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DigitalOcean Gradient AI vs Fireworks AI: Token Pricing, Speed & Intelligence

Full comparison of DigitalOcean Gradient AI and Fireworks AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.

DigitalOcean Gradient AI

Serverless inference on Gradient AI — Claude, GPT-5, DeepSeek V4, Kimi K2.6, Qwen 3.5, Llama 4

DigitalOcean Gradient AI is the serverless LLM inference platform from DigitalOcean, offering access to frontier and open-weight models including Claude Sonnet 4.6, Claude Haiku 4.5, Claude Opus 4.7, GPT-5.4, GPT-5.4 mini, GPT-5, GPT-4.1, GPT-4o, gpt-oss-120b, gpt-oss-20b, DeepSeek V4 Pro/Flash, Kimi K2.6, GLM-5.1, Qwen 3.5 397B A17B, Llama 4 Maverick, and MiMo V2.5 Pro. Pricing is published at docs.digitalocean.com/products/gradient-ai-platform/details/pricing.

ChatCodingReasoningOpen-sourceCost-efficiencyAgents
Open-weight hostHosts open weights

Fireworks AI

H100/H200/B200/B300/GB300 on-demand — Serverless Training API, Forge 2026 conference

Fireworks AI provides optimised inference for open-weight models with a focus on production reliability and low latency. On-demand GPU compute (H100, H200, B200, B300, GB300) is available alongside serverless inference. The Serverless Training API enables fine-tuning for GLM 5.3, Qwen 3.8 27B, Kimi K3, DeepSeek V4 Flash, and Muse Glimmer 30B without managing GPU infrastructure. Fireworks hosted its inaugural Forge 2026 conference.

ProductionReasoningSpeedOpen-sourceFine-tuning
Open-weight hostHosts open weights

Key metric comparison

Cheapest input ($/1M)

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Cheapest output ($/1M)

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Peak throughput

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Best latency (TTFT)

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Intelligence score

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Context window

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Live token pricing

Strengths and weaknesses

DigitalOcean Gradient AI

Frontier model access: Claude Opus 4.7, GPT-5.4, GPT-5 via serverless inference
Broad catalog: Claude, GPT, DeepSeek V4, Kimi K2.6, Qwen 3.5, Llama 4 Maverick
DigitalOcean's developer-friendly platform and billing
OpenAI-compatible API
Competitive pricing on open-weight models
Resells frontier models — no proprietary models
Pricing may be higher than direct provider APIs for frontier models
Newer inference platform — less mature than dedicated inference providers

Fireworks AI

320+ tokens/sec on Llama 3.3 70B — fast GPU inference
H100/H200/B200/B300/GB300 on-demand GPU access
Serverless Training API for fine-tuning without infrastructure
Production-grade reliability with SLAs
OpenAI-compatible API
Slightly higher pricing than budget alternatives
Smaller model catalog than Together AI
Serverless Training is newer and less battle-tested

Key differentiators

DigitalOcean Gradient AI

DigitalOcean's developer-friendly platform extended to LLM inference — frontier models (Claude, GPT-5) alongside open-weight models (DeepSeek V4, Kimi K2.6, Llama 4) under one billing account.

Fireworks AI

Production-grade reliability with the latest GPU hardware (B300/GB300) and a Serverless Training API — the most complete platform for open-weight model inference and fine-tuning.

Frequently asked questions

DigitalOcean Gradient AI FAQs

What is DigitalOcean Gradient AI?

DigitalOcean Gradient AI is DigitalOcean's serverless LLM inference platform, offering frontier and open-weight models including Claude, GPT-5, DeepSeek V4, Kimi K2.6, and Llama 4 Maverick. See docs.digitalocean.com/products/gradient-ai-platform/details/pricing for current rates.

What models does DigitalOcean Gradient AI offer?

The catalog includes Claude Sonnet 4.6, Claude Haiku 4.5, Claude Opus 4.7, GPT-5.4, GPT-5.4 mini, GPT-5, GPT-4.1, GPT-4o, gpt-oss-120b, gpt-oss-20b, DeepSeek V4 Pro/Flash, Kimi K2.6, GLM-5.1, Qwen 3.5 397B A17B, Llama 4 Maverick, and MiMo V2.5 Pro.

How much does DigitalOcean Gradient AI cost?

As of October 2026: Claude Sonnet 4.6 $3/$15, Claude Haiku 4.5 $1/$5, Claude Opus 4.7 $5/$25, GPT-5.4 $2.50/$15, GPT-5.4 mini $0.75/$4.50, GPT-5 $1.25/$10, GPT-4.1 $2/$8, GPT-4o $2.50/$10. See docs.digitalocean.com/products/gradient-ai-platform/details/pricing for current rates.

Fireworks AI FAQs

What GPU hardware does Fireworks AI offer?

Fireworks AI offers on-demand H100, H200, B200, B300, and GB300 GPU instances for dedicated deployments, alongside their serverless inference API for pay-per-token access.

What is the Fireworks Serverless Training API?

Fireworks AI's Serverless Training API lets you fine-tune open-weight models without managing GPU infrastructure. Upload your training data, run fine-tuning jobs, and deploy the resulting model via their inference API.

What models does Fireworks AI offer?

Fireworks AI hosts Llama 3.3 70B, DeepSeek R1, Mixtral, and other popular open-weight models. They focus on production-ready models with optimised inference rather than the broadest possible catalog.

Provider resources

DigitalOcean Gradient AI — Serverless inference on Gradient AI — Claude, GPT-5, DeepSeek V4, Kimi K2.6, Qwen 3.5, Llama 4

DigitalOcean Gradient AI is the serverless LLM inference platform from DigitalOcean, offering access to frontier and open-weight models including Claude Sonnet 4.6, Claude Haiku 4.5, Claude Opus 4.7, GPT-5.4, GPT-5.4 mini, GPT-5, GPT-4.1, GPT-4o, gpt-oss-120b, gpt-oss-20b, DeepSeek V4 Pro/Flash, Kimi K2.6, GLM-5.1, Qwen 3.5 397B A17B, Llama 4 Maverick, and MiMo V2.5 Pro. Pricing is published at docs.digitalocean.com/products/gradient-ai-platform/details/pricing.

DigitalOcean's developer-friendly platform extended to LLM inference — frontier models (Claude, GPT-5) alongside open-weight models (DeepSeek V4, Kimi K2.6, Llama 4) under one billing account.

Fireworks AI — H100/H200/B200/B300/GB300 on-demand — Serverless Training API, Forge 2026 conference

Fireworks AI provides optimised inference for open-weight models with a focus on production reliability and low latency. On-demand GPU compute (H100, H200, B200, B300, GB300) is available alongside serverless inference. The Serverless Training API enables fine-tuning for GLM 5.3, Qwen 3.8 27B, Kimi K3, DeepSeek V4 Flash, and Muse Glimmer 30B without managing GPU infrastructure. Fireworks hosted its inaugural Forge 2026 conference.

Production-grade reliability with the latest GPU hardware (B300/GB300) and a Serverless Training API — the most complete platform for open-weight model inference and fine-tuning.

Key strengths compared

DigitalOcean Gradient AI

  • Frontier model access: Claude Opus 4.7, GPT-5.4, GPT-5 via serverless inference
  • Broad catalog: Claude, GPT, DeepSeek V4, Kimi K2.6, Qwen 3.5, Llama 4 Maverick
  • DigitalOcean's developer-friendly platform and billing
  • Resells frontier models — no proprietary models
  • Pricing may be higher than direct provider APIs for frontier models

Fireworks AI

  • 320+ tokens/sec on Llama 3.3 70B — fast GPU inference
  • H100/H200/B200/B300/GB300 on-demand GPU access
  • Serverless Training API for fine-tuning without infrastructure
  • Slightly higher pricing than budget alternatives
  • Smaller model catalog than Together AI

Key weaknesses compared

DigitalOcean Gradient AI

  • Resells frontier models — no proprietary models
  • Pricing may be higher than direct provider APIs for frontier models
  • Newer inference platform — less mature than dedicated inference providers

Fireworks AI

  • Slightly higher pricing than budget alternatives
  • Smaller model catalog than Together AI
  • Serverless Training is newer and less battle-tested

Provider category context

DigitalOcean Gradient AI is a cloud, founded in 2012. Fireworks AI is a inference api, founded in 2022. The category difference means these providers serve partially overlapping use cases — compare the model lists and pricing tables above to find the best fit for your specific workload.

How to choose between them

Choose DigitalOcean Gradient AI if you need frontier model access: claude opus 4.7, gpt-5.4, gpt-5 via serverless inference. Choose Fireworks AI if you need 320+ tokens/sec on llama 3.3 70b — fast gpu inference. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.