Baseten vs Fireworks AI
Same workloads, both price lists, refreshed daily. On shared line items today: Baseten is cheaper on 4 of 19 shared models (input or output price), Fireworks AI on 2.
Baseten
Production inference platform with Truss packaging, optimized serving engines and enterprise-grade autoscaling. Strong for teams shipping custom models with SLAs.
- Optimized model serving (TensorRT-LLM)
- Enterprise autoscaling and observability
Fireworks AI
Speed-focused open-model inference with FireAttention serving stack, function-calling models and image generation. Strong latency SLAs for production apps.
- Very low latency serving
- Function-calling optimized
- Enterprise SLAs
Shared models, priced by both
List prices refreshed 2026-10-08 ยท input $/1M tokens| Model | Baseten in/out | Fireworks AI in/out | Cheaper input |
|---|---|---|---|
| GPT-OSS 120B | $0.100 / $0.500 | $0.150 / $0.600 | Baseten |
| DeepSeek V4 Flash | $0.130 / $0.260 | $0.140 / $0.280 | Baseten |
| GLM 5.3 Flash | $0.150 / $0.500 | $0.150 / $0.500 | tie |
| DeepSeek V4.1 Flash | $0.300 / $1.20 | $0.300 / $1.20 | tie |
| DeepSeek-V3.1 | $0.500 / $1.50 | $0.560 / $1.68 | Baseten |
| GLM-4.7 | $0.600 / $2.20 | $0.600 / $2.20 | tie |
| Kimi K2.5 | $0.600 / $3.00 | $0.600 / $3.00 | tie |
| Kimi K2 Thinking | $0.600 / $2.50 | $0.600 / $2.50 | tie |
| Kimi K2 | $0.600 / $2.50 | $0.600 / $2.50 | tie |
| GLM-4.6 | $0.600 / $2.20 | $0.550 / $2.19 | Fireworks AI |
| DeepSeek V3 | $0.770 / $0.770 | $0.900 / $0.900 | Baseten |
| Kimi K2.6 | $0.950 / $4.00 | $0.950 / $4.00 | tie |
| Kimi K2.7 Code | $0.950 / $4.00 | $0.950 / $4.00 | tie |
| Inkling | $1.00 / $4.05 | $1.00 / $4.05 | tie |
| GLM-5.2 | $1.40 / $4.40 | $1.40 / $4.40 | tie |
| GLM 5.3 | $1.40 / $4.40 | $1.40 / $4.40 | tie |
| DeepSeek V4 Pro | $1.74 / $3.48 | $1.20 / $1.20 | Fireworks AI |
| GLM-5p2-Fast | $2.10 / $6.60 | $2.10 / $6.60 | tie |
| Kimi K3 | $3.00 / $15.00 | $3.00 / $15.00 | tie |
Cheaper-on-count is a tally of listed prices, not a quality verdict: throughput, reliability and quantization differ between providers. Disclosure.