Fireworks AI vs Together AI: AI Performance, Scalability, and Cost
AI is moving fast and businesses and developers need robust platforms for AI model deployment, inference and training. Fireworks AI and Together AI are two of the most talked about AI infrastructure providers offering advanced model hosting, GPU-powered inference and cost-effective AI solutions.
This comparison goes deep into both platforms to see which one excels in different areas – whether you’re looking for performance, cost efficiency, scalability, security or developer experience. We’ll break down the pros and cons to help you decide.
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Fireworks AI vs Together AI: Key Points
Here’s a quick rundown of how Fireworks AI and Together AI stack up against each other:
- Fireworks AI is the best for AI inference – It’s faster and more cost-effective for chat models and image generation, making it ideal for startups and developers.
- Together AI is unbeatable for AI training – With 10,000+ GPUs and ultra-fast training speeds, it’s the top choice for enterprises and researchers building large AI systems.
- Fireworks AI saves money on inference, Together AI is better for large-scale compute – Fireworks AI keeps token costs low, while Together AI offers affordable GPU clusters for massive workloads.
Now let’s get into the details.
Performance & Speed
Fireworks AI is all about high-speed inference and efficient AI model execution. They claim 9x faster Retrieval-Augmented Generation (RAG) speeds than Groq so you get super fast response times. And image generation is 6x faster, especially with models like Stable Diffusion XL (SDXL).
The platform also has 1,000 tokens per second throughput with speculative decoding which predicts and preloads likely outputs. Fireworks AI’s FireAttention Kernel further optimizes model serving and is 4x faster than vLLM.
Together AI is focused on training and inference acceleration with powerful hardware and optimized software. They achieve 9x faster training with FlashAttention-3 and ultra-fast InfiniBand networking so you can train large models fast.
For inference, Together AI is 4x faster than vLLM with models like Llama 3 8B. They also have industry-leading GPU clusters with a combined training power of 20 exaFLOPS so it’s perfect for high-performance AI workloads.
For fast inference and model execution, Fireworks AI wins with speculative decoding and highly optimized inference pipelines. But for AI model training and large-scale computing Together AI wins with 9x faster training and many GPU clusters. So it depends on what you are looking for.
Pricing & Cost-Effectiveness
| Category | Fireworks AI Pricing | Together AI Pricing |
|---|---|---|
| Llama 3 8B | $0.20/M tokens | $0.10 – $0.20/M tokens |
| Llama 3 70B | Not listed | $0.54 – $0.90/M tokens |
| Mixtral 8x7B | $0.50/M tokens | Not listed |
| DeepSeek R1 | $3.00/M input, $8.00/M output | $3.00/M input, $7.00/M output |
| Stable Diffusion XL (SDXL) | $0.0039 per 30-step image | $0.001 per 25-step image |
| H100 GPU (on-demand) | $5.80/hour | $3.36/hour |
| H200 GPU (on-demand) | $9.99/hour | $4.99/hour |
| H100 GPU (reserved) | Not listed | Starts at $1.75/hour |
| H200 GPU (reserved) | Not listed | Starts at $2.09/hour |
| Fine-Tuning Costs | $0.50 – $6.00/M tokens | Pricing based on model size & epochs |
Fireworks AI
Fireworks AI is a cost-effective AI inference provider with competitive pricing for serverless models, image generation and GPU rentals. Llama 3.1 8B Instruct is $0.20 per million tokens, and Mixtral 8x7B is $0.50 per million tokens. Stable Diffusion XL (SDXL) is $0.0039 per 30-step image.
On-demand GPU pricing is flexible with H100 GPUs at $5.80 per hour and H200 GPUs at $9.99 per hour. Fireworks AI claims 250% better throughput and 50% lower latency than vLLM on GPUs.
For business, Fireworks AI has two plans: Developer Plan with pay-as-you-go pricing and $1 free credit and Enterprise Plan with custom pricing, unlimited rate limits and dedicated deployments. Spending limits are from $50 to $50,000 per month with a custom tier for large customers.
Together AI
Together AI focuses on high-performance compute at a lower cost than the major cloud providers, especially AWS. Llama 3 8B is $0.10 to $0.20 per million tokens, Llama 3 70B is $0.54 to $0.90 per million tokens. DeepSeek R1 is $3 per million input tokens and $7 per million output tokens, slightly cheaper than Fireworks AI for the same model with similar context lengths.
GPU pricing is where Together AI shines. H100 GPUs are $3.36 per hour and H200 GPUs are $4.99 per hour, much cheaper than Fireworks AI’s on-demand. Together AI also offers dedicated GPU clusters, H100 starting at $1.75 per hour and H200 at $2.09 per hour, a very compelling option for large AI trainings.
Together AI has three plans: Build Plan (pay-as-you-go with $1 free credit), Scale Plan (production scaling with premium support and discounted reserved GPUs) and Enterprise Plan (VPC deployment, continuous model optimization and 99.9% SLA with geo-redundancy).
Which one is cheaper?
For inference pricing, Fireworks AI is cheaper, especially for models like Mixtral 8x7B and Llama 3 8B. Serverless pricing is cheaper and flexible spending limits for individuals and enterprises without compromising quality. But Together AI has more competitive GPU pricing, with H100 and H200 rental at almost half of Fireworks AI’s price. So Together AI is better for large model training and dedicated compute.
For users focusing on efficient AI inference, Fireworks AI has a lower cost per token and competitive serverless pricing. For AI training, Together AI is the better choice with cheaper GPU clusters and a lower hourly rate for dedicated hardware. Your choice depends on your needs— cost-efficient inference or high-performance AI training.
Model Availability & Flexibility
Fireworks AI supports over 100 models including Llama 3, Mixtral, Stable Diffusion and Whisper. It has multiple ways to fine-tune, LoRA-based fine–tuning, supervised learning and self-tuning. You can customize the model as per your needs. Fireworks AI also has disaggregated serving and semantic caching to optimize the inference.
Together AI also supports over 100 open source new models including Llama 3, Mixtral-8x22B, Stable Diffusion XL and Phind Code Llama. It has robust fine-tuning capabilities for custom fine-tuning and private AI model ownership. Together AI also has retrieval-augmented generation (RAG) ready embeddings to make it adaptable for applications that require knowledge retrieval and optimization.
Both have model support, so they are very flexible for AI development. Together AI has an edge in fine-tuning and private model ownership, and Fireworks AI has an edge in inference optimization, so the choice depends on your use case.
Scalability & Deployment
Fireworks AI is built for scalability, generating over 1 trillion tokens per day. Serverless inference allows for 2.5 billion tokens per day, fast and efficient for AI applications. On-demand GPU deployments are 250% faster, great for businesses that need fast and scalable AI inference.
Together AI takes it to the next level, up to 10,000 GPUs for AI training. Enterprise-grade GPU clusters with NVIDIA GB200, H200 and H100 for high-performance computing for large-scale AI workloads. For added reliability, Together AI offers uptime SLAs for businesses that need AI model deployment at scale without disruption.
Fireworks AI is good for inference scalability, but Together AI has more computing, thousands of GPUs for large-scale AI training and enterprise AI workloads. So Together AI is the winner for businesses that need lots of AI training power.
Security & Compliance
Fireworks AI puts security and compliance first. It’s SOC2 Type II and HIPAA compliant so you can trust your enterprise is handling sensitive info. We don’t store model inputs or outputs so you have more privacy. For secure network access, we support Virtual Private Cloud (VPC) and Virtual Private Network (VPN) connectivity so you can drop AI into your infrastructure and maintain full control over security.
Together AI focuses on enterprise-grade security by offering private AI control and custom model ownership so you’re not locked in. You can deploy pre-trained models on your infrastructure and own full control, so data sovereignty and internal security policies are met. Together AI is SOC2 compliant and private cloud deployable so it’s a great choice for enterprises that need high security and control.
While Fireworks AI has good security and compliance, Together AI takes it further with private AI deployments and full model ownership so it’s the better choice for enterprises that prioritize security.
Developer & User Experience
Fireworks AI has a seamless developer experience with fast API deployment via the direct CLI tool. They have team collaboration features for startups and large enterprises so you can manage projects efficiently. And with pay-as-you-go pricing and free credits, you can try AI without committing to high upfront costs.
Together AI has a more tailored experience for advanced users with custom AI consulting and fine-tuning support. They have advanced monitoring tools and optimization features to help you get the most out of your model. For enterprise customers, they have private Slack support so you get direct help and troubleshooting.
Fireworks AI edges out as the better choice for developers with faster API deployment and easier onboarding. Their CLI tool and team collaboration features make it a more convenient choice for developers looking for quick and easy AI integration.
Which one to choose?
Fireworks AI is for businesses and developers looking for a cheap inference engine with fast response times. It’s a cheap way to process large language models and generate AI outputs while maintaining quality. If you are into natural language processing, generative AI or image generation at low costs Fireworks AI is the way to go. The API and deployment tools are user-friendly and make it easy for startups and teams to integrate AI capabilities without the high infrastructure costs.
Together AI on the other hand is for enterprises and researchers who need to train machine learning models and compound AI systems. With thousands of GPUs Together AI is designed for those who need advanced data management and fine-tuning AI systems. It has enterprise-grade security, private AI ownership and vendor lock-in prevention, so it’s a great option for companies that need full control over their AI deployments. The custom fine-tuning support further enhances machine learning capabilities so teams can personalize and optimize their models with expert guidance.
In short, both platforms are good at different things. Fireworks AI is the better option if you are looking for a cheap and fast inference engine, Together AI is for those who need high-performance AI training, enterprise security and advanced machine learning customization. The choice depends on your use case and budget.
