Tools
Fireworks AI vs Groq
Fireworks AI or Groq? Their plans monthly and yearly, the capabilities their makers state, security and latest updates, side by side — read from the makers' own pages.
In short
- Both: Choice of models, API, Official SDKs, Runs models for you
- Only Fireworks AI states: Command line
Fireworks AI
Fireworks AI hosts, fine-tunes, and serves open models through serverless and dedicated APIs.
Plans
Serverless Inference — Embeddings (up to 150M parameters)
- $0.008 / 1M input tokens
- Per-token pricing
- Zero setup
- No cold starts
- High rate limits
- Postpaid billing
Serverless Inference — Embeddings (150M–350M parameters)
- $0.016 / 1M input tokens
- Per-token pricing
- Zero setup
- No cold starts
- High rate limits
- Postpaid billing
Serverless Inference — Qwen3 8B
- $0.1 / 1M input tokens
- Per-token pricing
- Zero setup
- No cold starts
- High rate limits
- Postpaid billing
Managed Training — Models up to 16B parameters
- $0.50 / 1M training tokens
- $1.00 / 1M training tokens
- $2.00 / 1M training tokens
- Supervised and preference fine-tuning
- Serve fine-tuned models for the same price as base models
Managed Training — Models 16.1B–80B
- $3.00 / 1M training tokens
- $6.00 / 1M training tokens
- $12.00 / 1M training tokens
- Supervised and preference fine-tuning
- Serve fine-tuned models for the same price as base models
Managed Training — Models 80B–300B
- $6.00 / 1M training tokens
- $12.00 / 1M training tokens
- $24.00 / 1M training tokens
- Supervised and preference fine-tuning
- Serve fine-tuned models for the same price as base models
Managed Training — Models over 300B
- $10.00 / 1M training tokens
- $20.00 / 1M training tokens
- $40.00 / 1M training tokens
- Supervised and preference fine-tuning
- Serve fine-tuned models for the same price as base models
Serverless Training API — GLM 5.3
- $4.86 / 1M Prefill
- $0.972 / 1M Cached Prefill
- $12.15 / 1M Sample
- $14.58 / 1M Train
- Shared, always-on trainer pool for LoRA training
- No provisioning or idle cost
- Pay only for tokens prefetched, sampled, and trained
Serverless Training API — Qwen 3.8 27B
- $1.86 / 1M Prefill
- $0.372 / 1M Cached Prefill
- $5.595 / 1M Sample
- $4.103 / 1M Train
- Shared, always-on trainer pool for LoRA training
- No provisioning or idle cost
- Pay only for tokens prefetched, sampled, and trained
Serverless Training API — Kimi K3
- $10.87 / 1M Prefill
- $2.17 / 1M Cached Prefill
- $27.11 / 1M Sample
- $32.55 / 1M Train
- Shared, always-on trainer pool for LoRA training
- No provisioning or idle cost
- Pay only for tokens prefetched, sampled, and trained
Prices checked 2026-09-25 on the maker’s page.
Capabilities
- Command line — “Developers Model Library Docs CLI API Changelog” source
- Choice of models — “Route to the best open or closed model for every task, and cut your AI coding spend 50 to 75%.” source
- API — “Serverless. Pay per token with Priority and Fast options to meet your requirements. OpenAI and Anthropic compatible.” source
- Official SDKs — “The Fireworks Training SDK lets us focus on our research instead of wrestling with infrastructure.” source
- Runs models for you — “Serve the latest open models, or your own trained versions.” source
Security
- SOC 2 Type II — “SOC 2 Type 2” source
- SOC 2 — “SOC 2 Type 2” source
- ISO 27001 — “ISO 27001 Certificate” source
- ISO 42001 — “ISO 42001 Certificate” source
- GDPR — “Compliance SOC 2 Type 2 HIPAA GDPR” source
- HIPAA — “SOC 2 Type 2 HIPAA” source
Latest updates
- Serverless pricing update: DeepSeek V4.1 Flash
Serverless pricing for DeepSeek V4.1 Flash changes; dedicated deployment and Reserved Throughput pricing is unaffected.
- New deployment creation flags: deploymentShape: "default" and acceptShapelessRisk
Create Deployment adds deploymentShape: "default" to pick a validated deployment shape and acceptShapelessRisk to create without a shape.
- Upcoming Serverless deprecation: older DeepSeek, GLM, Muse, and Kimi models
Several older Serverless models will be decommissioned on September 25, 2026; migrate to a recommended replacement before then.
Groq
GroqCloud is an API platform for running language, speech, vision, and agentic AI models with low-latency inference.
Plans
Not read from the maker’s page yet.
Prices checked 2026-09-25 on the maker’s page.
Capabilities
- Choice of models — “Explore all available models on GroqCloud.” source
- API — “Get started with the Groq API” source
- Official SDKs — “import Groq from "groq-sdk";” source
- Runs models for you — “Hosted models are directly accessible through the GroqCloud Models API endpoint using the model IDs mentioned above.” source
Latest updates
- Added MCP Connectors (Beta)
Groq now supports Google Workspace connectors for Gmail, Google Calendar, and Google Drive using Model Context Protocol (MCP).
- Added OpenAI GPT-OSS-Safeguard 20B
This model helps classify text content based on customizable policies.
- Added Prompt Caching Enabled for GPT-OSS 120B
Automatic prompt caching is now live for openai/gpt-oss-120b; cache hits provide 50% cost savings on cached input tokens.