Description
️ Tool Name: 🖼
Parasail
Categories: 🔖
Programming and Development, Documentation and Software Development Kits, Integrations and APIs, Predictive Analytics and Applied Machine Learning, Data and Analytics, Automation and Smart Agents, Performance and Performance Optimization.
️ What does this tool offer? ✏
Parasail offers an Inference Cloud tailored for AI-driven startups, with a focus on reliability, performance, and scalability. The platform states that it serves trillions of tokens daily,provides Day 0 support for cutting-edge large language models (LLMs),and is up to 30 times cheaper than legacy clouds. It features a model library containing over 40 open and frontier models,with the ability to filter models, compare their specifications, and invoke them through a single OpenAI-compatible API.Among the models offered are GLM-5.3 from Z.AI,Kimi K3 from Moonshot,DeepSeek V4 Flash,and MiniMax M3. It also provides agentic optimization to balance speed, quality, and cost, using lossless compression by default and avoiding hidden quantization,with the option to enable lossy acceleration when needed. It also offers flexible drawdown billing for a single commitment across models or hardware,and elastic endpoints that scale according to actual traffic, so users pay only for the tokens they use. It also provides access to open models and user-specific fine-tunes through a single API interface, offering options for serverless endpoints, elastic endpoints,dedicated deployments, andbatch processing.
What does it actually offer based on user experience? ⭐
The information provided does not include verified independent user reviews or ratings, so no conclusions can be drawn about the user experience. According to the information provided, Parasail allows you to run any open model—whether popular or specialized—with the ability to use models via an OpenAI-compatible API, in addition to flexible inference options and scalability based on usage.
Does it include automation? 🤖
Yes, Parasail includes Agentic optimization, where an optimizer adjusts the deployment process to achieve the desired balance between speed, quality, and cost. Elastic Endpoints also automatically scales based on actual traffic, providing computing power when demand is high and reducing resources when it is low. It also offers Batch for high-throughput offline tasks and supports user-specific fine-tuned models.
Pricing Model: 💰
Based on a “Pay as you go” and“Reserved capacity” system, with options for Serverless endpoints,Elastic endpoints,Dedicated deployments, andBatch. Serverless endpoints are based on per-token access with no minimum, while Elastic endpoints are priced per million tokens, and Dedicated deployments provide reserved GPU units under Reserved Capacity. Batch offers the lowest cost per token for high-throughput, non-connected tasks.
🆓 Free plan details:
| Item | Details |
|---|---|
| Free Plan | No free plan is mentioned in the information provided |
| Usage | Pay as you go |
| Minimum | No minimums |
| Serverless endpoints | Pay-as-you-go per token |
| Community support | Available with Serverless endpoints |
| Models | Over 40+ open and frontier models, as described by the platform |
Paid plan details: 💳
| Option | Pricing | Features and Usage |
|---|---|---|
| Serverless endpoints | Per-token access | Over 2 million open models, call endpoints without setup, no minimums, community support, pay only for tokens used, no rate limits |
| Elastic endpoints | Per million tokens — Early access | Private, optimized endpoints; per-workload tuning; dedicated support |
| Dedicated deployments | Reserved capacity | Reserved GPU units sized according to the user’s roadmap, Negotiated latency SLA, Dedicated support |
| Batch | Lowest rate | Lowest cost per token, millions of requests per job, designed for high-throughput offline tasks, and suitable for evaluations and embeddings |
For Serverless endpoints,pricing per 1M tokens varies by model and usage type as follows:
| Model | Input / 1M tokens | Output / 1M tokens | Cache read / 1M tokens |
|---|---|---|---|
| Kimi K3 | $3.00 | $15.00 | $0.30 |
| Kimi K2.7 Code | $0.75 | $3.50 | $0.16 |
| Kimi K2.6 | $0.75 | $3.50 | $0.16 |
| GLM-5.3 Flash | $0.15 | $0.50 | $0.03 |
| GLM-5.3 | $1.40 | $4.40 | $0.26 |
| GLM-5.2 | $1.40 | $4.40 | $0.26 |
| GLM-5.1 | $1.40 | $4.40 | $0.26 |
| GLM-5 | $1.00 | $3.20 | $0.20 |
| MiniMax M3 | $0.30 | $1.20 | $0.06 |
| MiniMax M2.5 | $0.30 | $1.20 | $0.03 |
| DeepSeek V4 Pro | $1.74 | $3.48 | $0.10 |
| DeepSeek V4 Flash | $0.14 | $0.28 | $0.07 |
| DeepSeek V4.1 Flash | $0.30 | $1.20 | $0.006 |
| Qwen3.6 35B-A3B | $0.15 | $1.00 | $0.05 |
| Qwen3.5 397B-A17B | $0.50 | $3.60 | $0.30 |
| Qwen3.5 35B-A3B | $0.15 | $1.00 | $0.05 |
| Qwen3-Coder-Next | $0.12 | $0.80 | $0.07 |
| Qwen3-VL 235B-A22B | $0.21 | $1.90 | $0.10 |
| Qwen3-VL 8B | $0.25 | $0.75 | $0.12 |
| Qwen3-Next 80B | $0.10 | $1.10 | $0.07 |
| Qwen3 235B-A22B (2507) | $0.14 | $0.80 | $0.05 |
| Qwen2.5-VL 72B | $0.80 | $1.00 | $0.40 |
| Mistral Small 3.2 24B | $0.09 | $0.30 | $0.05 |
| Llama 4 Maverick (FP8) | $0.35 | $1.00 | $0.17 |
| Llama 3.3 70B (FP8) | $0.22 | $0.50 | $0.11 |
| Nemotron 3 Ultra 550B (NVFP4) | $0.50 | $2.50 | $0.10 |
| MiMo v2.5 | $0.14 | $0.28 | $0.05 |
| Resemble TTS (English) | $18.50 | — | — |
| Trinity Large (Thinking) | $0.22 | $0.85 | $0.06 |
| Gemma 4 26B-A4B | $0.13 | $0.40 | $0.05 |
| Gemma 4 31B | $0.15 | $0.40 | $0.06 |
| Skyfall 31B v4.2 | $0.55 | $0.80 | $0.25 |
| Cydonia 24B v4.1 | $0.30 | $0.50 | $0.15 |
| gpt-oss-120b | $0.10 | $0.75 | $0.055 |
| gpt-oss-120b (Fast) | $0.15 | $0.60 | — |
| gpt-oss-20b | $0.04 | $0.20 | $0.02 |
| UI-TARS 1.5 7B | $0.10 | $0.20 | $0.10 |
| Gemma 3 27B | $0.08 | $0.45 | $0.04 |
| Skyfall 36B v2 (FP8) | $0.55 | $0.80 | $0.25 |
| BGE-M3 | $0.01 | — | — |
How to access the tool: 🧭
| How to Access | Details |
|---|---|
| Web | Available via the Parasail website |
| API | One OpenAI-compatible API for accessing models |
| Docs | Parasail documentation is available on the website |
| Application | Not mentioned in the provided information |
| Add | Not mentioned in the information provided |
Link to the experience or official website: 🔗