Fireworks AI vs Together AI
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | Fireworks AI | Together AI |
|---|---|---|
| Pricing | Pay-per-token (serverless) / prepaid billing from July 1, 2026 | Freemium (free tier + pay-as-you-go / dedicated plans) |
| Inference Performance | 3x speedups, sub-second latency, 30T+ tokens/day | 31% more TPS than TensorRT-LLM, FlashAttention-4 |
| Model Access | DeepSeek V4, GLM 5.2, Qwen 3.7 Plus, MiniMax M3 (day-0 access) | 100+ open-source models including DeepSeek V4 Pro, Qwen3.7-Max, Llama 4 Maverick |
| Training Capabilities | Full-spectrum: guided, config-led, custom RL; Multi-LoRA | Fine-tuning with research-backed techniques, pre-training on GPU clusters |
| Target Audience | AI product teams, enterprises, startups building coding assistants | Developers, researchers, enterprises scaling from sandbox to AI Factory |
| Key Differentiator | Exclusive early access to frontier models, RL inference scaling | Zero egress storage, CodeSandbox SDK, ISO 27001 certification |
If you need the absolute lowest latency and earliest access to frontier open-weight models for real-time coding assistants, Fireworks AI is the clear winner — especially with its newer models like GLM 5.2 and MiniMax M3. However, if you want a broader model library, a freemium entry point, and enterprise-ready certifications without vendor lock-in, Together AI's zero-egress storage and ISO 27001 compliance make it a safer bet for compliance-heavy teams.
Low-latency inference and full-stack training for open-weight models, powering Cursor and Notion.
Visit WebsiteAI-native cloud for running open-source LLMs at scale—serverless inference, fine-tuning, and GPU clusters.
Visit WebsiteWhat 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
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
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
Who should pick which
- Solo developer building a real-time coding assistantPick: Fireworks AI
Fireworks AI's sub-second latency and 3x speedups are critical for real-time code suggestions, and it offers early access to models like Kimi K2.7 Code optimized for agentic tasks.
- Enterprise with compliance requirementsPick: Together AI
Together AI's ISO 27001:2022 certification and zero egress fees on storage make it suitable for enterprises needing auditable security and data portability.
- AI researcher fine-tuning open-source modelsPick: Together AI
Together AI offers research-backed fine-tuning techniques, FlashAttention-4, and a wide library of 100+ models, providing more flexibility for experiments.
- Startup needing latest models with minimum costPick: Fireworks AI
Fireworks AI provides day-0 access to frontier models like MiniMax M3 at 1/20th the cost of comparable models, and its serverless free tier may be used for prototyping before prepaid billing kicks in.
- Team running batch inference on large corporaPick: Together AI
Together AI supports batch inference with up to 30B tokens per model and managed storage with zero egress fees, making it ideal for processing massive datasets efficiently.
Frequently Asked Questions
Fireworks AI vs Together AI: which should you choose?
If you need the absolute lowest latency and earliest access to frontier open-weight models for real-time coding assistants, Fireworks AI is the clear winner — especially with its newer models like GLM 5.2 and MiniMax M3. However, if you want a broader model library, a freemium entry point, and enterprise-ready certifications without vendor lock-in, Together AI's zero-egress storage and ISO 27001 compliance make it a safer bet for compliance-heavy teams.
Which platform has the lowest latency for real-time applications?
Fireworks AI claims 3x speedups and sub-second latency, ideal for coding assistants. Together AI also offers high throughput (31% more TPS than TensorRT) but Fireworks' focus on latency gives it an edge.
Can I try either platform for free?
Together AI offers a freemium model with a free tier for experimentation. Fireworks AI currently has pay-per-token pricing, but prepaid billing starts July 1, 2026; there is no mention of a free tier.
Do they support fine-tuning?
Yes. Fireworks offers guided, config-led, and custom RL training with Multi-LoRA. Together AI provides fine-tuning with research-backed techniques and pre-training on GPU clusters.
Which platform gives early access to new open-weight models?
Fireworks AI explicitly offers 'exclusive early access to frontier open-weight models' and recently launched GLM 5.2, Qwen 3.7 Plus, and MiniMax M3 on its platform day-zero.
Is either platform ISO 27001 certified?
Yes, Together AI is ISO 27001:2022 certified. Fireworks AI does not mention any similar certification.
What integrations do they support?
Fireworks integrates with OpenAI API, Anthropic API, Azure Foundry, NVIDIA Foundry, PyTorch, GitHub Copilot, Claude Code, etc. Together AI integrates with CodeSandbox, Hugging Face, W&B, LangChain, LlamaIndex, and offers Python/Node.js SDKs.
Can I deploy dedicated GPU instances?
Fireworks offers on-demand dedicated GPU deployments and reserved capacity with guaranteed quotas. Together AI provides dedicated model inference on custom hardware and GPU clusters (GB300, GB200, B200, H200, H100).
Which platform is better for batch processing?
Together AI is specifically built for batch inference up to 30B tokens per model, with managed storage and zero egress fees. Fireworks does not emphasize batch inference as a core feature.
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Last reviewed: May 12, 2026