
| 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
Together AI
Pros: searched not found
Cons: searched not found