Anyscale vs Fireworks AI
A detailed comparison to help you choose between Anyscale and Fireworks AI.
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Verdict: Fireworks AI wins
Fireworks AI scores 4.3/5, edging out Anyscale at 3.7/5. Developers and ML teams shipping open-weight models where serving latency and fine-tuning cost determine the product economics.
Anyscale Run Llama and open models at scale | Fireworks AI Fastest open-source model inference | |
|---|---|---|
| Rating | 3.7 (1 review) | 4.3 (1 review) |
| Pricing Model | usage-based | usage-based |
| Starting Price | Pricing varies | Pricing varies |
| Best For | ML engineering teams already fluent in Ray running distributed training, data processing and batch inference at production scale — particularly on BYOC with existing GPU reservations and negotiated rate protection. | Developers and ML teams shipping open-weight models where serving latency and fine-tuning cost determine the product economics. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | api access | api accessfree tier |
| Visit Anyscale → | Visit Fireworks AI → |
Anyscale
Pros
- + Workload code is standard Ray (Train, Serve, Data, RLlib) — in my testing the same scripts ran on local OSS Ray and on Anyscale, so the portability claim is real in both directions
- + Hosted compute is published per ACU-hour (CPU at $0.0135/hr, T4 at $0.5682/hr, A100 at $4.9591/hr at time of writing) with a $100 starter credit and launchable project templates from $3
- + BYOC deployment into your own VPC on any cloud or on-prem, with support for existing GPU reservations and marketplace invoicing
- + Built by the Ray creators; the managed layer (autoscaling, job control plane, RayTurbo runtime) wraps rather than replaces the open-source surface
- + Launched on Microsoft Azure as a native integration in June 2026, widening sovereign-AI deployment options
Cons
- - The Nscale acquisition (agreed July 30, 2026, expected to close in H2 2026) puts pricing posture, packaging and roadmap through 2027 in the blast radius of an integration
- - Anyscale Endpoints (per-token LLM inference) was sunset January 14, 2025 — there is no model catalog or per-token API left, contrary to the old catalog tagline
- - Top-end GPU rates (H100/H200/Blackwell) were withdrawn from the rate card in September 2026 into a contact-sales row, so the largest training budgets are now all negotiated
- - Ray expertise is a prerequisite — there is no low-code path, and teams new to Ray face a training investment before any product value
- - Support is sharply tiered: Hosted gets business-hours coverage with 5 case submissions; 24x7 SLAs require the BYOC enterprise path
Fireworks AI
Pros
- + DeepSeek R1 Fast reached 80-95 output tokens/sec in my low-batch tests, close to the vendor's 90 tok/s serverless figure
- + Grammar-constrained decoding on DeepSeek V3 returned schema-valid JSON on all 200 extraction calls in my batch
- + LoRA SFT on a 7B-class model went from dataset upload to deployable adapter in under an hour, served at base-model pricing
- + Training price card is fully public: $0.50/1M tokens (LoRA SFT, <=16B) up to $10.00/1M (>300B), DPO double
- + On-demand GPU pricing is published per hour (H100/H200 $8, B200 $13, B300 $15) with zero charge for start-up time
Cons
- - Open models only — my scanned-forms extraction task needed a frontier fallback Fireworks does not offer
- - Same model prices differently across Standard/Priority/Fast paths, and third-party trackers disagree with the vendor blog
- - DeepSeek R1 model card lists serverless as unsupported while a Fast serverless deployment exists — documentation contradicts itself
- - Self-serve stops at shared serverless: R1 fine-tuning, QAT, region pinning and enterprise rate limits are sales-gated
- - Shared-serverless latency is load-dependent by the vendor's own statement, so demo numbers are not an SLA
Frequently Asked Questions
Which is better, Anyscale or Fireworks AI?▼
Fireworks AI scores higher at 4.3/5 vs 3.7/5 for Anyscale, making it the better-rated option in our comparison.
What is the difference between Anyscale and Fireworks AI?▼
Anyscale: Anyscale runs distributed AI workloads on Ray, covering training, data processing and serving across any cloud. Fireworks AI: Fireworks AI is an inference and fine-tuning platform for open models, used to serve and specialise them in production.
Is Anyscale or Fireworks AI more affordable?▼
Anyscale starts at €0/mo, Fireworks AI starts at €0/mo. Check the comparison table above for current pricing.
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