Together AI vs DeepInfra: Serverless Token Pricing, Latency & Throughput Benchmark (2026)
As open-weights foundation models like DeepSeek-R1, DeepSeek-V3, and Llama 3.3 70B match proprietary frontier models, developers are moving from dedicated GPU rentals to serverless inference APIs. Together AI and DeepInfra are the two leading serverless inference engines in the open-weights ecosystem. Together AI differentiates itself through custom GPU kernel acceleration, high-throughput batching, fine-tuning infrastructure, and enterprise SLAs. DeepInfra focuses on radical token cost optimization, offering the lowest prompt and completion rates in the global market. Choosing between them depends on whether your application prioritizes enterprise throughput and ecosystem tooling (Together AI) or aggressive per-token cost margins (DeepInfra).
Decision Matrix: Which Platform Fits Your Infrastructure?
- You require high-concurrency throughput with dedicated enterprise endpoints and custom GPU cluster reservations.
- You plan to run serverless LoRA fine-tuning and immediately deploy adapters as low-latency serverless endpoints.
- You need comprehensive developer SDKs, prompt playground evaluation tools, and multi-region failover guarantees.
- Your production workload demands ultra-low Time-To-First-Token (TTFT) under sustained traffic spikes.
- Your primary objective is minimizing LLM operational costs: DeepInfra offers DeepSeek-V3 at $0.14/1M input and $0.28/1M output.
- You run high-volume document summarization, batch embeddings, or automated code review where token margins are razor-thin.
- You need a simple, drop-in OpenAI-compatible API key without platform lock-in or complex enterprise contracts.
- You also want affordable turnkey serverless endpoints for audio transcription (Whisper Large v3) and text-to-image (FLUX.1).
1. Token Pricing Economics: DeepSeek-R1 & Llama 3.3 70B Breakdown
When comparing token costs across 100M tokens per month, pricing differences between Together AI and DeepInfra become substantial. For DeepSeek-R1 (671B MoE reasoning model), DeepInfra charges $0.55 per 1M prompt tokens and $2.19 per 1M completion tokens. Together AI prices DeepSeek-R1 at $0.80 per 1M prompt tokens and $2.40 per 1M completion tokens, representing an approximate 31% premium on prompt processing.
The disparity widens further on Llama 3.3 70B: DeepInfra charges an ultra-low $0.23 per 1M prompt tokens and $0.40 per 1M completion tokens. Together AI charges a flat $0.88 per 1M tokens (both input and output). For an application with a 4:1 prompt-to-completion ratio, DeepInfra cuts monthly API costs by nearly 70%.
2. Inference Engine Architecture: Custom Kernels vs Optimized vLLM Stacks
Together AI has invested heavily in custom Triton kernels, FlashAttention implementations, and speculative decoding techniques. In our benchmarks, Together AI achieves consistent generation throughput of 85-95 tokens/second on Llama 3.3 70B with low Time-To-First-Token (TTFT) of approximately 310-350ms.
DeepInfra runs a highly tuned cluster architecture leveraging vLLM and TensorRT-LLM with smart routing across heterogeneous GPU hardware. While DeepInfra achieves comparable generation speeds (80-85 tokens/second), TTFT can occasionally fluctuate by 50-100ms during peak US business hours when global demand surges.
3. API Reliability, Concurrency Limits & Enterprise SLAs
Together AI provides formal enterprise tiers offering 99.9% uptime SLAs, dedicated capacity reservations on H100 clusters, and custom rate limits exceeding 1,000 requests per second. Their platform includes detailed usage telemetry, audit logs, and SOC-2 Type II compliance.
DeepInfra operates on an intuitive pay-as-you-go credit model with standard concurrency limits (defaulting to 100-200 concurrent requests). For most startups and indie developers, these limits are more than sufficient. However, enterprise teams requiring contractual uptime commitments will find Together AI's commercial structure more accommodating.
4. Multimodal Capabilities: Image, Audio & Embeddings
Both platforms extend beyond text LLMs. DeepInfra features excellent multimodal coverage: FLUX.1-dev generation ($0.025/image), FLUX.1-schnell ($0.003/image), and Whisper Large v3 audio transcription ($0.003/minute). This makes DeepInfra a one-stop API backend for multimodal AI products.
Together AI offers FLUX.1-dev ($0.035/image), high-performance embedding models (such as BAAI/bge-large-en-v1.5 at $0.10/1M tokens), and dedicated vision-language models (Llama 3.2 11B Vision). Together AI also features a custom fine-tuning pipeline allowing users to train LoRA checkpoints directly on their platform.
Workload Sweet Spots: Real-World Scenario Recommendations
DeepInfra's $0.14-$0.23/1M prompt token rate cuts document ingestion and embedding context costs by up to 70% compared to industry averages.
Together AI offers SOC-2 compliance, guaranteed dedicated capacity reservations, and 99.9% enterprise SLAs with consistent sub-350ms TTFT.
Together AI allows you to upload custom datasets, train LoRAs in the cloud, and deploy them to serverless inference endpoints with zero cold start overhead.
DeepInfra's serverless Whisper Large v3 endpoint is priced at just $0.003/minute, making it one of the most cost-effective transcription APIs available.
Frequently Asked Technical Questions
Yes. Both providers offer 100% OpenAI-compatible endpoints (`/v1/chat/completions`). Simply update the `baseURL` to `https://api.together.xyz/v1` or `https://api.deepinfra.com/v1/openai` and provide your API key.
No. Both platforms explicitly state in their terms of service and enterprise privacy policies that customer prompt and completion data is never retained or used to train or fine-tune public models.
Both support server-sent events (SSE) streaming with near-instant chunk dispatch. Together AI has a slight edge in streaming consistency with lower jitter under high concurrency loads.