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Compare GPU and LLM inference API pricing between Fireworks AI and IO.NET. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Fireworks AI Price | IO.NET Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 PCIE 40GB VRAM • IO.NET | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • IO.NET | Not Available | 2x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • IO.NET | Not Available | 4x GPU | — | |
A30 24GB VRAM • | ||||
A40 48GB VRAM • IO.NET | Not Available | — | ||
A40 48GB VRAM • | ||||
Gaudi 2 96GB VRAM • IO.NET | Not Available | 8x GPU | — | |
Gaudi 2 96GB VRAM • | ||||
H100 SXM 80GB VRAM • IO.NET | Not Available | 4x GPU | — | |
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • IO.NET | Not Available | — | ||
H200 141GB VRAM • | ||||
L4 24GB VRAM • IO.NET | Not Available | 8x GPU | — | |
L4 24GB VRAM • | ||||
L40 40GB VRAM • IO.NET | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • IO.NET | Not Available | 4x GPU | — | |
L40S 48GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • IO.NET | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX A6000 48GB VRAM • IO.NET | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • IO.NET | Not Available | 4x GPU | — | |
RTX PRO 6000 96GB VRAM • | ||||
Tesla T4 16GB VRAM • IO.NET | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • IO.NET | Not Available | 8x GPU | — | |
Tesla V100 32GB VRAM • | ||||
A100 PCIE 40GB VRAM • IO.NET | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • IO.NET | Not Available | 2x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • IO.NET | Not Available | 4x GPU | — | |
A30 24GB VRAM • | ||||
A40 48GB VRAM • IO.NET | Not Available | — | ||
A40 48GB VRAM • | ||||
Gaudi 2 96GB VRAM • IO.NET | Not Available | 8x GPU | — | |
Gaudi 2 96GB VRAM • | ||||
H100 SXM 80GB VRAM • IO.NET | Not Available | 4x GPU | — | |
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • IO.NET | Not Available | — | ||
H200 141GB VRAM • | ||||
L4 24GB VRAM • IO.NET | Not Available | 8x GPU | — | |
L4 24GB VRAM • | ||||
L40 40GB VRAM • IO.NET | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • IO.NET | Not Available | 4x GPU | — | |
L40S 48GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • IO.NET | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX A6000 48GB VRAM • IO.NET | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • IO.NET | Not Available | 4x GPU | — | |
RTX PRO 6000 96GB VRAM • | ||||
Tesla T4 16GB VRAM • IO.NET | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • IO.NET | Not Available | 8x GPU | — | |
Tesla V100 32GB VRAM • | ||||
| Model ↑ | Fireworks AI | IO.NET | Input Diff ↕ |
|---|---|---|---|
DeepSeek | Not available | $0.568 in $2.28 out | — |
DeepSeek | Not available | $1.49 in $2.66 out | — |
DeepSeek | $0.220 in $0.660 out | $0.199 in $0.512 out | $0.021 |
DeepSeek | $0.220 in $0.660 out | Not available | — |
DeepSeek | $1.32 in $3.96 out | $1.75 in $3.49 out | $0.426 |
Google | Not available | $0.106 in $0.368 out | — |
Zhipu | Not available | $0.063 in $0.400 out | — |
Zhipu | Not available | $0.157 in $0.937 out | — |
Zhipu | Not available | $0.536 in $2.07 out | — |
Zhipu | Not available | $0.880 in $2.37 out | — |
Zhipu | Not available | $0.860 in $2.78 out | — |
Zhipu | Not available | $1.39 in $4.36 out | — |
Zhipu | $1.40 in $4.40 out | $1.58 in $4.97 out | $0.180 |
Z AI | $1.40 in $4.40 out | $1.36 in $4.40 out | $0.040 |
Z AI | $0.150 in $0.500 out | $0.150 in $0.500 out | $0.0000 |
Explore how these providers compare to other popular GPU cloud services
Compare Fireworks AI with another leading provider
Compare Fireworks AI with another leading provider
Compare Fireworks AI with another leading provider
Compare Fireworks AI with another leading provider
Compare Fireworks AI with another leading provider
Compare Fireworks AI with another leading provider
Text, vision, audio, image, and embedding models, including recent releases such as Kimi K3, GLM 5.2, DeepSeek V4, MiniMax M3, and Qwen3.7 Plus
Industry-leading throughput and latency with fast inference engine
SFT, DPO, and reinforcement fine-tuning of models up to 1T+ parameters, from guided runs through writing your own trainer and RL loop
Drop-in replacement for closed-model APIs - change the base URL to migrate, with the same SFT data format for fine-tuning
H100, H200, B200, B300, and GB300 deployments with per-second billing and autoscaling
Async bulk inference jobs run at scale for less than standard serverless requests
Access to 300,000+ verified GPUs from 139 countries with 6,000+ cluster-ready GPUs
Deploy clusters in under 90 seconds with auto-scaling capabilities
Choose from containers, Ray clusters, or bare metal based on workload needs
Uses the same distributed computing framework that OpenAI used to train GPT-3
AI models, smart agents, and API integration for workflow automation
Kernel-level VPN with secure mesh protocols for data protection
On-demand GPU clusters for AI/ML workloads with multiple deployment options
AI models, smart agents, and API integration platform
Decentralized pool of GPU providers with unified APIs and competitive pricing.
Pay-per-token pricing across Standard, Priority, and Fast serverless tiers with postpaid billing and no cold starts
Cached input tokens billed at a reduced rate on supported models
Async bulk inference billed at a discount to standard serverless requests
Embedding models billed per 1M input tokens, tiered by model parameter count
Supervised and preference fine tuning billed per 1M training tokens with LoRA or full-parameter options; reinforcement fine tuning billed per GPU hour
Shared always-on trainer pool for LoRA training with no provisioning or idle cost, billed per token prefilled, sampled, and trained
Per-second billing for H100, H200, B200, B300, and GB300 GPU deployments with no start-up charges; region-restricted deployments in the US or Europe are priced at 1.25x the standard rate
Guaranteed capacity with higher rate limits and earliest access to new hardware, arranged through sales
Most cost-effective option for distributed ML workloads using Ray framework
Standard containerized deployments with Docker support
Premium pricing for direct hardware access and maximum performance
Dynamic pricing based on actual resource usage with automatic scaling
Browse 100+ models at fireworks.ai/models
Experiment with prompts interactively without coding
Create an API key from user settings in your account
Use OpenAI-compatible endpoints or Fireworks SDK
Transition to on-demand GPU deployments for production workloads
Create an account on the IO.NET platform with no complex KYC requirements
Purchase $IO tokens for compute payments or add other supported payment methods
Select from containers, Ray clusters, or bare metal based on your workload
Specify GPU requirements, region preferences, and scaling options
Launch your cluster in under 90 seconds and start your AI/ML workloads
18+ global regions across 8 cloud providers with multi-region deployments and BYOC support for enterprise
Documentation, Discord community, status page, email support, and dedicated enterprise support with SLAs
Global distributed network across 139 countries with intelligent geographic clustering and latency optimization
Documentation portal, Discord community (500,000+ members), Telegram support, and direct engineering support for GPU and driver questions