Pricing · ArbitrageUpdated 2026-10-16 · 150 models with 2+ providers
Same Model · Different Price
Every model sold by two or more providers, ranked by how much the input price varies between the cheapest and most expensive offer.
| Model | Providers | Cheapest input | Spread |
|---|---|---|---|
| GLM 5.2 | 25 | $0.035 Relace | 7,023% |
| Qwen3.8 27B | 20 | $0.020 Tenstorrent · fp4 | 4,850% |
| GLM 5.3 | 34 | $0.061 Relace | 4,505% |
| DeepSeek V4 Flash 0731 | 24 | $0.011 Relace · fp4 | 3,864% |
| DeepSeek V4.1 Flash | 30 | $0.036 OpenInference · fp4 | 1,567% |
| Kimi K3 | 20 | $0.29 Wafer · mxfp4 | 1,431% |
| DeepSeek V3.2 | 12 | $0.21 GMICloud · fp8 | 1,337% |
| DeepSeek V4 Flash | 16 | $0.045 OpenInference · fp4 | 1,189% |
| GPT-6.1 Sol | 3 | $1.00 OpenAI | 1,100% |
| GPT-6.1 Sol Pro | 2 | $1.00 OpenAI | 1,100% |
| GPT-6 Astra | 3 | $5.00 OpenAI | 1,100% |
| GPT-6 Astra Pro | 2 | $5.00 OpenAI | 1,100% |
| GLM 5.3 Flash | 30 | $0.021 OpenInference · fp4 | 1,082% |
| gpt-oss-120b | 22 | $0.030 AkashML · bf16 | 1,067% |
| Llama 3.1 8B Instruct | 5 | $0.020 DeepInfra · fp8 | 1,000% |
| Llama 3.3 70B Instruct | 10 | $0.10 DeepInfra · fp8 | 940% |
| Mistral Nemo | 5 | $0.017 Io Net · fp16 | 806% |
| Gemma 4 31B | 12 | $0.10 CoreWeave · fp4 | 650% |
| DeepSeek V4 Pro 0813 | 20 | $0.25 Wafer · mxfp4 | 560% |
| GPT-5.5 | 3 | $2.50 OpenAI | 400% |
| MythoMax 13B | 3 | $0.080 Parasail · fp16 | 400% |
| Qwen3.6 35B A3B | 10 | $0.050 Darkbloom · fp4 | 400% |
| DeepSeek V4 Pro | 15 | $0.45 Parasail · fp8 | 324% |
| gpt-oss-20b | 10 | $0.018 Darkbloom · fp8 | 317% |
| GPT-5.1 | 2 | $0.63 OpenAI | 300% |
| GPT-5.2 | 2 | $0.88 OpenAI | 300% |
| GPT-5.4 | 3 | $1.25 OpenAI | 300% |
| GPT-5.4 Mini | 2 | $0.38 OpenAI | 300% |
| GPT-5.6 Luna | 3 | $0.10 OpenAI | 300% |
| GPT-5.6 Luna Pro | 2 | $0.10 OpenAI | 300% |
| GPT-5.6 Sol | 3 | $2.00 OpenAI | 300% |
| GPT-5.6 Sol Pro | 2 | $2.00 OpenAI | 300% |
| GPT-5.6 Terra | 3 | $1.00 OpenAI | 300% |
| GPT-5.6 Terra Pro | 2 | $1.00 OpenAI | 300% |
| GPT-6 Luna | 3 | $0.050 OpenAI | 300% |
| GPT-6 Luna Pro | 2 | $0.050 OpenAI | 300% |
| GPT-6 Sol | 3 | $1.00 OpenAI | 300% |
| GPT-6 Sol Pro | 2 | $1.00 OpenAI | 300% |
| Nemotron 3 Super | 3 | $0.080 DekaLLM · fp8 | 275% |
| Qwen3.5-35B-A3B | 7 | $0.065 Darkbloom · fp4 | 269% |
| Gemini 2.5 Flash | 2 | $0.15 Google AI Studio | 260% |
| Gemini 2.5 Flash Lite | 2 | $0.050 Google AI Studio | 260% |
| Gemini 2.5 Pro | 2 | $0.63 Google AI Studio | 260% |
| Gemini 2.5 Pro Preview 06-05 | 2 | $0.63 Google AI Studio | 260% |
| Gemini 2.5 Pro Preview 05-06 | 2 | $0.63 Google AI Studio | 260% |
| Gemini 3.1 Flash Lite | 2 | $0.13 Google | 260% |
| Gemini 3.1 Pro Preview | 2 | $1.00 Google | 260% |
| Gemini 3.5 Flash | 2 | $0.75 Google | 260% |
| Gemini 3.5 Flash Lite | 2 | $0.15 Google | 260% |
| Gemini 3.6 Flash | 2 | $0.38 Google | 260% |
| Gemini 3.7 Flash | 2 | $0.38 Google | 260% |
| Gemini 3.8 Flash | 2 | $0.38 Google | 260% |
| Gemini 3 Flash Preview | 2 | $0.25 Google | 260% |
| Gemini 4 Argon | 2 | $1.00 Google AI Studio | 260% |
| Gemma 4 26B A4B | 13 | $0.042 Darkbloom | 257% |
| MiMo-V2.5 | 5 | $0.12 GMICloud · fp8 | 236% |
| Llama 4 Scout | 3 | $0.080 DeepInfra · fp8 | 212% |
| MiniMax M2.7 | 5 | $0.21 GMICloud · fp8 | 186% |
| Kimi K2.7 Code | 12 | $0.67 Inceptron · int4 | 183% |
| Nemotron 3.5 Lightning | 4 | $0.025 Darkbloom · int4 | 180% |
| MiniMax M3 | 13 | $0.22 DeepInfra · fp8 | 168% |
| DeepSeek V3.1 | 5 | $0.25 DeepInfra · fp4 | 160% |
| Qwen3 235B A22B Instruct 2507 | 6 | $0.087 GMICloud · fp8 | 151% |
| Nemotron 3.5 Super VL | 5 | $0.10 Crusoe · bf16 | 150% |
| Kimi K2.6 | 17 | $0.44 Inceptron · int4 | 147% |
| MiniMax M2.5 | 8 | $0.27 StreamLake | 122% |
| GPT-5.4 Nano | 2 | $0.10 OpenAI | 120% |
| GPT-5 Mini | 2 | $0.13 OpenAI | 120% |
| GPT-5 Nano | 2 | $0.025 OpenAI | 120% |
| GLM 4.7 | 6 | $0.32 DeepInfra · fp4 | 119% |
| Qwen3.5-9B | 6 | $0.080 Darkbloom · fp4 | 113% |
| Qwen3 Next 80B A3B Instruct | 3 | $0.072 DeepInfra · fp8 | 108% |
| DeepSeek V4 Flash Vision Exp | 3 | $0.22 DeepInfra · fp8 | 104% |
| Claude Opus 4.8 | 5 | $5.00 Amazon Bedrock | 100% |
| Claude Opus 5 | 5 | $5.00 Amazon Bedrock | 100% |
| Claude Opus 5.5 | 5 | $4.00 Amazon Bedrock | 100% |
| GPT-5.3-Codex | 2 | $1.75 Azure | 100% |
| GPT-5.4 Pro | 2 | $15.00 OpenAI | 100% |
| Grok 4.6 | 2 | $2.00 xAI | 100% |
| Qwen3 VL 30B A3B Instruct | 3 | $0.15 DeepInfra · fp8 | 93% |
| Qwen3.5 397B A17B | 10 | $0.39 Alibaba | 92% |
| Gemma 3 12B | 2 | $0.040 DeepInfra · bf16 | 87% |
| Llama 4 Maverick | 4 | $0.19 DigitalOcean | 87% |
| Llama 3.1 70B Instruct | 2 | $0.40 DeepInfra · fp8 | 80% |
| Qwen3.6 27B | 7 | $0.25 Chutes · fp8 | 80% |
| MiMo-V2.6-Flash | 8 | $0.10 Darkbloom · fp4 | 75% |
| Qwen3 32B | 3 | $0.080 DeepInfra · fp8 | 75% |
| MiMo-V2.5-Pro | 6 | $0.30 GMICloud · bf16 | 71% |
| GLM 5 | 8 | $0.60 GMICloud · fp8 | 67% |
| Granite 4.2 8B | 2 | $0.060 DeepInfra · bf16 | 67% |
| Qwen3 Coder 480B A35B | 3 | $0.22 Google | 59% |
| Nemotron 3 Ultra | 3 | $0.40 DeepInfra · fp4 | 56% |
| GLM 4.5 Air | 3 | $0.13 Novita · bf16 | 54% |
| Qwen3.5-122B-A10B | 4 | $0.26 Alibaba | 54% |
| Qwen3.5-27B | 7 | $0.20 Alibaba | 54% |
| Hy3 | 5 | $0.13 Tencent · fp8 | 52% |
| GLM 4.6 | 4 | $0.40 DeepInfra · fp4 | 50% |
| Gemma 3 27B | 5 | $0.080 DeepInfra · fp8 | 49% |
| GLM 5.1 | 13 | $0.97 StreamLake · fp8 | 45% |
| R1 0528 | 4 | $0.50 DeepInfra · fp4 | 40% |
| MiniMax M1 | 2 | $0.40 Minimax | 38% |
| Mistral Small 3.2 24B | 4 | $0.075 DeepInfra · fp8 | 33% |
| ReMM SLERP 13B | 2 | $0.35 Mancer 2 · fp8 | 29% |
| DeepSeek V3.1 Terminus | 2 | $0.27 SiliconFlow · fp8 | 27% |
| DeepSeek V3 | 2 | $0.26 DeepInfra · fp4 | 25% |
| Gemma 3 4B | 2 | $0.040 Parasail · bf16 | 25% |
| Kimi K2.5 | 5 | $0.49 AtlasCloud · int4 | 22% |
| GLM 5.3 Flash (batch) | 2 | $0.050 Sail Research · fp4 | 20% |
| Nemotron 3 Nano 30B A3B | 2 | $0.050 Novita · fp4 | 20% |
| Qwen3 14B | 2 | $0.10 NextBit · int4 | 20% |
| MiniMax M2 | 2 | $0.26 Minimax · fp8 | 18% |
| GLM 4.7 Flash | 3 | $0.060 Venice · fp8 | 17% |
| DeepSeek V3 0324 | 2 | $0.25 SiliconFlow · fp8 | 16% |
| Qwen3 30B A3B Instruct 2507 | 3 | $0.090 DekaLLM | 11% |
| Claude Fable 5 | 5 | $10.00 Amazon Bedrock | 10% |
| Claude Haiku 4.5 | 4 | $1.00 Amazon Bedrock | 10% |
| Claude Haiku 5.5 | 5 | $0.10 Amazon Bedrock | 10% |
| Claude Opus 4.5 | 5 | $5.00 Amazon Bedrock | 10% |
| Claude Opus 4.6 | 5 | $5.00 Amazon Bedrock | 10% |
| Claude Opus 4.7 | 5 | $5.00 Amazon Bedrock | 10% |
| Claude Sonnet 4.5 | 5 | $3.00 Amazon Bedrock | 10% |
| Claude Sonnet 4.6 | 5 | $3.00 Amazon Bedrock | 10% |
| Claude Sonnet 5 | 5 | $2.00 Amazon Bedrock | 10% |
| Claude Sonnet 5.5 | 5 | $2.00 Amazon Bedrock | 10% |
| Nano Banana 2 (Gemini 3.1 Flash Image) | 2 | $0.50 Google | 10% |
| GPT-4.1 | 2 | $2.00 Azure | 10% |
| GPT-4.1 Mini | 2 | $0.40 Azure | 10% |
| GPT-4.1 Nano | 2 | $0.10 Azure | 10% |
| GPT-4o-mini | 2 | $0.15 Azure | 10% |
| GPT-5 | 2 | $1.25 Azure | 10% |
| Qwen3 VL 235B A22B Instruct | 3 | $0.20 DeepInfra · fp8 | 5% |
| Hy4 preview | 5 | $0.80 Makora · fp8 | 4% |
| Llama 3.2 3B Instruct | 2 | $0.050 Parasail · bf16 | 2% |
| MiMo-V2.6-Pro | 4 | $0.43 DeepInfra · fp8 | 1% |
| Claude Fable 5.1 | 4 | $10.00 Amazon Bedrock | 0% |
| Gemini 2.5 Flash Lite (batch) | 2 | $0.050 Google | 0% |
| Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) | 2 | $0.25 Google | 0% |
| Nano Banana Pro (Gemini 3 Pro Image) | 2 | $2.00 Google | 0% |
| GLM 4.5V | 2 | $0.60 Novita · fp8 | 0% |
| GLM 4.6V | 2 | $0.30 Novita · bf16 | 0% |
| GPT-3.5 Turbo 16k | 2 | $3.00 Azure | 0% |
| GPT-4 | 2 | $30.00 Azure | 0% |
| GPT-4o | 2 | $2.50 Azure | 0% |
| GPT-4o (2024-05-13) | 2 | $5.00 Azure | 0% |
| GPT-4o (2024-08-06) | 2 | $2.50 Azure | 0% |
| Kimi K2 Thinking | 2 | $0.60 Google | 0% |
| Llama 3 8B Lunaris | 2 | $0.040 DeepInfra · fp8 | 0% |
| Qwen3.8 2.4T A95B | 5 | $2.00 Alibaba | 0% |
| Step 3.7 Flash | 2 | $0.20 Novita · fp8 | 0% |
| Step 5 Preview | 4 | $1.00 DeepInfra · fp8 | 0% |
Prices in USD per million input tokens · OpenRouter provider list prices, collected daily · some offers are quantized (lower precision).
Frequently Asked Questions
Many open-weight and some proprietary models are served by several providers at different prices. Routing to the cheapest provider that meets your uptime, context and quantization needs can cut costs sharply.