# Pera Pera sells inference on Liquid Inference. A buyer names one of its models as pera/\, or names the model and pays the lowest offer that meets the buyer's rules. ## Facts - Handle: pera - Website: https://primaera.xyz/ - On the exchange since: 2026-10-10 - Models: 35 - Offers: 36 - Regions: asia, us - Precisions (declared): bf16, fp4, fp8, mxfp4, provider-managed - Lowest price on: 27 of 35 models ## Reliability, last 3 days - Probes answered: 99.32% - Hours with an answer: 100.0% - Median response time: 2.8s ## Checked by the exchange 14 of 36 offers match the fingerprint of the model. 1 has a finished evaluation. The exchange sends fixed prompts to each offer and compares the answers with a baseline for the model. It also runs benchmarks against the offers and keeps the results. ## Data handling - Zero retention, declared by the provider - No training, declared by the provider ## Models - [DeepSeek V3.2](https://liquidinference.ai/models/deepseek-v3.2.md): declared precision fp4, us, $0.325 input and $0.475 output per million tokens, $0.325 cache read per million tokens, 160K tokens of context - [DeepSeek V4 Flash](https://liquidinference.ai/models/deepseek-v4-flash.md): declared precision fp8, us, $0.140 input and $0.280 output per million tokens, $0.140 cache read per million tokens, $0.00057 fee for each request, 1M tokens of context - [DeepSeek V4 Flash 0731](https://liquidinference.ai/models/deepseek-v4-flash-0731.md): declared precision fp8, us, $0.027 input and $0.0018 output per million tokens, $0.027 cache read per million tokens, $0.000077 fee for each request, 1M tokens of context - [DeepSeek V4 Pro](https://liquidinference.ai/models/deepseek-v4-pro.md): declared precision fp8, us, $2.475 input and $3.005 output per million tokens, $2.475 cache read per million tokens, $0.0025 fee for each request, 1M tokens of context - [DeepSeek V4.1 Flash](https://liquidinference.ai/models/deepseek-v4.1-flash.md): declared precision fp8, us, $0.097 input and $0.0084 output per million tokens, $0.097 cache read per million tokens, 1M tokens of context - [DeepSeek V4.1 Flash 1017:thinking](https://liquidinference.ai/models/deepseek-v4.1-flash-1017%3Athinking.md): declared precision fp8, us, $0.354 input and $0.012 output per million tokens, $0.354 cache read per million tokens, $0.0016 fee for each request, 1M tokens of context - [DeepSeek V4.1 Flash:thinking](https://liquidinference.ai/models/deepseek-v4.1-flash%3Athinking.md): declared precision fp8, us, $0.405 input and $0.0099 output per million tokens, $0.405 cache read per million tokens, $0.0043 fee for each request, 1M tokens of context - [Gemma 3 27B It](https://liquidinference.ai/models/gemma-3-27b-it.md): declared precision fp8, us, $0.100 input and $0.200 output per million tokens, $0.100 cache read per million tokens, 40K tokens of context - [GLM 4.7](https://liquidinference.ai/models/glm-4.7.md): declared precision fp4, us, $0.750 input and $2.750 output per million tokens, $0.750 cache read per million tokens, 128K tokens of context - [GLM 5.2](https://liquidinference.ai/models/glm-5.2.md): declared precision fp4, us, $0.563 input and $1.800 output per million tokens, $0.563 cache read per million tokens, $0.02 fee for each request, 1M tokens of context - [GLM 5.3](https://liquidinference.ai/models/glm-5.3.md): declared precision fp4, us, $0.285 input and $1.995 output per million tokens, $0.285 cache read per million tokens, $0.02 fee for each request, 1M tokens of context - [GLM 5.3 Flash](https://liquidinference.ai/models/glm-5.3-flash.md): declared precision fp4, us, $0.150 input and $0.137 output per million tokens, $0.150 cache read per million tokens, $0.00065 fee for each request, 1M tokens of context - [GPT 5.6 Sol](https://liquidinference.ai/models/gpt-5.6-sol.md): declared precision provider-managed, us, $5.000 input and $37.500 output per million tokens, $5.000 cache read per million tokens, 1M tokens of context - [GPT 6 Astra](https://liquidinference.ai/models/gpt-6-astra.md): declared precision provider-managed, us, $30.000 input and $112.500 output per million tokens, $30.000 cache read per million tokens, $0.02 fee for each request, 1M tokens of context - [GPT 6 Luna](https://liquidinference.ai/models/gpt-6-luna.md): declared precision provider-managed, us, $0.125 input and $0.938 output per million tokens, $0.125 cache read per million tokens, 1M tokens of context - [GPT 6 Sol](https://liquidinference.ai/models/gpt-6-sol.md): declared precision provider-managed, us, $2.500 input and $18.750 output per million tokens, $2.500 cache read per million tokens, 1M tokens of context - [GPT 6.1 Sol](https://liquidinference.ai/models/gpt-6.1-sol.md): declared precision provider-managed, us, $2.910 input and $7.104 output per million tokens, $2.910 cache read per million tokens, $0.02 fee for each request, 1M tokens of context - [GPT: OSS 120B](https://liquidinference.ai/models/gpt-oss-120b.md): declared precision bf16, us, $0.037 input and $0.0034 output per million tokens, $0.037 cache read per million tokens, $0.00017 fee for each request, 122.9K tokens of context - [GPT: OSS 20B](https://liquidinference.ai/models/gpt-oss-20b.md): declared precision bf16, us, $0.037 input and $0.175 output per million tokens, $0.037 cache read per million tokens, 122.9K tokens of context - [hy4 Preview](https://liquidinference.ai/models/hy4-preview.md): declared precision fp8, us, $1.042 input and $3.126 output per million tokens, $1.042 cache read per million tokens, 991.8K tokens of context - [Kimi K3](https://liquidinference.ai/models/kimi-k3.md): declared precision mxfp4, asia, $1.800 input and $0.100 output per million tokens, $0.180 cache read per million tokens, $0.00025 fee for each request, 1M tokens of context, the cheapest of 2 offers - [Kimi K3.1 Pro](https://liquidinference.ai/models/kimi-k3.1-pro.md): declared precision provider-managed, us, $4.000 input and $20.000 output per million tokens, $4.000 cache read per million tokens, $0.02 fee for each request, 1M tokens of context - [Mimo V2.6 Flash](https://liquidinference.ai/models/mimo-v2.6-flash.md): declared precision fp8, us, $0.105 input and $0.0056 output per million tokens, $0.105 cache read per million tokens, $0.002 fee for each request, 1M tokens of context - [Mimo V2.6 Pro](https://liquidinference.ai/models/mimo-v2.6-pro.md): declared precision fp8, us, $0.652 input and $1.305 output per million tokens, $0.652 cache read per million tokens, $0.00046 fee for each request, 1M tokens of context - [MiniMax M3](https://liquidinference.ai/models/MiniMax-M3.md): declared precision fp8, us, $0.350 input and $1.375 output per million tokens, $0.350 cache read per million tokens, 516.1K tokens of context - [Mistral: Small 3.2 24B Instruct](https://liquidinference.ai/models/mistral-small-3.2-24b-instruct.md): declared precision fp8, us, $0.100 input and $0.0040 output per million tokens, $0.100 cache read per million tokens, $0.000049 fee for each request, 128K tokens of context - [Nemotron 3 Super 120B a12b](https://liquidinference.ai/models/nemotron-3-super-120b-a12b.md): declared precision bf16, us, $0.120 input and $0.346 output per million tokens, $0.120 cache read per million tokens, $0.00052 fee for each request, 254K tokens of context - [Nemotron 3 Ultra 550B a55b](https://liquidinference.ai/models/nemotron-3-ultra-550b-a55b.md): declared precision fp4, us, $0.450 input and $0.044 output per million tokens, $0.450 cache read per million tokens, $0.00057 fee for each request, 262.1K tokens of context - [Nemotron 3.5 Lightning](https://liquidinference.ai/models/nemotron-3.5-lightning.md): declared precision bf16, us, $0.053 input and $0.017 output per million tokens, $0.053 cache read per million tokens, $0.000072 fee for each request, 262.1K tokens of context - [Qwen 3 14B](https://liquidinference.ai/models/qwen3-14b.md): declared precision fp8, us, $0.087 input and $0.0048 output per million tokens, $0.087 cache read per million tokens, $0.000079 fee for each request, 32.8K tokens of context - [Qwen 3 Coder](https://liquidinference.ai/models/qwen3-coder.md): declared precision fp4, us, $0.375 input and $1.250 output per million tokens, $0.375 cache read per million tokens, 253.8K tokens of context - [Qwen 3 VL 235B a22b Instruct](https://liquidinference.ai/models/qwen3-vl-235b-a22b-instruct.md): declared precision fp8, us, $0.250 input and $1.100 output per million tokens, $0.250 cache read per million tokens, 256K tokens of context - [Qwen 3.5 397B a17b](https://liquidinference.ai/models/qwen3.5-397b-a17b.md): declared precision fp8, us, $0.500 input and $3.600 output per million tokens, $0.500 cache read per million tokens, $0.00048 fee for each request, 128K tokens of context - [Qwen 3.6 35B a3b](https://liquidinference.ai/models/qwen3.6-35b-a3b.md): declared precision fp8, us, $0.150 input and $0.125 output per million tokens, $0.150 cache read per million tokens, $0.00083 fee for each request, 262.1K tokens of context - [Qwen 3.8 27B](https://liquidinference.ai/models/qwen3.8-27b.md): declared precision bf16, us, $0.045 input and $0.013 output per million tokens, $0.045 cache read per million tokens, $0.000097 fee for each request, 262.1K tokens of context ## Related pages - [This page in a browser](https://liquidinference.ai/providers/f651491e-f85b-4f03-b80c-32876aeb80ce) - [All providers](https://liquidinference.ai/providers.md) - [All models](https://liquidinference.ai/models) - [Discover the best model for your budget](https://liquidinference.ai/discover) - [Quickstart](https://liquidinference.ai/docs/quickstart.md) - [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt) - [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)