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Inference APIOpen Weights

OpenRouter

One API for every major LLM — 300+ models, route to the cheapest or fastest provider automatically

OpenRouter is a unified LLM API that routes requests to the cheapest or fastest available provider for any given model. With a single API key you can access GPT-5.6 Sol, Claude 5, Llama 4, Gemini 3.x, DeepSeek V4 Pro, and 300+ other models, with automatic fallback and cost optimisation. The catalog has grown significantly in 2026 with the addition of Chinese frontier models.

A unified API for accessing major LLMs — including Chinese frontier models — with a single key and automatic routing to the cheapest or fastest available provider.

Cost optimisationPrototyping
OpenRouter Models
22
OpenRouter Cheapest Input
$0.03
per 1M tokens
OpenRouter Max Throughput
270 t/s
OpenRouter Min Latency
290ms
TTFT p50
OpenRouter Best Intelligence
90/100
OpenRouter Vision Models
5
OpenRouter Strengths
  • Single API for 300+ models across all major providers
  • Automatic routing to cheapest or fastest provider
  • Fallback and load balancing built in
  • OpenAI-compatible API
  • Free tier with rate-limited access to many models
  • Access to Chinese frontier models (Kimi, GLM, MiniMax, Qwen)
OpenRouter Weaknesses
  • Adds a small latency overhead vs direct provider APIs
  • Pricing is slightly above direct provider rates (routing fee)
  • Less control over which specific provider handles your request
OpenRouter Model Tiers
frontier
6
advanced
6
efficient
6
budget
4
OpenRouter Capabilities
Vision5
Tool Use21
Reasoning5
Open Weights17
Multilingual0
RAG / Search0
Structured Out0
Embeddings0
OpenRouter Intelligence vs Pricelog scale
frontieradvancedefficientbudget
OpenRouter Throughput (tokens/sec)
OpenRouter Input vs Output Pricing ($/1M tokens)
InputOutput
OpenRouter Context Window (tokens)
OpenRouter Best Model by Use Case
chat
qwen3.8-2.4t-a95b
frontier$2.00/1M in
vision
gemini-2.5-pro
frontier$1.25/1M in
coding
qwen3.8-2.4t-a95b
frontier$2.00/1M in
cost
qwen3.7-flash
budget$0.03/1M in
reasoning
qwen3.8-2.4t-a95b
frontier$2.00/1M in
speed
qwen3.8-flash
budget$0.15/1M in

OpenRouter Models

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ModelModalityTierPriceCached /1MTTFTThroughputContextIntel.Caps
qwen3.7-flash
Qwen3.7
Chatbudget
$0.03/ $0.13
in / out per 1M
EST Oct 2026
———1.0M
70
qwen3.8-27b
Qwen3.8
Chatefficient
$0.04/ $2.20
in / out per 1M
EST Oct 2026
———1.0M
76
qwen3.6-35b-a3b
Qwen3.6
Chatefficient
$0.05/ $0.70
in / out per 1M
EST Oct 2026
———262K
80
qwen3.5-flash
Qwen3.5
Chatbudget
$0.07/ $0.26
in / out per 1M
EST Oct 2026
———1.0M
72
qwen3.5-35b-a3b
Qwen3.5
Chatefficient
$0.07/ $0.75
in / out per 1M
EST Oct 2026
———262K
78
qwen3.5-9b
Qwen3.5
Chatbudget
$0.08/ $0.13
in / out per 1M
EST Oct 2026
———262K
68
qwen3-235b-a22b-instruct-2507
Qwen3
Chatadvanced
$0.09/ $0.35
in / out per 1M
EST Oct 2026
———262K
83
llama-3.3-70b-instruct
Llama 3.3
Chatefficient
$0.12/ $0.30
in / out per 1M
EST Jul 2026
—290ms270 t/s131K
64
qwen3-coder-next
Qwen3 Coder
Chatefficient
$0.12/ $0.80
in / out per 1M
EST Oct 2026
———262K
80
qwen3-235b-a22b
Qwen3
Chatadvanced
$0.14/ $0.60
in / out per 1M
EST Jul 2026
—1.1s65 t/s131K
83
qwen3.8-flash
Qwen3.8
Chatbudget
$0.15/ $0.47
in / out per 1M
EST Oct 2026
———1.0M
72
qwen3-vl-235b-a22b-instruct
Qwen3 VL
Chatadvanced
$0.20/ $0.88
in / out per 1M
EST Oct 2026
———262K
82
qwen3.7-plus
Qwen3.7
Chatefficient
$0.32/ $1.28
in / out per 1M
EST Oct 2026
———1.0M
82
qwen3.5-397b-a17b
Qwen3.5
Chatadvanced
$0.39/ $2.34
in / out per 1M
EST Oct 2026
———262K
88
deepseek-r1
DeepSeek R1
Chatadvanced
$0.55/ $2.19
in / out per 1M
EST Jul 2026
—920ms75 t/s164K
85
kimi-k2
Kimi K2
Chatadvanced
$0.60/ $2.50
in / out per 1M
EST Jul 2026
—800ms90 t/s131K
80
gemini-2.5-pro
Gemini 2.5
Chatfrontier
$1.25/ $10.00
in / out per 1M
EST Jul 2026
—920ms88 t/s1.0M
87
qwen3.8-max-0902
Qwen3.8
Chatfrontier
$2.00/ $6.00
in / out per 1M
EST Oct 2026
———1.0M
88
qwen3.8-2.4t-a95b
Qwen3.8
Chatfrontier
$2.00/ $6.00
in / out per 1M
EST Oct 2026
———1.1M
90
gpt-4o
GPT-4o
Chatfrontier
$2.50/ $10.00
in / out per 1M
EST Jul 2026
—540ms105 t/s128K
78
claude-3.5-sonnet
Claude 3.5
Chatfrontier
$3.00/ $15.00
in / out per 1M
EST Jul 2026
—600ms95 t/s200K
82
grok-4
Grok 4
Chatfrontier
$3.00/ $15.00
in / out per 1M
EST Jul 2026
—1.2s70 t/s256K
88

OpenRouter — Frequently Asked Questions (FAQs)

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OpenRouter LLM pricing overview

OpenRouter is an inference API provider that hosts open-weight and third-party large language models. OpenRouter is a unified LLM API that routes requests to the cheapest or fastest available provider for any given model. With a single API key you can access GPT-5.6 Sol, Claude 5, Llama 4, Gemini 3.x, DeepSeek V4 Pro, and 300+ other models, with automatic fallback and cost optimisation. The catalog has grown significantly in 2026 with the addition of Chinese frontier models. Common use cases include Multi-model applications, Cost optimisation, Provider fallback, Prototyping. Headquartered in San Francisco, CA, founded 2023. All models are accessible via a REST API compatible with standard OpenAI-style request formats, enabling drop-in integration with most LLM frameworks and orchestration tools.

OpenRouter vs other LLM providers

OpenRouter competes with OpenAI, Anthropic, Google, Groq, Together AI, Mistral, Cohere, and other inference API providers across dimensions of price, throughput, latency, context window, and model intelligence. A unified API for accessing major LLMs — including Chinese frontier models — with a single key and automatic routing to the cheapest or fastest available provider. Use the LLM provider comparison tool to see OpenRouter token pricing, latency, and throughput side-by-side with any other provider. The full LLM pricing table shows all providers ranked by input token cost, output token cost, and throughput in a single sortable view.

Why choose OpenRouter?

OpenRouter stands out because: A unified API for accessing major LLMs — including Chinese frontier models — with a single key and automatic routing to the cheapest or fastest available provider.. The API currently offers 22 models, spanning 6 frontier, 6 advanced, 6 efficient, 4 budget tiers. For teams running high-volume inference workloads, prompt caching and batch API endpoints can reduce effective input token costs by 50–90% — check the context window cost guide for a full breakdown of caching economics.

Understanding OpenRouter token pricing

OpenRouter charges separately for input (prompt) and output (completion) tokens, priced per 1M tokens in USD. Output tokens are typically 3–5× more expensive than input tokens due to the compute cost of autoregressive generation. The cheapest {meta.name} input rate is currently $0.03/1M tokens. Prices shown are sourced from OpenRouter's public pricing page and updated every 15 minutes. Need help estimating your spend? Read the LLM API cost calculator guide — it covers tokens, context windows, prompt caching, and batch discounts with worked examples for RAG, chat history, and document processing workloads.

OpenRouter context window and model capabilities

Context window size directly affects both capability and cost — every token in the context window is charged as an input token. OpenRouter's largest context window is 1.1M tokens. For RAG and document processing workloads, longer context windows enable richer retrieval but increase per-call costs proportionally. Prompt caching — where supported — stores the KV state of repeated prefixes and charges 75–90% less for cache hits, making it the most impactful cost optimization for applications with consistent system prompts or retrieved documents. See the LLM context window cost guide for a full analysis of how context length affects your API bill.

Self-hosted vs managed inference: when OpenRouter makes sense

Managed inference APIs like OpenRouter eliminate infrastructure overhead — no GPU provisioning, driver management, or model serving stack to maintain. The trade-off is cost at scale: a single H100 at ~$2.50/hr can serve ~500K tokens/min of Llama 3.3 70B, which at OpenRouter API rates would cost significantly more per token. The break-even point depends on your request volume, latency requirements, and engineering capacity. For teams processing fewer than ~10M tokens/day, managed APIs are almost always cheaper when total cost of ownership is considered. Above that threshold, self-hosted inference on rented GPU compute typically wins on unit economics. Read the cheapest GPU cloud guide for a full break-even analysis. Historical OpenRouter token price data is available in the LLM price history charts.

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