Fireworks AI vs Together AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-09-30
Cross-checked through our multi-step verification ·
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At a glance

DimensionFireworks AITogether AI
Pricingfreemium · from Serverless Inference Per token (GLM 5.3: $1.4/M input, $4.4/M output; GLM 5.3 Flafreemium · from Serverless Inference Per 1M tokens (from $0.00)
Best forAI product teams where inference latency is a visible feature, such as coding assistants and agents, Enterprises fine-tuning open models on private data and deploying them at scaleProduction coding agents and high-throughput apps running open models like DeepSeek V4 Pro or Kimi K3, Batch jobs processing enormous token volumes — up to 30B tokens per model asynchronously
Standout featuresServerless inference with Standard, Priority, and Fast per-token tiers · OpenAI and Anthropic compatible APIs for drop-in migration · On-demand dedicated GPU deployments: H100, H200, B200, B300, GB300Serverless inference APIs across 100+ open-source models · Batch inference scaling to 30 billion tokens per model · Provisioned Throughput with reserved capacity and a 99% uptime SLA
Viability score86/10088/100
APIYesYes

Fireworks AI is the stronger pick for ai product teams where inference latency is a visible feature, such as coding assistants and agents; Together AI fits better for production coding agents and high-throughput apps running open models like deepseek v4 pro or kimi k3.

Built from live tool data, last verified 2026-09-30.

Fireworks AI
Fireworks AI

Production inference and training for open-weight models, built by the creators of PyTorch.

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Together AI
Together AI

Together AI runs serverless inference on 100+ open-source LLMs plus GPU clusters for training and fine-tuning.

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Pricing
Freemium
Freemium
Plans
Per token (GLM 5.3: $1.4/M input, $4.4/M output; GLM 5.3 Fla
$0.50 - $40 per 1M training tokens
Per token (prefill, cached prefill, sample, train)
$8 - $20 per GPU hour (September 1 rates)
Custom
Per 1M tokens (from $0.00)
Per 1M tokens (batch rates)
Contact sales
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Popularity
3.8k views
3.6k views
Skill Level
Intermediate
Advanced
API Available
Platforms
WebAPICLI
WebAPI
Categories
🖥️ GPU Cloud & Model Inference
🖥️ GPU Cloud & Model Inference
Features
Serverless inference with Standard, Priority, and Fast per-token tiers
OpenAI and Anthropic compatible APIs for drop-in migration
On-demand dedicated GPU deployments: H100, H200, B200, B300, GB300
Reserved capacity with guaranteed quotas and earliest access to new hardware
Guided fine-tuning: describe the task, review plan and cost, approve the run
Config-led training for known models, data, and methods
Custom training with your own loss, trainer, and RL loop
Multi-LoRA serving of several adapters at once
Agent Skills for training workflows
Cached input tokens at 50% off; batch inference at 50% of serverless pricing
Embeddings and reranking models for search and retrieval
Vision, audio, and image models (FLUX.1 Kontext Pro, Whisper V3 Large)
Function calling and structured JSON outputs for agentic workflows
Fireworks Nexus drop-in routing across open and closed models
Elastic RL inference that scales up when production traffic drops
Serverless inference APIs across 100+ open-source models
Batch inference scaling to 30 billion tokens per model
Provisioned Throughput with reserved capacity and a 99% uptime SLA
Dedicated Model Inference on custom GPU hardware
Dedicated Container Inference for video, audio, and image models
Voice Agents for building production voice agents via API
Chat, vision, image, audio, video, transcribe, embeddings, rerank, and moderation endpoints
On-demand NVIDIA B200 GPUs on Together GPU Clusters
GPU clusters with GB300, GB200, H200, and H100
AI Factory custom infrastructure at frontier scale
Fine-tuning with FlashAttention and ATLAS research kernels
Custom training with reinforcement learning support
Evaluations to measure model quality before shipping
Managed Storage with object storage, parallel filesystems, and zero egress fees
Sandbox development environments via the CodeSandbox SDK
Integrations
Azure AI Foundry
Microsoft Foundry
NVIDIA Foundry
PyTorch
LangChain
LiteLLM
Claude Code
MCP
GitHub Copilot
Codex
CodeSandbox
Hugging Face
Weights & Biases
LlamaIndex

What real users say: Fireworks AI vs Together AI

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Fireworks AI

40 mentions across 4 sources · 44% positive — mixed (averaged across 4 sources)

Reddit, Hacker News, Stack Overflow, Lemmy

What users praise

  • • Cheaper than Bedrock for serving Kimi models.
  • • Wide selection of open-weight models like GLM, DeepSeek, Qwen.
  • • Exclusive early access to models like GLM 5.2 and Kimi K2.7 Code.
  • • Strong performance optimization for latency-sensitive workloads.

What frustrates them

  • • Training and fine-tuning require more engineering effort than managed services.
  • • Heavy reliance on Cursor as a major customer raises uncertainty.
  • • Limited community feedback on support quality and reliability.
  • • Prepaid billing transition in 2026 may surprise some users.

Researched Jul 31, 2026

Together AI

75 mentions across 4 sources · 63% positive — mixed (averaged across 4 sources)

Hacker News, Bluesky, Stack Overflow, Lemmy

What users praise

  • • Supports 100+ open-source models with easy API integration.
  • • Offers per-token pricing that is cheaper than Claude Opus by 76%.
  • • Provides 31% more tokens per second than TensorRT-LLM.
  • • Includes free $25 credit for new users to test models.

What frustrates them

  • • Pricing may be VC-subsidized and could increase drastically.
  • • Limited community feedback on support quality and uptime.
  • • No ongoing free tier beyond initial trial credits.
  • • Primarily benefits developers already comfortable with open-weight models.

Researched Jul 6, 2026

Frequently Asked Questions

Which is better, Fireworks AI or Together AI?

The best choice between Fireworks AI and Together AI depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.

What are the main differences between Fireworks AI and Together AI?

The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.

Is there a free version of Fireworks AI or Together AI?

Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.

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Fireworks AI
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Last reviewed: May 12, 2026