Top 5 Together AI Alternatives in 2026

1. 01

   Closed-source LLMs are not in the catalog

   Together AI's strength is open-source models — DeepSeek, Meta Llama, Qwen, Mistral, the OpenAI open-weight line, and a growing list of community fine-tunes. Anthropic Claude, OpenAI's proprietary GPT line, and Google Gemini proprietary tiers are not on the platform. Teams shipping mixed open/closed traffic — which describes most products doing both reasoning-heavy work and cost-sensitive bulk work — still need a second vendor for the closed-source half.

   Source→
2. 02

   Multi-vendor routing is not the wedge

   The product is built around a single-vendor cloud experience — your traffic stays inside Together AI's infrastructure. Gateway-shaped features — per-key budgets spanning multiple upstream providers, real-time fallback to Anthropic when DeepSeek is degraded, mixed-vendor analytics in one dashboard — are not the primary investment. The infrastructure depth is real, but the orchestration layer across vendors is somebody else's problem.

3. 03

   Infra-shaped pricing surfaces

   Beyond serverless per-token there are GPU cluster hourly rates (NVIDIA H100, H200, B200, etc.), fine-tuning custom pricing, dedicated container inference contracts, and a Batch Inference API offering 50% off for non-interactive workloads. This breadth is powerful at scale — Cursor and Decagon use it — but a small team chasing the cheapest token rate spends real time understanding which surface to buy. Choice paralysis is a real cost.

   Source→
4. 04

   Generative image and video aren't the main surface

   Together AI publishes serious research on inference (FlashAttention, ThunderKittens, ATLAS) and supports some image models, but the platform's narrative — research blog posts, customer case studies, kernel team profile — leans heavily LLM-shaped. Generative video, text-to-image, and audio synthesis exist on the platform but are not where the product invests its public storytelling. Teams shipping a Sora-style pipeline read this signal early.

All pricing data captured from public sources on 2026-05-18. Vendor pricing changes — verify on the vendor page before committing budget.

1. #1

   ElliotGate

   Editor's pick

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   Unified gateway covering Anthropic, OpenAI, Google, and open-source models in one API, with multimodal billing under one balance.

   Strengths

   • Closed-source LLMs (Claude, GPT proprietary, Gemini proprietary) and open-source LLMs in one catalog.
   • Multimodal: text + image + video + audio under one balance.
   • OpenAI + Anthropic protocols both native.
   • Per-token rate matches upstream — no infra overhead to amortize.

   Trade-offs

   • Not an inference cloud — no dedicated GPU clusters or fine-tuning offering.
   • Curated catalog — long-tail OSS models on Together may not be on ElliotGate.
   • No research lab — we do not ship FlashAttention.
   Pricing

   Pay-per-use across modalities at upstream rates. No GPU hourly, no fine-tune custom.

   Best for

   Teams shipping products that mix Claude, GPT, Gemini, OSS LLMs, and multimodal generation.
2. #2

   Replicate

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   Run open-source models with a single REST API — strongest on community-published models including image, video, and audio.

   Strengths

   • Very broad community model catalog including image and video.
   • Per-second compute pricing is transparent.

   Trade-offs

   • Cold-start latency for less-trafficked models.
   • No Claude / GPT proprietary — closed-source LLMs not in catalog.
   Pricing

   Per-second compute, varies by hardware.

   Best for

   Teams running community-published open-source models including image and video.
3. #3

   Fireworks AI

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   Production inference platform for open-source LLMs with strong throughput optimization and serverless + dedicated tiers.

   Strengths

   • Competitive throughput on Llama, DeepSeek, and Qwen families.
   • Dedicated endpoints for production SLA.

   Trade-offs

   • Closed-source LLMs not in catalog.
   • Single-vendor cloud — does not aggregate multiple providers.
   Pricing

   Per-token serverless, per-hour dedicated.

   Best for

   Teams running OSS LLMs in production at scale.
4. #4

   OpenRouter

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   Routing-first gateway across 30 selected models / 60+ providers, including Anthropic and OpenAI proprietary tiers.

   Strengths

   • Closed-source LLMs (Claude, GPT proprietary) and OSS in one place.
   • Broadest text/embedding catalog.

   Trade-offs

   • 5.5% platform fee on Pay-as-you-go.
   • Multimodal generation thinner than text.
   Pricing

   Free 50 req/day, Pay-as-you-go +5.5%, Enterprise custom.

   Best for

   Teams who want the widest text-LLM catalog.
5. #5

   Groq

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   LPU-based inference cloud delivering very high tokens/sec on a curated set of OSS LLMs.

   Strengths

   • Industry-leading throughput on supported models.
   • Low TTFT for interactive UX.

   Trade-offs

   • Curated catalog — narrower than Together or Fireworks.
   • Closed-source LLMs not in catalog.
   Pricing

   Per-token, varies by model.

   Best for

   Teams where throughput on supported OSS LLMs is the deciding factor.

# Together AI (before — OpenAI-compatible serverless)
- base_url: https://api.together.xyz/v1
- api_key:  $TOGETHER_API_KEY
- model:    "meta-llama/Llama-3.3-70B-Instruct-Turbo"

# ElliotGate (after — multi-vendor gateway)
+ base_url: https://api.elliotgate.com/v1
+ api_key:  $OMINIGATE_API_KEY
+ model:    "meta-llama/llama-3.3-70b-instruct"   # OSS still works
# Also available with the same key:
+   "anthropic/claude-opus-4.7"
+   "openai/gpt-5.5"
+   "google/gemini-3.1-pro"

Together AI's OSS slugs map directly. Closed-source models that were not on Together become available under the same client.