Most Context Per Dollar
Models ranked by context window size relative to input token cost. Higher ratios mean more processing capacity for less money.
Methodology: Computed as context_window_tokens / input_price_per_1m. Only models with both values included. Higher is better.
| # | Model | Provider | Metric |
|---|---|---|---|
| 1 | Gemini 1.5 Flash | Google DeepMind | 13,333,333 tokens/$1 |
| 2 | Gemini 2.0 Flash | Google DeepMind | 6,666,667 tokens/$1 |
| 3 | Gemini 1.5 Pro | Google DeepMind | 1,600,000 tokens/$1 |
| 4 | Llama 3.3 70B | Meta | 1,280,000 tokens/$1 |
| 5 | GPT-4o mini | OpenAI | 853,333 tokens/$1 |
| 6 | Claude 3 Haiku | Anthropic | 800,000 tokens/$1 |
| 7 | DeepSeek V3 | DeepSeek | 474,074 tokens/$1 |
| 8 | Qwen 2.5 72B | Alibaba Cloud (Qwen) | 320,000 tokens/$1 |
| 9 | Claude 3.5 Haiku | Anthropic | 250,000 tokens/$1 |
| 10 | Mistral 7B | Mistral AI | 131,072 tokens/$1 |
| 11 | DeepSeek R1 | DeepSeek | 116,364 tokens/$1 |
| 12 | Claude 3 Sonnet | Anthropic | 66,667 tokens/$1 |
| 13 | Claude 3.5 Sonnet | Anthropic | 66,667 tokens/$1 |
| 14 | Claude Sonnet 4.6 | Anthropic | 66,667 tokens/$1 |
| 15 | Gemini 1.0 Pro | Google DeepMind | 65,536 tokens/$1 |
| 16 | Grok 2 | xAI | 65,536 tokens/$1 |
| 17 | GPT-4o | OpenAI | 51,200 tokens/$1 |
| 18 | Mixtral 8x7B | Mistral AI | 46,811 tokens/$1 |
| 19 | Mistral Large 2 | Mistral AI | 42,667 tokens/$1 |
| 20 | Command R+ | Cohere | 42,667 tokens/$1 |
| 21 | GPT-3.5 Turbo | OpenAI | 32,770 tokens/$1 |
| 22 | Llama 3.1 405B | Meta | 25,600 tokens/$1 |
| 23 | o1 | OpenAI | 13,333 tokens/$1 |
| 24 | Claude 3 Opus | Anthropic | 13,333 tokens/$1 |
| 25 | GPT-4 Turbo | OpenAI | 12,800 tokens/$1 |
| 26 | Claude 2 | Anthropic | 12,500 tokens/$1 |
| 27 | Llama 3 70B | Meta | 9,102 tokens/$1 |
| 28 | Llama 2 70B | Meta | 4,551 tokens/$1 |
| 29 | GPT-4 | OpenAI | 273 tokens/$1 |
| 30 | GPT-3 (davinci-002) | OpenAI | 68 tokens/$1 |