LLM API Provider Comparison 2026

Provider Overview (by Benchmark Speed)

Sorted by best measured throughput. Click any provider for full model listings and detailed benchmark history.

Provider	Models Benchmarked	Best Tok/s	Median Tok/s	Best Model	Strength
cerebras	2	129	105	Gemma 4 31B	General purpose
bedrock	32	115	54	Nova Micro 1.0	Enterprise compliance
openai	30	111	27	o3 Mini	Frontier quality, ecosystem
groq	6	93	65	Llama 3.3 70B Instruct	Speed, low latency
mara	3	86	72	gpt-oss-120b	General purpose
friendli	5	83	40	Gemma 4 31B	General purpose
modelrun	3	78	24	Gemma 4 31B	General purpose
parasail	21	76	24	Qwen3 Next 80B A3B Instruct	General purpose
coreweave	15	75	21	Llama 3.1 8B Instruct	General purpose
google	3	75	2	Gemini 2.5 Flash Lite	General purpose
sambanovaturbo	1	73	73	Llama 3.3 70B Instruct	General purpose
baseten	6	68	32	Kimi K2.7 Code	General purpose
mistral	2	65	49	GLM 5.2	European, GDPR
nebius	5	54	14	gpt-oss-120b	General purpose
crusoe	6	53	29	Llama 3.3 70B Instruct	General purpose

Provider Profiles

OpenAI

The market leader for frontier models. GPT-5, GPT-5 Nano, o3, and o1 series lead reasoning, coding, and general capability benchmarks. Best ecosystem support and widest third-party integrations.

Best for: Frontier model quality, reasoning tasks, coding assistants, and applications where API reliability and ecosystem maturity matter most.

Watch out for: Direct OpenAI API throughput is lower than inference-optimized providers. Premium pricing on frontier models.

Claude 3 and Claude 4 models excel at instruction-following, long-context analysis, and safe output. Strong performer for document processing, multi-turn dialogue, and tasks requiring precise adherence to complex instructions.

Best for: Long-context analysis, instruction-following, regulated industries where output safety matters, and applications needing reliable structured output.

Watch out for: Smaller model catalog than OpenAI. API throughput is moderate.

Groq

Purpose-built inference hardware (LPUs) delivers category-leading throughput on open-weight models. Llama 3.3 70B and Qwen 3-32B regularly top speed benchmarks at 150+ tok/s with near-zero TTFT.

Best for: Real-time applications, voice interfaces, gaming, and any workload where sub-second streaming response start matters more than frontier model quality.

Watch out for: Limited to open-weight models. No GPT-4 or Claude. Rate limits can be tight on free tier.

AWS Bedrock

Aggregates models from Anthropic, Meta, Mistral, Amazon Nova, and others under one AWS-native API. Nova Micro (~118 tok/s) is the fastest Bedrock model. Strong compliance story: SOC2, HIPAA, FedRAMP.

Best for: Enterprise teams already on AWS. VPC-native deployments. HIPAA/FedRAMP compliance requirements. Data residency control.

Watch out for: API overhead adds latency vs direct provider calls. More complex IAM setup.

DeepInfra

One of the fastest open-weight inference providers, particularly on smaller models. Qwen 3.5-2B at ~203 tok/s and multiple 100+ tok/s options. OpenAI-compatible API.

Best for: High-volume, cost-sensitive workloads on open-weight models. Speed-critical applications where proprietary models are not required.

Watch out for: Less brand recognition than major providers. SLA / support coverage less mature than Groq or Fireworks.

Key Insights

OpenAI and Anthropic lead on model quality and capability breadth; inference-optimized providers (Groq, DeepInfra, Fireworks) lead on raw speed.
AWS Bedrock and Azure OpenAI suit enterprise teams with existing cloud agreements, compliance requirements, or VPC-native data residency needs.
Google Vertex AI integrates natively with Gemini models and GCP infrastructure — the strongest choice if you're already on Google Cloud.
Together AI and Fireworks offer the widest selection of open-weight models (Llama, Mistral, Qwen, DeepSeek) at competitive prices.
No single provider wins across all dimensions: speed, quality, price, compliance, and model variety all trade off differently.

Frequently Asked Questions

Which LLM API provider is best in 2026?

It depends on your use case. OpenAI and Anthropic lead on frontier model quality. Groq and DeepInfra lead on throughput. AWS Bedrock and Azure lead on enterprise compliance. Use the comparison table above to match your priorities.

OpenAI vs Anthropic — which is better?

OpenAI offers more models and the widest ecosystem integration. Anthropic's Claude models benchmark strongly on reasoning, instruction-following, and safety. For coding tasks, both are strong; for long-context analysis, Claude 3 Opus and GPT-4 are comparable.

Which provider has the most models?

Together AI and Fireworks host the widest range of open-weight models. OpenAI has the largest selection of proprietary frontier models. AWS Bedrock aggregates multiple providers under one API.

Which LLM API is cheapest?

Pricing changes frequently. Groq and DeepInfra often offer the lowest per-token cost for open-weight models. For OpenAI-compatible APIs, Together AI and Fireworks are typically cheaper than OpenAI direct. Always check current pricing pages as this data is not tracked in these benchmarks.

Can I switch providers without changing my code?

Most providers expose an OpenAI-compatible API endpoint. If you use the OpenAI SDK and point BASE_URL at another provider, most requests will work without code changes — though tool use, vision, and structured output support vary.