Parasail
Inference host · 33 models · 39 priced routes · parasail.io
Models on Parasail
| Model | In / out per 1M | Vs headline | |
|---|---|---|---|
| $0.03 / $0.03+43% vs headline | +43% | fp8 · A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. | |
| $0.04 / $0.05Same vs headline | Same | bf16 · Gemma 3 introduces multimodality, supporting vision-language input and text outputs. | |
| $0.03 / $0.15+728% vs headline | +728% | fp4 · gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. | |
| $0.05 / $0.33Same vs headline | Same | bf16 · Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. | |
| $0.1 / $0.25+49% vs headline | +49% | bf16 · Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. | |
| $0.09 / $0.3+34% vs headline | +34% | bf16 · Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. | |
| $0.08 / $0.45+72% vs headline | +72% | fp8 · Gemma 3 introduces multimodality, supporting vision-language input and text outputs. | |
| $0.14 / $0.28+96% vs headline | +96% | fp8 · DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. | |
| $0.14 / $0.28+56% vs headline | +56% | fp8 · DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. | |
| $0.13 / $0.4+132% vs headline | +132% | bf16 · Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. | |
| $0.15 / $0.4+33% vs headline | +33% | fp8 · Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. | |
| $0.15 / $0.5+389% vs headline | +389% | fp4 · GLM-5.3-Flash is a native multimodal model from Z.ai. | |
| $0.1 / $0.75+1467% vs headline | +1467% | fp4 · gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. | |
| $0.12 / $0.8Same vs headline | Same | bf16 · Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. | |
| $0.22 / $0.5+87% vs headline | +87% | fp8 · The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). | |
| $0.188 / $0.625+511% vs headline | +511% | fast, fp4 · GLM-5.3-Flash is a native multimodal model from Z.ai. | |
| $0.15 / $0.75+1691% vs headline | +1691% | fast, fp4 · gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. | |
| $0.1 / $0.9+525% vs headline | +525% | fp8 · Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. | |
| $0.14 / $0.8+49% vs headline | +49% | fp8 · Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. | |
| $0.1 / $1.1+28% vs headline | +28% | fp8 · Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. |
About Parasail
Across GlyphCompany profileFunding roundssocials