Fireworks AI vs Telnyx: Token Pricing, Speed & Intelligence
Full comparison of Fireworks AI and Telnyx — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
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.
Telnyx
OpenAI-compatible inference API — GLM-5.3, Kimi, DeepSeek, MiniMax
Telnyx Inference API provides OpenAI-compatible access to a curated set of open-weight and frontier models including GLM-5.3 Flash, Kimi K2.6, DeepSeek V4 Flash, and MiniMax-M3. PAYG pricing with no minimum spend. Telnyx is primarily known as a communications platform; the inference API is a newer addition to their product suite.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Fireworks AI
Telnyx
Key differentiators
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.
OpenAI-compatible inference API from a communications platform, with competitive rates on GLM-5.3 Flash and DeepSeek V4 Flash.
Frequently asked questions
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.
Telnyx FAQs
What models does Telnyx Inference API offer?
As of October 2026: GLM-5.3 Flash ($0.135/$0.45 per 1M tokens, cached $0.027), Kimi K2.6 ($0.665/$4.00), DeepSeek V4 Flash ($0.130/$0.260), and MiniMax-M3 ($0.270/$1.100). All are OpenAI-compatible. See telnyx.com/pricing/inference-api for current rates.
Is Telnyx Inference API OpenAI-compatible?
Yes. Telnyx provides an OpenAI-compatible REST API, so you can use it as a drop-in replacement in any application that supports custom base URLs.
Does Telnyx offer prompt caching?
Yes, on GLM-5.3 Flash. Cached input tokens are billed at $0.027/1M vs $0.135/1M standard.
Provider resources
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.
Telnyx — OpenAI-compatible inference API — GLM-5.3, Kimi, DeepSeek, MiniMax
Telnyx Inference API provides OpenAI-compatible access to a curated set of open-weight and frontier models including GLM-5.3 Flash, Kimi K2.6, DeepSeek V4 Flash, and MiniMax-M3. PAYG pricing with no minimum spend. Telnyx is primarily known as a communications platform; the inference API is a newer addition to their product suite.
OpenAI-compatible inference API from a communications platform, with competitive rates on GLM-5.3 Flash and DeepSeek V4 Flash.
Key strengths compared
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
Telnyx
- OpenAI-compatible API — drop-in replacement for existing integrations
- Competitive pricing on GLM-5.3 Flash and DeepSeek V4 Flash
- PAYG with no minimum spend
- Smaller model catalog vs major inference hubs
- Inference is a secondary product — communications is the core business
Key weaknesses compared
Fireworks AI
- Slightly higher pricing than budget alternatives
- Smaller model catalog than Together AI
- Serverless Training is newer and less battle-tested
Telnyx
- Smaller model catalog vs major inference hubs
- Inference is a secondary product — communications is the core business
- Limited benchmark transparency vs dedicated inference providers
Provider category context
Fireworks AI is a inference api, founded in 2022. Telnyx is a inference api, founded in 2009. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Fireworks AI and Telnyx host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.