37 models. LLaMA, Mixtral, Gemma on Groq inference hardware. Prices per 1M tokens in USD.
Cheapest input
$0.04/1M
llama-3.2-1b-preview
Most expensive input
$1/1M
kimi-k2-instruct-0905
Models with cache pricing
7 of 37
| Model | Input $/1M | Output $/1M | Cache $/1M |
|---|---|---|---|
| llama-3.2-1b-preview | $0.04 | $0.04 | - |
| llama-3.1-8b-instant | $0.05 | $0.08 | - |
| llama3-8b-8192 | $0.05 | $0.08 | - |
| llama-3.2-3b-preview | $0.06 | $0.06 | - |
| gemma-7b-it | $0.07 | $0.07 | - |
| openai/gpt-oss-20b | $0.075 | $0.3 | $0.0375 |
| gpt-oss-20b | $0.075 | $0.3 | $0.0375 |
| gpt-oss-safeguard-20b | $0.075 | $0.3 | $0.037 |
| meta-llama/llama-4-scout-17b-16e-instruct | $0.11 | $0.34 | - |
| llama-4-scout-17b-16e-instruct | $0.11 | $0.34 | - |
| openai/gpt-oss-120b | $0.15 | $0.6 | $0.075 |
| gpt-oss-120b | $0.15 | $0.6 | $0.075 |
| llama-3.2-11b-text-preview | $0.18 | $0.18 | - |
| llama-3.2-11b-vision-preview | $0.18 | $0.18 | - |
| llama3-groq-8b-8192-tool-use-preview | $0.19 | $0.19 | - |
| gemma2-9b-it | $0.2 | $0.2 | - |
| llama-guard-3-8b | $0.2 | $0.2 | - |
| meta-llama/llama-4-maverick-17b-128e-instruct | $0.2 | $0.6 | - |
| meta-llama/llama-guard-4-12b | $0.2 | $0.2 | - |
| llama-guard-4-12b | $0.2 | $0.2 | - |
| llama-4-maverick-17b-128e-instruct | $0.2 | $0.6 | - |
| mixtral-8x7b-32768 | $0.24 | $0.24 | - |
| qwen/qwen3-32b | $0.29 | $0.59 | - |
| qwen3-32b | $0.29 | $0.59 | - |
| llama-3.3-70b-versatile | $0.59 | $0.79 | - |
| llama-3.1-405b-reasoning | $0.59 | $0.79 | - |
| llama-3.1-70b-versatile | $0.59 | $0.79 | - |
| llama-3.3-70b-specdec | $0.59 | $0.99 | - |
| llama3-70b-8192 | $0.59 | $0.79 | - |
| llama2-70b-4096 | $0.7 | $0.8 | - |
| deepseek-r1-distill-llama-70b | $0.75 | $0.99 | - |
| mistral-saba-24b | $0.79 | $0.79 | - |
| llama3-groq-70b-8192-tool-use-preview | $0.89 | $0.89 | - |
| llama-3.2-90b-text-preview | $0.9 | $0.9 | - |
| llama-3.2-90b-vision-preview | $0.9 | $0.9 | - |
| moonshotai/kimi-k2-instruct | $1 | $3 | $0.5 |
| kimi-k2-instruct-0905 | $1 | $3 | $0.5 |
Proxy your Groq requests through LLMKit. Every call gets logged with token counts, dollar costs, and session attribution. Set budget limits that actually reject requests before they hit the provider.
MIT licensed. Built with Claude Code. Source on GitHub