Together AI vs Fireworks AI
A detailed comparison to help you choose between Together AI and Fireworks AI.
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Verdict: Fireworks AI wins
Fireworks AI scores 4.3/5, edging out Together AI at 4.1/5. Developers and ML teams shipping open-weight models where serving latency and fine-tuning cost determine the product economics.
Together AI Run open-source AI models in the cloud | Fireworks AI Fastest open-source model inference | |
|---|---|---|
| Rating | 4.1 (1 review) | 4.3 (1 review) |
| Pricing Model | usage-based | usage-based |
| Starting Price | Pricing varies | Pricing varies |
| Best For | Developers and researchers who want to run, compare and fine-tune open-weight models across a wide catalogue with OpenAI-compatible calls and no minimum spend. | 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 accessfree tieropen source | api accessfree tier |
| Visit Together AI → | Visit Fireworks AI → |
Together AI
Pros
- + Switched one pipeline across four serverless models in an afternoon — only the base URL and model string changed
- + Model table publishes context length, cached pricing and quantisation format (NVFP4/FP8/MXFP4) per model
- + Flash-tier pricing ($0.15-$0.30 input) made a 10M-token/day extraction job far cheaper than frontier equivalents
- + Breadth: chat, image, vision, video, audio, embedding, rerank and moderation under one API
- + $800M raise at $8.3B valuation (July 2026) is a strong continuity signal for an infrastructure vendor
Cons
- - No proprietary frontier models; my messy scanned-forms task needed a frontier fallback
- - No published per-model latency figures — you must measure for yourself
- - Fine-tuning pricing (tokens x epochs, per-model rates) takes real digging to budget
- - Experimental and free-tier models sit in the same list as production ones with no quality signal
- - Dedicated GPU cluster options exist but are not as configurable as pure compute providers
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, Together AI or Fireworks AI?▼
Fireworks AI scores higher at 4.3/5 vs 4.1/5 for Together AI, making it the better-rated option in our comparison.
What is the difference between Together AI and Fireworks AI?▼
Together AI: Together AI is a cloud platform for running, fine-tuning and serving open-source AI models, including dedicated GPU clusters. Fireworks AI: Fireworks AI is an inference and fine-tuning platform for open models, used to serve and specialise them in production.
Is Together AI or Fireworks AI more affordable?▼
Together AI starts at €0/mo, Fireworks AI starts at €0/mo. Check the comparison table above for current pricing.
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