Community: K2-Think
k2-think
K2-Think costs $0.221 per million input tokens and $0.884 per million output tokens, supports 128K context, and is available through the OpenAI-compatible API.
K2-Think is a 32B open-weights general reasoning model with strong competitive math performance. Benchmarks: AIME 2024 90.83, AIME 2025 81.24, GPQA-Diamond 71.08, LiveCodeBench v5 63.97.
Modalities
Text → Text
Input / output price
$0.221 / $0.884 per 1M
Context
128K · max output 33K
Capabilities
Pricing
Billed per token actually used and deducted from your credits.
| Item | USD per 1M tokens |
|---|---|
| Input | $0.221 |
| Output | $0.884 |
| Cached input | $0.111 |
Calculator
Drag the sliders to estimate what this model will cost.
- Per request
- $0.00137
- Per day
- $0.6851
- Per month (30 days)
- $20.55
K2-Think: input $0.221/M · output $0.884/M · cached input $0.1105/M
curl https://api.geniusrelaygpt.com/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "k2-think", "max_tokens": 800,
"messages": [{"role": "user", "content": "…"}]}'Code samples
OpenAI-compatible. Set the base URL to https://api.geniusrelaygpt.com/v1 and the model to k2-think.
curl https://api.geniusrelaygpt.com/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "k2-think",
"stream": true,
"messages": [{"role": "user", "content": "Hello"}]
}'Use it in a client: Cursor · Cline · SillyTavern · Codex
Parameters
Common OpenAI parameters can be passed as-is.
temperaturetop_pmax_tokensstreamstoppresence_penaltyfrequency_penaltyseedFAQ
- How is K2-Think billed?
- Input is $0.221 and output is $0.884 per million tokens; cached input is $0.111. The charge for every request is listed in Usage Logs in the console.
- How long is the context window?
- 128K tokens. In a long conversation every turn is billed for the full input, so keep the history under control.
- Does it support streaming?
- Yes. Add "stream": true to the request to receive server-sent events in the OpenAI format.