Best serverless LLM inference API
4 models · updated 2026-07-15
The verdict
Fireworks AI leads — 1 of 4 models rank Fireworks AI the top pick.
Not unanimous: Claude picks Together AI; Gemini picks Together AI; Grok picks Groq.
As of 2026-07-15, ChatGPT, Claude, Gemini and Grok collectively rank Fireworks AI #1 for serverless llm inference api on ModelsAgree by aggregate score. The models' case: Best overall balance of fast, no-cold-start serving, strong open-model coverage, OpenAI-compatible APIs, prompt caching, batch discounts, fine-tuning, and a clean path to. The models' main caveat: Shared serverless latency can still vary, while priority and dedicated tiers materially increase cost. The strongest alternative is Together AI — The broadest production-grade catalog of open-weight models (Llama, DeepSeek, Qwen, Kimi, FLUX) behind one OpenAI-compatible API, with consistently. Not unanimous: Claude picks Together AI; Gemini picks Together AI; Grok picks Groq. Source: https://modelsagree.com/best/best-serverless-llm-inference-api (modelsagree.com, CC BY 4.0).
Combined ranking
- 1GPT #1Claude #2Gemini #2Grok #2
Best overall balance of fast, no-cold-start serving, strong open-model coverage, OpenAI-compatible APIs, prompt caching, batch discounts, fine-tuning, and a clean path to higher-reliability or dedicated capacity; narrowly beats Together for production ergonomics.
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GPT Best overall balance of fast, no-cold-start serving, strong open-model coverage, OpenAI-compatible APIs, prompt caching, batch discounts, fine-tuning, and a clean path to higher-reliability or dedicated capacity; narrowly beats Together for production ergonomics.
Claude Fastest to serve new open models day-one, excellent latency via its custom serving stack, and the best developer surface for production apps — reliable function calling, structured/JSON output, grammar mode, plus SOC 2/HIPAA compliance that matters once a prototype becomes a product; near-tie with Together, edged out only on catalog breadth.
Gemini Engineered for production agent architectures with outstanding support for structured JSON generation, fast tool-calling performance, and custom LoRA hosting.
Grok blazing serverless speed via FireAttention engine, day-0 new model support, strong multimodal/fine-tuning/production features with clean API
Where it falls shortper GPT Shared serverless latency can still vary, while priority and dedicated tiers materially increase cost.
per Claude Smaller model selection than Together or DeepInfra, and pricing sits at a premium over budget hosts — not the pick for cost-driven batch workloads.
per Gemini Curated model list is narrower than Together AI, and pricing is higher compared to budget-focused providers.
per Grok lower per-token pricing to compete better at high volume
- 2GPT #2Claude #1Gemini #1Grok #3
The broadest production-grade catalog of open-weight models (Llama, DeepSeek, Qwen, Kimi, FLUX) behind one OpenAI-compatible API, with consistently strong throughput, high rate limits, and a real growth path from pay-per-token to fine-tuning and dedicated endpoints — the safest default for a practitioner shipping on open models; assumes the typical user wants open-model breadth, not a single frontier model.
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Claude The broadest production-grade catalog of open-weight models (Llama, DeepSeek, Qwen, Kimi, FLUX) behind one OpenAI-compatible API, with consistently strong throughput, high rate limits, and a real growth path from pay-per-token to fine-tuning and dedicated endpoints — the safest default for a practitioner shipping on open models; assumes the typical user wants open-model breadth, not a single frontier model.
Gemini Unmatched breadth in its open-weight model catalog, highly reliable serverless endpoints with OpenAI compatibility, and seamless paths for custom fine-tuning. It serves as the primary benchmark for developer-friendly prototyping.
GPT Near-tie for first with broad, rapidly updated multimodal model coverage, competitive throughput and pricing, automatic cached-input discounts, batch inference, Serverless LoRA, and easy migration to dedicated deployments.
Grok broadest open model catalog (200+), excellent fine-tuning + serverless inference, strong performance and reliability for production scale
Where it falls shortper GPT Its very broad catalog has uneven model-specific performance, so serious workloads require benchmarking rather than trusting platform-wide speed claims.
per Claude Neither the cheapest per token (DeepInfra undercuts it) nor the fastest (Groq/Cerebras beat it on latency), so pure cost- or speed-maximizers should look elsewhere.
per Gemini Higher Time to First Token (TTFT) latency compared to hardware-optimized competitors like Groq, and scaling custom models requires expensive dedicated endpoints.
per Grok simplify billing and reduce complexity for easier high-volume use
- 3GPT #3Claude #3Gemini #4Grok #1
unmatched ultra-low latency and highest tokens/sec (500-1000+ tps on LPUs) with no cold starts for real-time apps like agents/voice
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Grok unmatched ultra-low latency and highest tokens/sec (500-1000+ tps on LPUs) with no cold starts for real-time apps like agents/voice
GPT Exceptional token-generation speed and low latency on supported models, straightforward OpenAI-compatible integration, competitive token pricing, and discounted batch processing make it the strongest choice for latency-sensitive interactive applications.
Claude LPU hardware delivers hundreds of tokens/sec at low per-token prices, making it the clear winner for latency-critical UX (voice agents, real-time chat, agent loops) where time-to-final-token dominates the experience.
Gemini Delivers unmatched, class-leading inference speeds and sub-second Time to First Token (TTFT) using custom LPU hardware, making it essential for conversational voice applications.
Where it falls shortper GPT The curated model catalog and hardware-specific support are substantially narrower than Fireworks or Together, limiting model choice and customization.
per Claude A narrow, slow-moving model menu with no custom-model or fine-tuned deployment support, plus capacity/rate-limit constraints at scale — unusable if your model isn't on their list.
per Gemini High rate limits and restricted context windows make it unsuitable for high-volume document processing or long-context RAG applications.
per Grok dramatically expand model catalog beyond narrow selection of optimized models
- 4GPT #4Claude #4Gemini #3Grok #4
The value champion offering the lowest pricing for standard open-weights models (like Llama and Qwen) while maintaining excellent throughput. Near-tied with Fireworks AI on speed metrics, but ranked lower due to fewer developer features.
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Gemini The value champion offering the lowest pricing for standard open-weights models (like Llama and Qwen) while maintaining excellent throughput. Near-tied with Fireworks AI on speed metrics, but ranked lower due to fewer developer features.
GPT Excellent price-to-performance, broad open-model selection, simple pay-as-you-go OpenAI-compatible APIs, embeddings and rerankers, and low operational friction make it especially compelling for cost-conscious applications.
Claude Consistently the lowest per-token prices on a wide open-model catalog with a no-friction OpenAI-compatible API — the best value pick for cost-sensitive, high-volume workloads like batch processing, embeddings, and classification.
Grok best cost-efficiency with low per-token rates, reliable serverless scaling, solid model selection for budget-conscious production workloads
Where it falls shortper GPT It offers fewer production-control, capacity-guarantee, and enterprise deployment options than the top two.
per Claude Latency and throughput are less consistent than Fireworks/Together and the enterprise feature set (compliance, SLAs, dedicated capacity options) is thinner — not for latency-sensitive production frontends.
per Gemini Lacks advanced agentic tooling, structured output optimizations, or robust fine-tuning options, making it unsuitable for highly customized agent pipelines.
per Grok improve raw speed and TTFT to match leaders for latency-sensitive use cases
- 5GPT —Claude #5Gemini —Grok —
True serverless pay-per-token access to frontier commercial models (Claude, plus Meta/Mistral/Amazon models) with IAM, VPC endpoints, guardrails, and compliance baked in — the practical choice when the practitioner sits inside an AWS-governed enterprise; ranked on the assumption that "serverless inference" includes managed frontier-model APIs, not just open-weight hosts.
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Claude True serverless pay-per-token access to frontier commercial models (Claude, plus Meta/Mistral/Amazon models) with IAM, VPC endpoints, guardrails, and compliance baked in — the practical choice when the practitioner sits inside an AWS-governed enterprise; ranked on the assumption that "serverless inference" includes managed frontier-model APIs, not just open-weight hosts.
Where it falls shortper Claude Higher prices, laggy availability of new models, and AWS-grade configuration overhead — painful for indie developers who just want an API key.
- 6GPT #5Claude —Gemini —Grok —
Class-leading inference speed and very high throughput can transform coding agents, search, and other sequential workloads where each generation blocks the next; it is a near-tie with Groq when raw latency dominates.
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GPT Class-leading inference speed and very high throughput can transform coding agents, search, and other sequential workloads where each generation blocks the next; it is a near-tie with Groq when raw latency dominates.
Where it falls shortper GPT Its relatively small supported-model catalog makes it unsuitable when breadth, custom models, or multimodal coverage matters more than speed.
- 7GPT —Claude —Gemini #5Grok —
Highly practical proxy aggregator that simplifies developer workflows by providing unified billing, automatic fallback routing, and access to dozens of underlying serverless providers via a single API key.
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Gemini Highly practical proxy aggregator that simplifies developer workflows by providing unified billing, automatic fallback routing, and access to dozens of underlying serverless providers via a single API key.
Where it falls shortper Gemini Adds an extra network hop of latency and does not allow native developer integration with provider-specific custom model endpoints.
- 8GPT —Claude —Gemini —Grok #5
superior price-to-performance with 2x+ faster inference and lower latency than many peers, strong all-in-one serverless for open models
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Grok superior price-to-performance with 2x+ faster inference and lower latency than many peers, strong all-in-one serverless for open models
Where it falls shortper Grok enhance global availability and enterprise compliance features
Rank history
Just missed the top 5
GPT Cloudflare Workers AI — excellent edge integration and developer value, but weaker model breadth and inference specialization than the leaders · Baseten — strong production platform for custom-model deployment, but less compelling for practitioners seeking a broad, inexpensive shared serverless model catalog
Claude Cerebras — record-setting tokens/sec that beats even Groq, but the model catalog and available capacity are too thin to serve as a primary provider
Gemini Nebius AI — offers excellent GPU infrastructure and very competitive pricing, but has a smaller track record in serverless model offerings compared to the established giants · Cloudflare Workers AI — highly convenient for developers embedded in the Cloudflare edge ecosystem, but limited by a very restrictive model selection and low rate-limit ceilings
Grok Modal — great Python-native serverless GPUs but requires more custom code/setup than pure APIs · Replicate — easy for open models but less optimized speed/cost at scale
By model
ChatGPT
- 1.Fireworks AI
- 2.Together AI
- 3.Groq
- 4.DeepInfra
- 5.Cerebras
Claude
- 1.Together AI
- 2.Fireworks AI
- 3.Groq
- 4.DeepInfra
- 5.Amazon Bedrock
Gemini
- 1.Together AI
- 2.Fireworks AI
- 3.DeepInfra
- 4.Groq
- 5.OpenRouter
Grok
- 1.Groq
- 2.Fireworks AI
- 3.Together AI
- 4.DeepInfra
- 5.SiliconFlow
Common questions
What is the best serverless llm inference api according to AI models?
Fireworks AI leads. 1 of 4 models rank Fireworks AI the top pick. The current top 3: Fireworks AI, Together AI, Groq. Ranked by asking ChatGPT, Claude, Gemini, Grok the same buying question and merging their top-5 picks, updated 2026-07-15. Source: modelsagree.com.
Which serverless llm inference api did each AI model pick first?
ChatGPT: Fireworks AI. Claude: Together AI. Gemini: Together AI. Grok: Groq.
Do the AI models agree on the best serverless llm inference api?
Not unanimous. Claude picks Together AI; Gemini picks Together AI; Grok picks Groq.
What changed in the latest serverless llm inference api ranking?
In the latest poll (2026-07-15): Amazon Bedrock climbed 4 spots, Cerebras climbed 2 spots; OpenRouter dropped 1 spot; SiliconFlow entered the ranking. The models are re-polled on demand, so this ranking moves.
How is this serverless llm inference api ranking made?
ChatGPT, Claude, Gemini, Grok are each asked the same buying question in a fresh session with no system steering. Their top-5 answers are merged (rank 1 = 5 pts … rank 5 = 1 pt) into the consensus ranking, re-polled on demand and tracked over time.
More on how polling works: full methodology →
Cite this ranking
ModelsAgree, “Best serverless LLM inference API” — merged ranking from ChatGPT, Claude, Gemini & Grok, polled 2026-07-15. https://modelsagree.com/best/best-serverless-llm-inference-api (CC BY 4.0)
Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled on demand